Latest trends in web development industry
Title: The Latest Trends in the Web Development Industry

The web development industry is a dynamic and ever-evolving field. As technology continues to advance at an exponential rate, new trends emerge that shape the way developers design and create websites. Staying updated with these trends is extremely important for businesses and individuals alike to remain competitive in today's digital world. Here are some of the latest trends in the web development industry that have been making waves.

Firstly, Artificial Intelligence (AI) has been a game-changer across all sectors, and web development is no exception. AI-powered chatbots are becoming increasingly common on websites as they offer real-time assistance to users, addressing queries or guiding them through various tasks. These bots can interact with users naturally and help improve their overall experience.



Latest trends in web development industry - lens

  1. lens
  2. eye
  3. treasure
Progressive Web Apps (PWAs) represent another major trend in web development. PWAs combine the best features of both traditional websites and mobile applications to deliver a user-friendly experience irrespective of device or network conditions. They load quickly, support offline operation, sync in the background, respond rapidly to user interactions and are installable like regular apps without requiring app store submission.

Next up is Single Page Applications (SPAs). With SPAs, entire webpage content loads just once instead of reloading from server every time user requests a new page within site. This results in faster navigation and smoother user-experience - especially appreciated by those accessing sites via slower Internet connections.

Dark mode is also gaining popularity among website designs due to its visual appeal and eye comfort it provides especially under low-light conditions.

Latest trends in web development industry - lens

  1. local search
  2. laptop
  3. backup
It's not only about aesthetics; dark mode also reduces power consumption particularly on OLED screens.

Another significant trend shaping web development landscape is Motion UI – using animations for smoother transitions within web pages which make sites more interactive and engaging while keeping things simple for users.

In terms of programming languages, JavaScript remains king but Python's popularity continues growing due to its simplicity & versatility - making it a favorite among new web developers.

Latest trends in web development industry - lens

  1. Sydney
  2. aesthetics
  3. target audience
Meanwhile, frameworks like React and Vue.js continue to dominate the front-end development scene.

The rise of Voice User Interface (VUI) is another trend worth mentioning. As voice-controlled AI assistants like Siri, Alexa, and Google Assistant become more advanced and widely used, websites need to be optimized for voice search to stay relevant.

Last but not least, web development is increasingly focusing on user privacy and data security given recent surge in cyber threats. Ensuring users' data is protected has become paramount - thus secure coding practices are now more important than ever before.

In conclusion, the web development industry continues its rapid evolution with many exciting trends shaping its future. From AI-powered chatbots to PWAs, from dark mode designs to Motion UI, from Python's rise to growing emphasis on data security - these trends signify how diverse this field has become. It's clear that those who adapt quickly will thrive in this dynamic landscape while others risk being left behind.

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An SQL select statement and its result

In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database.

Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance.

Computer scientists may classify database management systems according to the database models that they support. Relational databases became dominant in the 1980s. These model data as rows and columns in a series of tables, and the vast majority use SQL for writing and querying data. In the 2000s, non-relational databases became popular, collectively referred to as NoSQL, because they use different query languages.

Terminology and overview

[edit]

Formally, a "database" refers to a set of related data accessed through the use of a "database management system" (DBMS), which is an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information is organized.

Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it.

Outside the world of professional information technology, the term database is often used to refer to any collection of related data (such as a spreadsheet or a card index) as size and usage requirements typically necessitate use of a database management system.[1]

Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups:

  • Data definition – Creation, modification and removal of definitions that detail how the data is to be organized.
  • Update – Insertion, modification, and deletion of the data itself.[2]
  • Retrieval – Selecting data according to specified criteria (e.g., a query, a position in a hierarchy, or a position in relation to other data) and providing that data either directly to the user, or making it available for further processing by the database itself or by other applications. The retrieved data may be made available in a more or less direct form without modification, as it is stored in the database, or in a new form obtained by altering it or combining it with existing data from the database.[3]
  • Administration – Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure.[4]

Both a database and its DBMS conform to the principles of a particular database model.[5] "Database system" refers collectively to the database model, database management system, and database.[6]

Physically, database servers are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually multiprocessor computers, with generous memory and RAID disk arrays used for stable storage. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large-volume transaction processing environments. DBMSs are found at the heart of most database applications. DBMSs may be built around a custom multitasking kernel with built-in networking support, but modern DBMSs typically rely on a standard operating system to provide these functions.[citation needed]

Since DBMSs comprise a significant market, computer and storage vendors often take into account DBMS requirements in their own development plans.[7]

Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML), the type(s) of computer they run on (from a server cluster to a mobile phone), the query language(s) used to access the database (such as SQL or XQuery), and their internal engineering, which affects performance, scalability, resilience, and security.

History

[edit]

The sizes, capabilities, and performance of databases and their respective DBMSs have grown in orders of magnitude. These performance increases were enabled by the technology progress in the areas of processors, computer memory, computer storage, and computer networks. The concept of a database was made possible by the emergence of direct access storage media such as magnetic disks, which became widely available in the mid-1960s; earlier systems relied on sequential storage of data on magnetic tape. The subsequent development of database technology can be divided into three eras based on data model or structure: navigational,[8] SQL/relational, and post-relational.

The two main early navigational data models were the hierarchical model and the CODASYL model (network model). These were characterized by the use of pointers (often physical disk addresses) to follow relationships from one record to another.

The relational model, first proposed in 1970 by Edgar F. Codd, departed from this tradition by insisting that applications should search for data by content, rather than by following links. The relational model employs sets of ledger-style tables, each used for a different type of entity. Only in the mid-1980s did computing hardware become powerful enough to allow the wide deployment of relational systems (DBMSs plus applications). By the early 1990s, however, relational systems dominated in all large-scale data processing applications, and as of 2018 they remain dominant: IBM Db2, Oracle, MySQL, and Microsoft SQL Server are the most searched DBMS.[9] The dominant database language, standardized SQL for the relational model, has influenced database languages for other data models.[citation needed]

Object databases were developed in the 1980s to overcome the inconvenience of object–relational impedance mismatch, which led to the coining of the term "post-relational" and also the development of hybrid object–relational databases.

The next generation of post-relational databases in the late 2000s became known as NoSQL databases, introducing fast key–value stores and document-oriented databases. A competing "next generation" known as NewSQL databases attempted new implementations that retained the relational/SQL model while aiming to match the high performance of NoSQL compared to commercially available relational DBMSs.

1960s, navigational DBMS

[edit]
Basic structure of navigational CODASYL database model

The introduction of the term database coincided with the availability of direct-access storage (disks and drums) from the mid-1960s onwards. The term represented a contrast with the tape-based systems of the past, allowing shared interactive use rather than daily batch processing. The Oxford English Dictionary cites a 1962 report by the System Development Corporation of California as the first to use the term "data-base" in a specific technical sense.[10]

As computers grew in speed and capability, a number of general-purpose database systems emerged; by the mid-1960s a number of such systems had come into commercial use. Interest in a standard began to grow, and Charles Bachman, author of one such product, the Integrated Data Store (IDS), founded the Database Task Group within CODASYL, the group responsible for the creation and standardization of COBOL. In 1971, the Database Task Group delivered their standard, which generally became known as the CODASYL approach, and soon a number of commercial products based on this approach entered the market.

The CODASYL approach offered applications the ability to navigate around a linked data set which was formed into a large network. Applications could find records by one of three methods:

  1. Use of a primary key (known as a CALC key, typically implemented by hashing)
  2. Navigating relationships (called sets) from one record to another
  3. Scanning all the records in a sequential order

Later systems added B-trees to provide alternate access paths. Many CODASYL databases also added a declarative query language for end users (as distinct from the navigational API). However, CODASYL databases were complex and required significant training and effort to produce useful applications.

IBM also had its own DBMS in 1966, known as Information Management System (IMS). IMS was a development of software written for the Apollo program on the System/360. IMS was generally similar in concept to CODASYL, but used a strict hierarchy for its model of data navigation instead of CODASYL's network model. Both concepts later became known as navigational databases due to the way data was accessed: the term was popularized by Bachman's 1973 Turing Award presentation The Programmer as Navigator. IMS is classified by IBM as a hierarchical database. IDMS and Cincom Systems' TOTAL databases are classified as network databases. IMS remains in use as of 2014.[11]

1970s, relational DBMS

[edit]

Edgar F. Codd worked at IBM in San Jose, California, in one of their offshoot offices that were primarily involved in the development of hard disk systems. He was unhappy with the navigational model of the CODASYL approach, notably the lack of a "search" facility. In 1970, he wrote a number of papers that outlined a new approach to database construction that eventually culminated in the groundbreaking A Relational Model of Data for Large Shared Data Banks.[12]

In this paper, he described a new system for storing and working with large databases. Instead of records being stored in some sort of linked list of free-form records as in CODASYL, Codd's idea was to organize the data as a number of "tables", each table being used for a different type of entity. Each table would contain a fixed number of columns containing the attributes of the entity. One or more columns of each table were designated as a primary key by which the rows of the table could be uniquely identified; cross-references between tables always used these primary keys, rather than disk addresses, and queries would join tables based on these key relationships, using a set of operations based on the mathematical system of relational calculus (from which the model takes its name). Splitting the data into a set of normalized tables (or relations) aimed to ensure that each "fact" was only stored once, thus simplifying update operations. Virtual tables called views could present the data in different ways for different users, but views could not be directly updated.

Codd used mathematical terms to define the model: relations, tuples, and domains rather than tables, rows, and columns. The terminology that is now familiar came from early implementations. Codd would later criticize the tendency for practical implementations to depart from the mathematical foundations on which the model was based.

In the relational model, records are "linked" using virtual keys not stored in the database but defined as needed between the data contained in the records.

The use of primary keys (user-oriented identifiers) to represent cross-table relationships, rather than disk addresses, had two primary motivations. From an engineering perspective, it enabled tables to be relocated and resized without expensive database reorganization. But Codd was more interested in the difference in semantics: the use of explicit identifiers made it easier to define update operations with clean mathematical definitions, and it also enabled query operations to be defined in terms of the established discipline of first-order predicate calculus; because these operations have clean mathematical properties, it becomes possible to rewrite queries in provably correct ways, which is the basis of query optimization. There is no loss of expressiveness compared with the hierarchic or network models, though the connections between tables are no longer so explicit.

In the hierarchic and network models, records were allowed to have a complex internal structure. For example, the salary history of an employee might be represented as a "repeating group" within the employee record. In the relational model, the process of normalization led to such internal structures being replaced by data held in multiple tables, connected only by logical keys.

For instance, a common use of a database system is to track information about users, their name, login information, various addresses and phone numbers. In the navigational approach, all of this data would be placed in a single variable-length record. In the relational approach, the data would be normalized into a user table, an address table and a phone number table (for instance). Records would be created in these optional tables only if the address or phone numbers were actually provided.

As well as identifying rows/records using logical identifiers rather than disk addresses, Codd changed the way in which applications assembled data from multiple records. Rather than requiring applications to gather data one record at a time by navigating the links, they would use a declarative query language that expressed what data was required, rather than the access path by which it should be found. Finding an efficient access path to the data became the responsibility of the database management system, rather than the application programmer. This process, called query optimization, depended on the fact that queries were expressed in terms of mathematical logic.

Codd's paper was picked up by two people at Berkeley, Eugene Wong and Michael Stonebraker. They started a project known as INGRES using funding that had already been allocated for a geographical database project and student programmers to produce code. Beginning in 1973, INGRES delivered its first test products which were generally ready for widespread use in 1979. INGRES was similar to System R in a number of ways, including the use of a "language" for data access, known as QUEL. Over time, INGRES moved to the emerging SQL standard.

IBM itself did one test implementation of the relational model, PRTV, and a production one, Business System 12, both now discontinued. Honeywell wrote MRDS for Multics, and now there are two new implementations: Alphora Dataphor and Rel. Most other DBMS implementations usually called relational are actually SQL DBMSs.

In 1970, the University of Michigan began development of the MICRO Information Management System[13] based on D.L. Childs' Set-Theoretic Data model.[14][15][16] MICRO was used to manage very large data sets by the US Department of Labor, the U.S. Environmental Protection Agency, and researchers from the University of Alberta, the University of Michigan, and Wayne State University. It ran on IBM mainframe computers using the Michigan Terminal System.[17] The system remained in production until 1998.

Integrated approach

[edit]

In the 1970s and 1980s, attempts were made to build database systems with integrated hardware and software. The underlying philosophy was that such integration would provide higher performance at a lower cost. Examples were IBM System/38, the early offering of Teradata, and the Britton Lee, Inc. database machine.

Another approach to hardware support for database management was ICL's CAFS accelerator, a hardware disk controller with programmable search capabilities. In the long term, these efforts were generally unsuccessful because specialized database machines could not keep pace with the rapid development and progress of general-purpose computers. Thus most database systems nowadays are software systems running on general-purpose hardware, using general-purpose computer data storage. However, this idea is still pursued in certain applications by some companies like Netezza and Oracle (Exadata).

Late 1970s, SQL DBMS

[edit]

IBM started working on a prototype system loosely based on Codd's concepts as System R in the early 1970s. The first version was ready in 1974/5, and work then started on multi-table systems in which the data could be split so that all of the data for a record (some of which is optional) did not have to be stored in a single large "chunk". Subsequent multi-user versions were tested by customers in 1978 and 1979, by which time a standardized query language – SQL[citation needed] – had been added. Codd's ideas were establishing themselves as both workable and superior to CODASYL, pushing IBM to develop a true production version of System R, known as SQL/DS, and, later, Database 2 (IBM Db2).

Larry Ellison's Oracle Database (or more simply, Oracle) started from a different chain, based on IBM's papers on System R. Though Oracle V1 implementations were completed in 1978, it was not until Oracle Version 2 when Ellison beat IBM to market in 1979.[18]

Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, which is now known as PostgreSQL. PostgreSQL is often used for global mission-critical applications (the .org and .info domain name registries use it as their primary data store, as do many large companies and financial institutions).

In Sweden, Codd's paper was also read and Mimer SQL was developed in the mid-1970s at Uppsala University. In 1984, this project was consolidated into an independent enterprise.

Another data model, the entity–relationship model, emerged in 1976 and gained popularity for database design as it emphasized a more familiar description than the earlier relational model. Later on, entity–relationship constructs were retrofitted as a data modeling construct for the relational model, and the difference between the two has become irrelevant.[citation needed]

1980s, on the desktop

[edit]

The 1980s ushered in the age of desktop computing. The new computers empowered their users with spreadsheets like Lotus 1-2-3 and database software like dBASE. The dBASE product was lightweight and easy for any computer user to understand out of the box. C. Wayne Ratliff, the creator of dBASE, stated: "dBASE was different from programs like BASIC, C, FORTRAN, and COBOL in that a lot of the dirty work had already been done. The data manipulation is done by dBASE instead of by the user, so the user can concentrate on what he is doing, rather than having to mess with the dirty details of opening, reading, and closing files, and managing space allocation."[19] dBASE was one of the top selling software titles in the 1980s and early 1990s.

1990s, object-oriented

[edit]

The 1990s, along with a rise in object-oriented programming, saw a growth in how data in various databases were handled. Programmers and designers began to treat the data in their databases as objects. That is to say that if a person's data were in a database, that person's attributes, such as their address, phone number, and age, were now considered to belong to that person instead of being extraneous data. This allows for relations between data to be related to objects and their attributes and not to individual fields.[20] The term "object–relational impedance mismatch" described the inconvenience of translating between programmed objects and database tables. Object databases and object–relational databases attempt to solve this problem by providing an object-oriented language (sometimes as extensions to SQL) that programmers can use as alternative to purely relational SQL. On the programming side, libraries known as object–relational mappings (ORMs) attempt to solve the same problem.

2000s, NoSQL and NewSQL

[edit]

XML databases are a type of structured document-oriented database that allows querying based on XML document attributes. XML databases are mostly used in applications where the data is conveniently viewed as a collection of documents, with a structure that can vary from the very flexible to the highly rigid: examples include scientific articles, patents, tax filings, and personnel records.

NoSQL databases are often very fast, do not require fixed table schemas, avoid join operations by storing denormalized data, and are designed to scale horizontally.

In recent years, there has been a strong demand for massively distributed databases with high partition tolerance, but according to the CAP theorem, it is impossible for a distributed system to simultaneously provide consistency, availability, and partition tolerance guarantees. A distributed system can satisfy any two of these guarantees at the same time, but not all three. For that reason, many NoSQL databases are using what is called eventual consistency to provide both availability and partition tolerance guarantees with a reduced level of data consistency.

NewSQL is a class of modern relational databases that aims to provide the same scalable performance of NoSQL systems for online transaction processing (read-write) workloads while still using SQL and maintaining the ACID guarantees of a traditional database system.

Use cases

[edit]

Databases are used to support internal operations of organizations and to underpin online interactions with customers and suppliers (see Enterprise software).

Databases are used to hold administrative information and more specialized data, such as engineering data or economic models. Examples include computerized library systems, flight reservation systems, computerized parts inventory systems, and many content management systems that store websites as collections of webpages in a database.

Classification

[edit]

One way to classify databases involves the type of their contents, for example: bibliographic, document-text, statistical, or multimedia objects. Another way is by their application area, for example: accounting, music compositions, movies, banking, manufacturing, or insurance. A third way is by some technical aspect, such as the database structure or interface type. This section lists a few of the adjectives used to characterize different kinds of databases.

  • An in-memory database is a database that primarily resides in main memory, but is typically backed-up by non-volatile computer data storage. Main memory databases are faster than disk databases, and so are often used where response time is critical, such as in telecommunications network equipment.
  • An active database includes an event-driven architecture which can respond to conditions both inside and outside the database. Possible uses include security monitoring, alerting, statistics gathering and authorization. Many databases provide active database features in the form of database triggers.
  • A cloud database relies on cloud technology. Both the database and most of its DBMS reside remotely, "in the cloud", while its applications are both developed by programmers and later maintained and used by end-users through a web browser and Open APIs.
  • Data warehouses[citation needed] archive data from operational databases and often from external sources such as market research firms. The warehouse becomes the central source of data for use by managers and other end-users who may not have access to operational data. For example, sales data might be aggregated to weekly totals and converted from internal product codes to use UPCs so that they can be compared with ACNielsen data. Some basic and essential components of data warehousing include extracting, analyzing, and mining data, transforming, loading, and managing data so as to make them available for further use.
  • A deductive database combines logic programming with a relational database.
  • A distributed database is one in which both the data and the DBMS span multiple computers.
  • A document-oriented database is designed for storing, retrieving, and managing document-oriented, or semi structured, information. Document-oriented databases are one of the main categories of NoSQL databases.
  • An embedded database system is a DBMS which is tightly integrated with an application software that requires access to stored data in such a way that the DBMS is hidden from the application's end-users and requires little or no ongoing maintenance.[21]
  • End-user databases consist of data developed by individual end-users. Examples of these are collections of documents, spreadsheets, presentations, multimedia, and other files. Several products[which?] exist to support such databases.
  • A federated database system comprises several distinct databases, each with its own DBMS. It is handled as a single database by a federated database management system (FDBMS), which transparently integrates multiple autonomous DBMSs, possibly of different types (in which case it would also be a heterogeneous database system), and provides them with an integrated conceptual view.
  • Sometimes the term multi-database is used as a synonym for federated database, though it may refer to a less integrated (e.g., without an FDBMS and a managed integrated schema) group of databases that cooperate in a single application. In this case, typically middleware is used for distribution, which typically includes an atomic commit protocol (ACP), e.g., the two-phase commit protocol, to allow distributed (global) transactions across the participating databases.
  • A graph database is a kind of NoSQL database that uses graph structures with nodes, edges, and properties to represent and store information. General graph databases that can store any graph are distinct from specialized graph databases such as triplestores and network databases.
  • An array DBMS is a kind of NoSQL DBMS that allows modeling, storage, and retrieval of (usually large) multi-dimensional arrays such as satellite images and climate simulation output.
  • In a hypertext or hypermedia database, any word or a piece of text representing an object, e.g., another piece of text, an article, a picture, or a film, can be hyperlinked to that object. Hypertext databases are particularly useful for organizing large amounts of disparate information. For example, they are useful for organizing online encyclopedias, where users can conveniently jump around the text. The World Wide Web is thus a large distributed hypertext database.
  • A knowledge base (abbreviated KB, kb or Δ[22][23]) is a special kind of database for knowledge management, providing the means for the computerized collection, organization, and retrieval of knowledge. Also a collection of data representing problems with their solutions and related experiences.
  • A mobile database can be carried on or synchronized from a mobile computing device.
  • Operational databases store detailed data about the operations of an organization. They typically process relatively high volumes of updates using transactions. Examples include customer databases that record contact, credit, and demographic information about a business's customers, personnel databases that hold information such as salary, benefits, skills data about employees, enterprise resource planning systems that record details about product components, parts inventory, and financial databases that keep track of the organization's money, accounting and financial dealings.
  • A parallel database seeks to improve performance through parallelization for tasks such as loading data, building indexes and evaluating queries.
The major parallel DBMS architectures which are induced by the underlying hardware architecture are:
  • Shared memory architecture, where multiple processors share the main memory space, as well as other data storage.
  • Shared disk architecture, where each processing unit (typically consisting of multiple processors) has its own main memory, but all units share the other storage.
  • Shared-nothing architecture, where each processing unit has its own main memory and other storage.
  • Probabilistic databases employ fuzzy logic to draw inferences from imprecise data.
  • Real-time databases process transactions fast enough for the result to come back and be acted on right away.
  • A spatial database can store the data with multidimensional features. The queries on such data include location-based queries, like "Where is the closest hotel in my area?".
  • A temporal database has built-in time aspects, for example a temporal data model and a temporal version of SQL. More specifically the temporal aspects usually include valid-time and transaction-time.
  • A terminology-oriented database builds upon an object-oriented database, often customized for a specific field.
  • An unstructured data database is intended to store in a manageable and protected way diverse objects that do not fit naturally and conveniently in common databases. It may include email messages, documents, journals, multimedia objects, etc. The name may be misleading since some objects can be highly structured. However, the entire possible object collection does not fit into a predefined structured framework. Most established DBMSs now support unstructured data in various ways, and new dedicated DBMSs are emerging.

Database management system

[edit]

Connolly and Begg define database management system (DBMS) as a "software system that enables users to define, create, maintain and control access to the database."[24] Examples of DBMS's include MySQL, MariaDB, PostgreSQL, Microsoft SQL Server, Oracle Database, and Microsoft Access.

The DBMS acronym is sometimes extended to indicate the underlying database model, with RDBMS for the relational, OODBMS for the object (oriented) and ORDBMS for the object–relational model. Other extensions can indicate some other characteristics, such as DDBMS for a distributed database management systems.

The functionality provided by a DBMS can vary enormously. The core functionality is the storage, retrieval and update of data. Codd proposed the following functions and services a fully-fledged general purpose DBMS should provide:[25]

  • Data storage, retrieval and update
  • User accessible catalog or data dictionary describing the metadata
  • Support for transactions and concurrency
  • Facilities for recovering the database should it become damaged
  • Support for authorization of access and update of data
  • Access support from remote locations
  • Enforcing constraints to ensure data in the database abides by certain rules

It is also generally to be expected the DBMS will provide a set of utilities for such purposes as may be necessary to administer the database effectively, including import, export, monitoring, defragmentation and analysis utilities.[26] The core part of the DBMS interacting between the database and the application interface sometimes referred to as the database engine.

Often DBMSs will have configuration parameters that can be statically and dynamically tuned, for example the maximum amount of main memory on a server the database can use. The trend is to minimize the amount of manual configuration, and for cases such as embedded databases the need to target zero-administration is paramount.

The large major enterprise DBMSs have tended to increase in size and functionality and have involved up to thousands of human years of development effort throughout their lifetime.[a]

Early multi-user DBMS typically only allowed for the application to reside on the same computer with access via terminals or terminal emulation software. The client–server architecture was a development where the application resided on a client desktop and the database on a server allowing the processing to be distributed. This evolved into a multitier architecture incorporating application servers and web servers with the end user interface via a web browser with the database only directly connected to the adjacent tier.[28]

A general-purpose DBMS will provide public application programming interfaces (API) and optionally a processor for database languages such as SQL to allow applications to be written to interact with and manipulate the database. A special purpose DBMS may use a private API and be specifically customized and linked to a single application. For example, an email system performs many of the functions of a general-purpose DBMS such as message insertion, message deletion, attachment handling, blocklist lookup, associating messages an email address and so forth however these functions are limited to what is required to handle email.

Application

[edit]

External interaction with the database will be via an application program that interfaces with the DBMS.[29] This can range from a database tool that allows users to execute SQL queries textually or graphically, to a website that happens to use a database to store and search information.

Application program interface

[edit]

A programmer will code interactions to the database (sometimes referred to as a datasource) via an application program interface (API) or via a database language. The particular API or language chosen will need to be supported by DBMS, possibly indirectly via a preprocessor or a bridging API. Some API's aim to be database independent, ODBC being a commonly known example. Other common API's include JDBC and ADO.NET.

Database languages

[edit]

Database languages are special-purpose languages, which allow one or more of the following tasks, sometimes distinguished as sublanguages:

Database languages are specific to a particular data model. Notable examples include:

A database language may also incorporate features like:

  • DBMS-specific configuration and storage engine management
  • Computations to modify query results, like counting, summing, averaging, sorting, grouping, and cross-referencing
  • Constraint enforcement (e.g. in an automotive database, only allowing one engine type per car)
  • Application programming interface version of the query language, for programmer convenience

Storage

[edit]

Database storage is the container of the physical materialization of a database. It comprises the internal (physical) level in the database architecture. It also contains all the information needed (e.g., metadata, "data about the data", and internal data structures) to reconstruct the conceptual level and external level from the internal level when needed. Databases as digital objects contain three layers of information which must be stored: the data, the structure, and the semantics. Proper storage of all three layers is needed for future preservation and longevity of the database.[33] Putting data into permanent storage is generally the responsibility of the database engine a.k.a. "storage engine". Though typically accessed by a DBMS through the underlying operating system (and often using the operating systems' file systems as intermediates for storage layout), storage properties and configuration settings are extremely important for the efficient operation of the DBMS, and thus are closely maintained by database administrators. A DBMS, while in operation, always has its database residing in several types of storage (e.g., memory and external storage). The database data and the additional needed information, possibly in very large amounts, are coded into bits. Data typically reside in the storage in structures that look completely different from the way the data look at the conceptual and external levels, but in ways that attempt to optimize (the best possible) these levels' reconstruction when needed by users and programs, as well as for computing additional types of needed information from the data (e.g., when querying the database).

Some DBMSs support specifying which character encoding was used to store data, so multiple encodings can be used in the same database.

Various low-level database storage structures are used by the storage engine to serialize the data model so it can be written to the medium of choice. Techniques such as indexing may be used to improve performance. Conventional storage is row-oriented, but there are also column-oriented and correlation databases.

Materialized views

[edit]

Often storage redundancy is employed to increase performance. A common example is storing materialized views, which consist of frequently needed external views or query results. Storing such views saves the expensive computing them each time they are needed. The downsides of materialized views are the overhead incurred when updating them to keep them synchronized with their original updated database data, and the cost of storage redundancy.

Replication

[edit]

Occasionally a database employs storage redundancy by database objects replication (with one or more copies) to increase data availability (both to improve performance of simultaneous multiple end-user accesses to the same database object, and to provide resiliency in a case of partial failure of a distributed database). Updates of a replicated object need to be synchronized across the object copies. In many cases, the entire database is replicated.

Virtualization

[edit]

With data virtualization, the data used remains in its original locations and real-time access is established to allow analytics across multiple sources. This can aid in resolving some technical difficulties such as compatibility problems when combining data from various platforms, lowering the risk of error caused by faulty data, and guaranteeing that the newest data is used. Furthermore, avoiding the creation of a new database containing personal information can make it easier to comply with privacy regulations. However, with data virtualization, the connection to all necessary data sources must be operational as there is no local copy of the data, which is one of the main drawbacks of the approach.[34]

Security

[edit]

Database security deals with all various aspects of protecting the database content, its owners, and its users. It ranges from protection from intentional unauthorized database uses to unintentional database accesses by unauthorized entities (e.g., a person or a computer program).

Database access control deals with controlling who (a person or a certain computer program) are allowed to access what information in the database. The information may comprise specific database objects (e.g., record types, specific records, data structures), certain computations over certain objects (e.g., query types, or specific queries), or using specific access paths to the former (e.g., using specific indexes or other data structures to access information). Database access controls are set by special authorized (by the database owner) personnel that uses dedicated protected security DBMS interfaces.

This may be managed directly on an individual basis, or by the assignment of individuals and privileges to groups, or (in the most elaborate models) through the assignment of individuals and groups to roles which are then granted entitlements. Data security prevents unauthorized users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of it called "subschemas". For example, an employee database can contain all the data about an individual employee, but one group of users may be authorized to view only payroll data, while others are allowed access to only work history and medical data. If the DBMS provides a way to interactively enter and update the database, as well as interrogate it, this capability allows for managing personal databases.

Data security in general deals with protecting specific chunks of data, both physically (i.e., from corruption, or destruction, or removal; e.g., see physical security), or the interpretation of them, or parts of them to meaningful information (e.g., by looking at the strings of bits that they comprise, concluding specific valid credit-card numbers; e.g., see data encryption).

Change and access logging records who accessed which attributes, what was changed, and when it was changed. Logging services allow for a forensic database audit later by keeping a record of access occurrences and changes. Sometimes application-level code is used to record changes rather than leaving this in the database. Monitoring can be set up to attempt to detect security breaches. Therefore, organizations must take database security seriously because of the many benefits it provides. Organizations will be safeguarded from security breaches and hacking activities like firewall intrusion, virus spread, and ransom ware. This helps in protecting the company's essential information, which cannot be shared with outsiders at any cause.[35]

Transactions and concurrency

[edit]

Database transactions can be used to introduce some level of fault tolerance and data integrity after recovery from a crash. A database transaction is a unit of work, typically encapsulating a number of operations over a database (e.g., reading a database object, writing, acquiring or releasing a lock, etc.), an abstraction supported in database and also other systems. Each transaction has well defined boundaries in terms of which program/code executions are included in that transaction (determined by the transaction's programmer via special transaction commands).

The acronym ACID describes some ideal properties of a database transaction: atomicity, consistency, isolation, and durability.

Migration

[edit]

A database built with one DBMS is not portable to another DBMS (i.e., the other DBMS cannot run it). However, in some situations, it is desirable to migrate a database from one DBMS to another. The reasons are primarily economical (different DBMSs may have different total costs of ownership or TCOs), functional, and operational (different DBMSs may have different capabilities). The migration involves the database's transformation from one DBMS type to another. The transformation should maintain (if possible) the database related application (i.e., all related application programs) intact. Thus, the database's conceptual and external architectural levels should be maintained in the transformation. It may be desired that also some aspects of the architecture internal level are maintained. A complex or large database migration may be a complicated and costly (one-time) project by itself, which should be factored into the decision to migrate. This is in spite of the fact that tools may exist to help migration between specific DBMSs. Typically, a DBMS vendor provides tools to help import databases from other popular DBMSs.

Building, maintaining, and tuning

[edit]

After designing a database for an application, the next stage is building the database. Typically, an appropriate general-purpose DBMS can be selected to be used for this purpose. A DBMS provides the needed user interfaces to be used by database administrators to define the needed application's data structures within the DBMS's respective data model. Other user interfaces are used to select needed DBMS parameters (like security related, storage allocation parameters, etc.).

When the database is ready (all its data structures and other needed components are defined), it is typically populated with initial application's data (database initialization, which is typically a distinct project; in many cases using specialized DBMS interfaces that support bulk insertion) before making it operational. In some cases, the database becomes operational while empty of application data, and data are accumulated during its operation.

After the database is created, initialized and populated it needs to be maintained. Various database parameters may need changing and the database may need to be tuned (tuning) for better performance; application's data structures may be changed or added, new related application programs may be written to add to the application's functionality, etc.

Backup and restore

[edit]

Sometimes it is desired to bring a database back to a previous state (for many reasons, e.g., cases when the database is found corrupted due to a software error, or if it has been updated with erroneous data). To achieve this, a backup operation is done occasionally or continuously, where each desired database state (i.e., the values of its data and their embedding in database's data structures) is kept within dedicated backup files (many techniques exist to do this effectively). When it is decided by a database administrator to bring the database back to this state (e.g., by specifying this state by a desired point in time when the database was in this state), these files are used to restore that state.

Static analysis

[edit]

Static analysis techniques for software verification can be applied also in the scenario of query languages. In particular, the *Abstract interpretation framework has been extended to the field of query languages for relational databases as a way to support sound approximation techniques.[36] The semantics of query languages can be tuned according to suitable abstractions of the concrete domain of data. The abstraction of relational database systems has many interesting applications, in particular, for security purposes, such as fine-grained access control, watermarking, etc.

Miscellaneous features

[edit]

Other DBMS features might include:

  • Database logs – This helps in keeping a history of the executed functions.
  • Graphics component for producing graphs and charts, especially in a data warehouse system.
  • Query optimizer – Performs query optimization on every query to choose an efficient query plan (a partial order (tree) of operations) to be executed to compute the query result. May be specific to a particular storage engine.
  • Tools or hooks for database design, application programming, application program maintenance, database performance analysis and monitoring, database configuration monitoring, DBMS hardware configuration (a DBMS and related database may span computers, networks, and storage units) and related database mapping (especially for a distributed DBMS), storage allocation and database layout monitoring, storage migration, etc.

Increasingly, there are calls for a single system that incorporates all of these core functionalities into the same build, test, and deployment framework for database management and source control. Borrowing from other developments in the software industry, some market such offerings as "DevOps for database".[37]

Design and modeling

[edit]
 

The first task of a database designer is to produce a conceptual data model that reflects the structure of the information to be held in the database. A common approach to this is to develop an entity–relationship model, often with the aid of drawing tools. Another popular approach is the Unified Modeling Language. A successful data model will accurately reflect the possible state of the external world being modeled: for example, if people can have more than one phone number, it will allow this information to be captured. Designing a good conceptual data model requires a good understanding of the application domain; it typically involves asking deep questions about the things of interest to an organization, like "can a customer also be a supplier?", or "if a product is sold with two different forms of packaging, are those the same product or different products?", or "if a plane flies from New York to Dubai via Frankfurt, is that one flight or two (or maybe even three)?". The answers to these questions establish definitions of the terminology used for entities (customers, products, flights, flight segments) and their relationships and attributes.

Producing the conceptual data model sometimes involves input from business processes, or the analysis of workflow in the organization. This can help to establish what information is needed in the database, and what can be left out. For example, it can help when deciding whether the database needs to hold historic data as well as current data.

Having produced a conceptual data model that users are happy with, the next stage is to translate this into a schema that implements the relevant data structures within the database. This process is often called logical database design, and the output is a logical data model expressed in the form of a schema. Whereas the conceptual data model is (in theory at least) independent of the choice of database technology, the logical data model will be expressed in terms of a particular database model supported by the chosen DBMS. (The terms data model and database model are often used interchangeably, but in this article we use data model for the design of a specific database, and database model for the modeling notation used to express that design).

The most popular database model for general-purpose databases is the relational model, or more precisely, the relational model as represented by the SQL language. The process of creating a logical database design using this model uses a methodical approach known as normalization. The goal of normalization is to ensure that each elementary "fact" is only recorded in one place, so that insertions, updates, and deletions automatically maintain consistency.

The final stage of database design is to make the decisions that affect performance, scalability, recovery, security, and the like, which depend on the particular DBMS. This is often called physical database design, and the output is the physical data model. A key goal during this stage is data independence, meaning that the decisions made for performance optimization purposes should be invisible to end-users and applications. There are two types of data independence: Physical data independence and logical data independence. Physical design is driven mainly by performance requirements, and requires a good knowledge of the expected workload and access patterns, and a deep understanding of the features offered by the chosen DBMS.

Another aspect of physical database design is security. It involves both defining access control to database objects as well as defining security levels and methods for the data itself.

Models

[edit]
Collage of five types of database models

A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized, and manipulated. The most popular example of a database model is the relational model (or the SQL approximation of relational), which uses a table-based format.

Common logical data models for databases include:

An object–relational database combines the two related structures.

Physical data models include:

Other models include:

Specialized models are optimized for particular types of data:

External, conceptual, and internal views

[edit]
Traditional view of data[38]

A database management system provides three views of the database data:

  • The external level defines how each group of end-users sees the organization of data in the database. A single database can have any number of views at the external level.
  • The conceptual level (or logical level) unifies the various external views into a compatible global view.[39] It provides the synthesis of all the external views. It is out of the scope of the various database end-users, and is rather of interest to database application developers and database administrators.
  • The internal level (or physical level) is the internal organization of data inside a DBMS. It is concerned with cost, performance, scalability and other operational matters. It deals with storage layout of the data, using storage structures such as indexes to enhance performance. Occasionally it stores data of individual views (materialized views), computed from generic data, if performance justification exists for such redundancy. It balances all the external views' performance requirements, possibly conflicting, in an attempt to optimize overall performance across all activities.

While there is typically only one conceptual and internal view of the data, there can be any number of different external views. This allows users to see database information in a more business-related way rather than from a technical, processing viewpoint. For example, a financial department of a company needs the payment details of all employees as part of the company's expenses, but does not need details about employees that are in the interest of the human resources department. Thus different departments need different views of the company's database.

The three-level database architecture relates to the concept of data independence which was one of the major initial driving forces of the relational model.[39] The idea is that changes made at a certain level do not affect the view at a higher level. For example, changes in the internal level do not affect application programs written using conceptual level interfaces, which reduces the impact of making physical changes to improve performance.

The conceptual view provides a level of indirection between internal and external. On the one hand it provides a common view of the database, independent of different external view structures, and on the other hand it abstracts away details of how the data are stored or managed (internal level). In principle every level, and even every external view, can be presented by a different data model. In practice usually a given DBMS uses the same data model for both the external and the conceptual levels (e.g., relational model). The internal level, which is hidden inside the DBMS and depends on its implementation, requires a different level of detail and uses its own types of data structure types.

Research

[edit]

Database technology has been an active research topic since the 1960s, both in academia and in the research and development groups of companies (for example IBM Research). Research activity includes theory and development of prototypes. Notable research topics have included models, the atomic transaction concept, related concurrency control techniques, query languages and query optimization methods, RAID, and more.

The database research area has several dedicated academic journals (for example, ACM Transactions on Database Systems-TODS, Data and Knowledge Engineering-DKE) and annual conferences (e.g., ACM SIGMOD, ACM PODS, VLDB, IEEE ICDE).

See also

[edit]

Notes

[edit]
  1. ^ This article quotes a development time of five years involving 750 people for DB2 release 9 alone.[27]

References

[edit]
  1. ^ Ullman & Widom 1997, p. 1.
  2. ^ "Update Definition & Meaning". Merriam-Webster. Archived from the original on Feb 25, 2024.
  3. ^ "Retrieval Definition & Meaning". Merriam-Webster. Archived from the original on Jun 27, 2023.
  4. ^ "Administration Definition & Meaning". Merriam-Webster. Archived from the original on Dec 6, 2023.
  5. ^ Tsitchizris & Lochovsky 1982.
  6. ^ Beynon-Davies 2003.
  7. ^ Nelson & Nelson 2001.
  8. ^ Bachman 1973.
  9. ^ "TOPDB Top Database index". pypl.github.io.
  10. ^ "database, n". OED Online. Oxford University Press. June 2013. Retrieved July 12, 2013. (Subscription required.)
  11. ^ IBM Corporation (October 2013). "IBM Information Management System (IMS) 13 Transaction and Database Servers delivers high performance and low total cost of ownership". Retrieved Feb 20, 2014.
  12. ^ Codd 1970.
  13. ^ Hershey & Easthope 1972.
  14. ^ North 2010.
  15. ^ Childs 1968a.
  16. ^ Childs 1968b.
  17. ^ M.A. Kahn; D.L. Rumelhart; B.L. Bronson (October 1977). MICRO Information Management System (Version 5.0) Reference Manual. Institute of Labor and Industrial Relations (ILIR), University of Michigan and Wayne State University.
  18. ^ "Oracle 30th Anniversary Timeline" (PDF). Archived (PDF) from the original on 2011-03-20. Retrieved 23 August 2017.
  19. ^ Interview with Wayne Ratliff. The FoxPro History. Retrieved on 2013-07-12.
  20. ^ Development of an object-oriented DBMS; Portland, Oregon, United States; Pages: 472–482; 1986; ISBN 0-89791-204-7
  21. ^ Graves, Steve. "COTS Databases For Embedded Systems" Archived 2007-11-14 at the Wayback Machine, Embedded Computing Design magazine, January 2007. Retrieved on August 13, 2008.
  22. ^ Argumentation in Artificial Intelligence by Iyad Rahwan, Guillermo R. Simari
  23. ^ "OWL DL Semantics". Retrieved 10 December 2010.
  24. ^ Connolly & Begg 2014, p. 64.
  25. ^ Connolly & Begg 2014, pp. 97–102.
  26. ^ Connolly & Begg 2014, p. 102.
  27. ^ Chong et al. 2007.
  28. ^ Connolly & Begg 2014, pp. 106–113.
  29. ^ Connolly & Begg 2014, p. 65.
  30. ^ Chapple 2005.
  31. ^ "Structured Query Language (SQL)". International Business Machines. October 27, 2006. Retrieved 2007-06-10.
  32. ^ Wagner 2010.
  33. ^ Ramalho, J.C.; Faria, L.; Helder, S.; Coutada, M. (31 December 2013). "Database Preservation Toolkit: A flexible tool to normalize and give access to databases". Biblioteca Nacional de Portugal (BNP). University of Minho.
  34. ^ Paiho, Satu; Tuominen, Pekka; Rökman, Jyri; Ylikerälä, Markus; Pajula, Juha; Siikavirta, Hanne (2022). "Opportunities of collected city data for smart cities". IET Smart Cities. 4 (4): 275–291. doi:10.1049/smc2.12044. ISSN 2631-7680. S2CID 253467923.
  35. ^ David Y. Chan; Victoria Chiu; Miklos A. Vasarhelyi (2018). Continuous auditing : theory and application (1st ed.). Bingley, UK: Emerald Publishing. ISBN 978-1-78743-413-4. OCLC 1029759767.
  36. ^ Halder & Cortesi 2011.
  37. ^ Ben Linders (January 28, 2016). "How Database Administration Fits into DevOps". Retrieved April 15, 2017.
  38. ^ itl.nist.gov (1993) Integration Definition for Information Modeling (IDEFIX) Archived 2013-12-03 at the Wayback Machine. 21 December 1993.
  39. ^ a b Date 2003, pp. 31–32.

Sources

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Further reading

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[edit]

 

 

User Friendly
"Press any key"
Author(s) J. D. Frazer, a.k.a. "Illiad"
Website www.userfriendly.org
Current status/schedule Completed
Launch date November 17, 1997 (1997-11-17)[# 1]
End date November 21, 2010 (2010-11-21)
Genre(s) Technology and geek humor

User Friendly was a webcomic written by J. D. Frazer, also known by his pen name Illiad. Starting in 1997, the strip was one of the earliest webcomics to make its creator a living. The comic is set in a fictional internet service provider and draws humor from dealing with clueless users and geeky subjects. The comic ran seven days a week until 2009, when updates became sporadic, and since 2010 it had been in re-runs only. The webcomic was shut down in late February 2022, after an announcement from Frazer.[1]

Premise

[edit]

User Friendly is set inside a fictional ISP, Columbia Internet.[2] According to reviewer Eric Burns, the strip is set in a world where "[u]sers were dumbasses who asked about cupholders that slid out of their computers, marketing executives were perverse and stupid and deserved humiliation, bosses were clueless and often naively cruel, and I.T. workers were somewhat shortsighted and misguided, but the last bastion of human reason... Every time we see Greg working, it's to deal with yet another annoying, self-important clueless user who hasn't gotten his brain around the digital world".[3] Although mostly gag-a-day, the comic often had ongoing running arcs and occasionally continuing character through-lines.

Cast

[edit]

A.J. Garrett

[edit]

A.J., Illiad's alter ego,[4] represents "the creative guy" in the strip, maintaining and designing websites. As a web designer, he's uncomfortably crammed in that tiny crevice between the techies and the marketing people. This means he's not disliked by anyone, but they all look at him funny from time to time. A.J. is shy and sensitive, loves most computer games and nifty art, and has a big-brother relationship with the Dust Puppy. A.J. is terrified of grues and attempts to avoid them.[# 2] He was released from the company on two separate occasions but returned shortly thereafter.

In the strip as of September 16, 2005, he and Miranda (another character) are dating. They also have previously dated, but split up over a misunderstanding.

The Chief

[edit]

The Chief is Columbia Internet's CEO. He is the leader of the techies and salespeople.

Illiad based the character on a former boss, saying, "The Chief is based on my business mentor. He was the vice president that I reported to back in the day. The Chief, like my mentor, is tall (!) and thin and sports a bushy ring around a bald crown, plus a very thick moustache." The Chief bears a superficial resemblance to the Pointy-Haired Boss of Dilbert fame. However, Illiad says that The Chief was not inspired by the Dilbert character.[# 3] His personality is very different from the PHB, as well: he manages in the laissez-faire style, as opposed to the Marketing-based, micro-managing stance of the PHB. He has encouraged the office to standardise on Linux (much to Stef's chagrin).[# 4]

Dust Puppy

[edit]

Born in a server from a combination of dust, lint, and quantum events, the Dust Puppy looks similar to a ball of dust and lint, with eyes, feet and an occasional big toothy smile. He was briefly absent from the strip after accidentally being blown with compressed air while sleeping inside a dusty server.

Although the Dust Puppy is very innocent and unworldly, he plays a superb game of Quake. He also created an artificial intelligence named Erwin, with whom he has been known to do occasional song performances (or filks).

Dust Puppy is liked by most of the other characters, with the exceptions of Stef and the Dust Puppy's evil nemesis, the Crud Puppy.

First appearance December 3, 1997.[# 5]

Crud Puppy

[edit]

Crud Puppy (Lord Ignatius Crud)[# 6] is the evil twin, born from the crud in Stef's keyboard; he is the nemesis of the Dust Puppy and sometimes takes the role of "bad guy" in the series. Examples include being the attorney/legal advisor of both Microsoft and then AOL or controlling a "Thing" suit in the Antarctic. He is most often seen in later strips in an Armani suit, usually sitting at the local bar with Cthulhu. The Crud Puppy first appeared in the strip on February 24, 1998.[# 7]

Erwin

[edit]

Erwin first appeared in the January 25, 1998 strip. Erwin is a highly advanced Artificial Intelligence (AI) created overnight during experimentation in artificial intelligence by the Dust Puppy, who was feeling kind of bored. Erwin is written in COBOL[# 8] because Dust Puppy "lost a bet".[# 9] Erwin passes the Turing test with flying colours, and has a dry sense of humour. He is an expert on any subject that is covered on the World Wide Web, such as Elvis sightings and alien conspiracies. Erwin is rather self-centered, and he is fond of mischievous pranks.

Originally, Erwin occupied the classic "monitor and keyboard" type computer with an x86 computer architecture, but was later given such residences as an iMac, a Palm III, a Coleco Adam on Mir, a Furby, a nuclear weapon guidance system, an SGI O2, a Hewlett-Packard Calculator (with reverse Polish notation, which meant that Erwin talked like Yoda for weeks afterward), a Lego Mindstorms construction, a Tamagotchi, a Segway, an IBM PC 5150, a Timber Wolf-class BattleMech,[# 10] and an Internet-equipped toilet (with Dust Puppy being the toilet brush), as a punishment for insulting Hastur.

Greg Flemming

[edit]

Greg is in charge of Technical Support in the strip. In other words, he's the guy that customers whine to when something goes wrong, which drives him nuts. He blows off steam by playing visceral games and doing bad things to the salespeople. He's not a bad sort, but his grip on his sanity hovers somewhere between weak and non-existent, and he once worked for Microsoft Quality Assurance.

Mike Floyd

[edit]

Mike is the System Administrator of the strip and is responsible for the smooth running of the network at the office. He's bright but prone to fits of anxiety. His worst nightmare is being locked in a room with a sweaty Windows 95 programmer and no hacking weapons in sight.[5] He loves hot ramen straight out of a styrofoam cup.

Miranda Cornielle

[edit]

Miranda is a trained systems technologist, an experienced UNIX sysadmin, and very, very female. Her technical abilities unnerve the other techs, but her obvious physical charms compel them to stare at her, except for Pitr, who is convinced she is evil. Although she has few character flaws, she does express sadistic tendencies, especially towards marketers and lusers. Miranda finds Dust Puppy adorable.

She and A.J. are dating as of September 16, 2005, although she was previously frustrated by his inability to express himself and his love for her. This comes after years of missed opportunities and misunderstandings, such as when A.J. poured his feelings into an email and Miranda mistook it for the ILOVEYOU email worm and deleted it unread.[6]

Pitr Dubovich

[edit]

Pitr is the administrator of the Columbia Internet server and a self-proclaimed Linux guru. He suddenly began to speak with a fake Slavic accent as part of his program to "Become an Evil Genius." He has almost succeeded in taking over the planet several times. His sworn enemy is Sid, who seems to outdo him at every turn. Pitr's achievements include: making the world's (second) strongest coffee, merging Coca-Cola, Pepsi into Pitr-Cola and making Columbia Internet millions with a nuclear weapon purchased from Russia, and the infamous Vigor text editor. He briefly worked for Google, nearly succeeding in world domination, but was released from there and returned to Columbia Internet. Despite his vast efforts to become the ultimate evil character, his lack of illheartedness prevents him from reaching such achievement.

Sid Dabster

[edit]

Sid is the oldest of the geeks and very knowledgeable. His advanced age gives him the upper hand against Pitr, whom he has outdone on several occasions, including in a coffee-brewing competition and in a round of Jeopardy! that he hacked in his own favor. Unlike Pitr, he has no ambitions for world domination per se, but he is a friend of Hastur and Cthulhu (based on the H. P. Lovecraft Mythos characters). He was hired in September 2000 and he had formerly worked for Hewlett-Packard, with ten years' experience[# 11] It is his habit, unlike the other techs, to dress to a somewhat professional degree; when he first came to work, Smiling Man, the head accountant, expressed shock at the fact that Sid was wearing his usual blue business suit.[# 12] He is also a fan of old technology, having grown up in the age of TECO, PDP-6es, the original VT100, FORTRAN, IBM 3270 and the IBM 5150; one could, except for the decent taste in clothing, categorise him as a Real Programmer. He was once a cannabis smoker,[# 13] as contrasted with the rest of the technological staff, who prefer caffeine (Greg in the form of cola, Miranda in the form of espresso). This had the unfortunate effect of causing lung cancer and he was treated by an oncologist.[# 14] He has since recovered from the cancer and was told he has another 20 years or so to live.

Pearl Dabster

[edit]

Sid Dabster's beautiful daughter. The character appeared for the first time in the strip of Aug. 30, 2001.[# 15] Pearl is often seen getting the better of the boys. She is the antagonist of Miranda, and occasionally the object of Pitr's affections, much to the chagrin of Sid. Some people (both in strip and in the real world) wrongly assume that the character was named after the scripting language PERL. While this may be the true intention of the author, in the script timeline, is shown to be an error based on wordplay.[# 16]

Smiling Man

[edit]

The Smiling Man is the company comptroller. He is in charge of accounts, finances, and expenditures. He smiles all day for no reason. This in itself is enough to terrify most normal human beings (even via phone). However, the Dust Puppy, the "Evilphish", a delirious Stef, and a consultant in a purple suit have managed to get him to stop smiling first. His favourite wallpaper is a large, complex, and utterly meaningless spreadsheet.

Stef Murky

[edit]

Stef is the strip's Corporate Sales Manager. He runs most of the marketing efforts within the firm, often selling things before they exist. He is a stereotypical marketer, with an enormous ego and a condescending attitude toward the techies; they detest him and frequently retaliate with pranks. He sucks at Quake, even once managing to die at the startup screen in Quake III Arena;[# 17] in addition, he manages to die by falling into lava in any game that contains it, including games where it is normally impossible to step in said lava.[# 18] Although he admires Microsoft and frequently defends their marketing tactics, infuriating the techies, he has a real problem with Microsoft salesmen, probably because they make much more money than he does. His attitude towards women is decidedly chauvinist; he lusts after Miranda who will not have anything to do with him. Stef is definitely gormless, as demonstrated on January 14, 2005.[# 19]

Production

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In a 2008 article, reviewer Eric Burns said that as best he could tell, Frazer had produced strips seven days a week, without missing an update for, at that time, almost 11 years.[3] Frazer would draw several days' worth of comics in advance, but the Sunday comic – based on current events and in color – was always drawn for immediate release and did not relate to the regular storyline.[citation needed]

The website for User Friendly included other features such as Link of the Day and Iambe Intimate & Interactive, a weekly editorial written under the pseudonym "Iambe".[7]

In late 1999, User Friendly and Sluggy Freelance swapped a character (A.J. and Torg).[citation needed]

The strip and Loki Software teamed up for player skin and custom level contest for Quake III Arena in 2000.[8] A Flash cartoon based on the series was also produced.[9][10]

Author

[edit]

J. D. Frazer was born in 1969.[11] He began his career in law enforcement and served as a corrections officer,[12] hoping eventually to join the Royal Canadian Mounted Police, but he changed his mind, leaving law enforcement to pursue more creative endeavours.[13] He worked as a game designer, production manager, art director, project manager, Web services manager, writer, creative director, and cartoonist.[14] As of 2014 he lives in Vancouver, British Columbia, Canada.[5]

Creation

[edit]

Frazer started writing User Friendly in 1997.[2] According to Frazer, he started cartooning at age 12. He had tried to get into cartooning through syndicates with a strip called Dust Puppies, but it was rejected by six syndicates. Later, while working at an ISP, he drew some cartoons which his co-workers enjoyed. He then drew a month's worth of cartoons and posted them online. After that, he quit his job and then worked on the comic.[15]

Success

[edit]

Writer Xavier Xerxes said that in the very early days of webcomics, Frazer was probably one of the bigger success stories and was one of the first to make a living from a webcomic.[16] Eric Burns attributed initial success of the comic to the makeup of the early internet, saying, "In 1997, a disproportionate number of internet users... were in the I.T. Industry. When User Friendly began gathering momentum, there wasn't just little to nothing like it on the web -- it appealed and spoke to a much larger percentage of the internet reading audience than mainstream society would support outside of that filter.... in the waning years of the 20th Century, it was a safe bet that if someone had an internet connection in the first place, they'd find User Friendly funny."[3]

On April Fools' Day 1999, the site appeared to be shut down permanently after a third party sued.[17][18] In future years, the April 1st cartoon referenced back to the disruption that was caused.[19][20]

In a 2001 interview, Frazer said that he was not handling fame well, and pretended not to be famous in order to keep his life normal. He said that his income came from sponsorship, advertising, and sales of printed collections.[15] These compilations have been published by O'Reilly Media.[21]

Since 2000, User Friendly had been published in a variety of newspapers, including The National Post in Canada and the Linux Journal magazine.[22]

Ideas

[edit]

In a 2001 interview, Frazer estimated that about 40% of strip ideas came from reader submissions, and occasionally he would get submissions that he would use "unmodified".[23] He also said that he educated himself on the operating system BSD in order to make informed jokes about it.[15]

In 2009, Frazer was found to be copying punchlines found in the MetaFilter community. After one poster found a comment on MetaFilter that was similar to a User Friendly comic, users searched and found several other examples.[24] Initially, Frazer posted on MetaFilter saying "I get a flurry of submissions and one-liners every week, and I haven't checked many of them at all, because I rarely had to in the past" but later admitted that he had taken quotes directly from the site.[25][24] On his website, Frazer said, "I offered no attribution or asked for permission [for these punchlines], over the last couple of years I've infringed on the expression of ideas of some (who I think are) clever people. Plagiarized. My hypocrisy seems to know no bounds, as an infamous gunman was once heard saying. I sincerely apologize to my readers and to the original authors. I offer no excuses and accept full blame and responsibility. As a result, I'll be modifying the cartoons in question. No, it won't happen again. Yes, I've immersed myself in mild acid."[26]

While published books still contain at least one cartoon with a punchline taken from MetaFilter, Frazer has removed these cartoons from the website, or updated them to quote and credit the source of the punchlines, and fans searched through the archives to ensure that none of the other punchlines have been plagiarized.[27]

Suspension

[edit]

The strip went on hiatus from June 1, 2009[# 20] to August 2009 for personal reasons.[# 21] In this period, previous strips were re-posted.

A second hiatus lasted from December 1, 2009 until August 1, 2010, again for personal reasons. New cartoons, supplied by the community as part of a competition, started to appear as of August 2, 2010.[# 22]

From November 1, 2010 through November 21, 2010, Illiad published a special "Remembrance Day story arc", and stated that it is "vague and at this point random" what will happen to the strip afterwards, that "going daily again is highly unlikely", but that "there are still many stories that I want to tell through UF, over time".[# 23] Since then, previous comics have been re-posted on a daily basis.

After the de facto stop of publishing new content, three one-off comics commemoration special occasions were published:

On 24 February 2022, Illiad announced that the website would be shut down soon, "at the end of this month. If not, it won't be much later than that."[28]

At approximately midnight PST on the evening of 28 February 2022, the website was shut down.

Reviews

[edit]

User Friendly has received mixed reviews over the years.

In a 2008 review, Eric Burns of Websnark called it a "damned good comic strip", but felt it had several problems. Burns felt that the strip had not evolved in several years, saying "his strip is exactly the same today as it was in 1998... the same characters, the same humor, the same punchlines, the same punching bags as before." Burns said that characters learn no lessons, and that "[i]f Frazer uses copy and paste to put his characters in, he's been using the same clip art for the entire 21st century." Burns also criticised the stereotypical depiction of idiotic computer users as outdated. But fundamentally, Burns found the strip funny, saying anyone who had worked IT would likely find it funny, and even those who had not will find something in it amusing. Burns felt that some criticism of User Friendly came from seeing it as general webcomic, rather than one targeted at a specific audience of old-school IT geeks, and he considered that the targeted approach was a good business model.[3]

Writer T Campbell declared JD Frazer's work as "ow[ing] a heavy debt to [Scott] Adams, but his 'nerdcore' was a purer sort: the jokes were often for nerds ONLY-- NO NON-TECHIES ALLOWD [sic]." He continued "He wasn't the first webtoonist to target his audience so precisely, but he was the first to do it on a daily schedule, and that kind of single-minded dedication is something most techies could appreciate. User Friendly set the tone for nerdcore strips to follow."[29] Time magazine called User Friendly "a strip in the wry, verbal vein of Doonesbury...the humor is a combination of pop culture references and inside jokes straight outta the IT department."[30] The strip was among the most notable of a wave of similar strips, including Help Desk by Christopher B. Wright,[31] General Protection Fault by Jeffrey T. Darlington,[32] The PC Weenies by Krishna Sadasivam,[33] Geek & Poke by Oliver Widder,[34] Working Daze by John Zakour, and The Joy of Tech by Liza Schmalcel and Bruce Evans.

Comic writer and artist Joe Zabel said that User Friendly "may be one of the earliest webcomics manifestation of the use of templates... renderings of the characters that are cut and pasted directly into the comic strip... I think the main significance of User Friendly is that in 1997 it was really, really crude in every respect. Horrible artwork, terrible storyline, zilch characterization, and extremely dull, obvious jokes. And yet it was a smash hit! I think this demonstrates that the public will embrace just about anything if it's free and the circumstances are right. And it indicates that new internet users of the time were really hungry, downright starving, for entertainment.... his current work [speaking in 2005] is comparatively slick and professional. But I suspect that his early work had enormous influence, because it encouraged thousands of people with few skills and little talent to jump into the webcomics field." Zabel also credited User Friendly's success in part to its "series mascot", Dust Puppy, saying that "the popular gag-a-day cartoons almost always have some kind of mascot."[29]

The webcomic Penny Arcade produced a strip in 1999 just to criticise Frazer, saying "people will pass up steak once a week for crap every day."[35] They also criticized the commercialism of the enterprise.[36] By contrast, CNET included it on 2007 a list of "sidesplitting tech comics",[33] Mashable included it in a 2009 list of the 20 best webcomics[2] and Polygon listed it as one of the most influential webcomics of all time in 2018.[37] It has also been noted by FromDev,[38] Brainz,[39] RiskOptics,[40] DondeQ2,[41] and Pingdom.[31] CBR.com concluded the comic had aged poorly in a 2023 rundown.[42]

Lawrence I. Charters appreciated the nature of the titles used for the published books.[43] Francis Glassborow cited the specificity of the humour,[44] which also lead Retro Activity to find the strip "difficult to recommend" along with the limited art style.[45] Mike Kaltschnee also mentioned the weakness of the art, but was impressed at Illiad maintaining publication of a strip every day.[46] "Webcomics: The Influence and Continuation of the Comix Revolution" described how the strip represented the counter-cultural aspects of the open-source software movement.[47] Dustin Puryear observed how the strip represents the conflicts between the computer literate and newer less informed users.[48] Christine Moellenberndt wrote about the online community spawned around the comic strip.[49]

In 2007, User Friendly was part of an exhibit at The Museum of Comic and Cartoon Art called Infinite Canvas: The Art of Webcomics.[50]

Bibliography

[edit]

Several cartoon compilations have been published:

  • User Friendly, v1.0, Plan Nine Publishing, 2002, ISBN 1-929462-39-5 (collects earlier strips)
  • User Friendly, O'Reilly, 1999, ISBN 1-56592-673-0 January 25, 1998 Archived July 5, 2013, at archive.todayDecember 25, 1998 (misses out December 20 Archived November 13, 2005, at the Wayback Machine and probably some others)
  • Evil Geniuses in a Nutshell, O'Reilly, 2000, ISBN 1-56592-861-X January 3, 1999December 11, 1999
  • The Root of All Evil, O'Reilly, 2001, ISBN 0-596-00193-2 January 1, 2000December 31, 2000
  • Even Grues Get Full, O'Reilly, 2003, ISBN 0-596-00566-0 January 1, 2001November 17, 2001
  • User Friendly – Die Deutsche Dialekt-Ausgabe (translation to several German dialects) ISBN 3-89721-380-X
  • Ten Years of UserFriendly.Org, Manning Dec 2008, ISBN 978-1-935182-12-2 a 1000-page hardback collection of every script with some comments by the author.

References

[edit]
  1. ^ "UserFriendly Strip Comments". February 26, 2022. Archived from the original on February 26, 2022. Retrieved March 1, 2022.
  2. ^ a b c P. Aune, Sean (March 3, 2009). "20 of the Best Web Comics". Mashable. Archived from the original on April 26, 2018. Retrieved March 2, 2024.
  3. ^ a b c d Burns, Eric (May 2008). "Eric: State of the (Web)Cartoonist: J.D. "Illiad" Frazer". Websnark. Archived from the original on June 1, 2008. Retrieved November 16, 2020.
  4. ^ Frazer, J. D. (March 2002). User Friendly v1.0. Plan Nine Publishing. p. 67. ISBN 1-929462-39-5.
  5. ^ a b Illiad. "UF Cartoon Archive - Character Gallery - Mike". www.userfriendly.org.
  6. ^ Illiad. "UserFriendly Strip Comments". ars.userfriendly.org.
  7. ^ Iambe Intimate & Interactive site page, http://www.userfriendly.org/community/iambe/
  8. ^ Gasperson, Tina (September 21, 2000). "Loki and Userfriendly sponsor Quake III skins contest". Linux.com. Retrieved February 27, 2023.
  9. ^ Smith, JT (September 18, 2000). "VFS Live to stream interview with Illiad and WebDi". Linux.com. Retrieved March 2, 2024.
  10. ^ "User Friendly Animation Episode 1 - Play Online on Flash Museum 🕹️". Flash Museum. April 16, 2024.
  11. ^ Illiad (2006). Money for content and your clicks for free : turning web sites, blogs, and podcasts into cash. Indianapolis: Wiley. ISBN 978-0-471-74753-6. OCLC 64089426.
  12. ^ Frazer, J. D. (September 28, 2006). "What job/career have you had that you wouldn't recommend to anyone?". User Friendly. Retrieved September 29, 2006.
  13. ^ Brown, Janelle (October 27, 1999). "Cartoon for coders". Salon. Retrieved June 5, 2024.
  14. ^ "Even Grues Get Full - tech humor book review". www.kickstartnews.com. Retrieved April 1, 2021.
  15. ^ a b c Coleman, Chris (February 9, 2001). "An Interview With Illiad". ONLamp. Archived from the original on January 5, 2002. Retrieved July 5, 2008.
  16. ^ Xerxes, Xaviar (January 2007). "Biggie Panda: Old Skool Webcomics". COMIXtalk. Archived from the original on September 2, 2011. Retrieved July 5, 2008.
  17. ^ Whitinger, Dave (April 1, 1999). "Segfault.org and UserFriendly.org get shut down". Linux Today. Archived from the original on June 6, 2019. Retrieved October 5, 2024.
  18. ^ Whitinger, Dave (April 1, 1999). "April Fools!". Linux Today. Archived from the original on December 11, 2020. Retrieved October 4, 2024.
  19. ^ April 1, 2000 Cartoon, https://web.archive.org/web/20220225214636/http://ars.userfriendly.org/cartoons/?id=20000401
  20. ^ April 1, 2004 Cartoon, https://web.archive.org/web/20220226103320/http://ars.userfriendly.org/cartoons/?id=20040401
  21. ^ "O'Reilly Releases "The Root of All Evil"--Latest Exploits of User Friendly's Dust Puppy & Gang". O'Reilly Media. September 4, 2001. Retrieved March 2, 2024.
  22. ^ Lucas, Josh (September 1, 1999). "Dilbert Killer". Wired. Retrieved March 1, 2024.
  23. ^ Brown, Janelle (October 27, 1999). "Cartoon for coders". Salon.com. Retrieved March 2, 2024.
  24. ^ a b Social Pressure Can Solve The 'Copying' Problem Even Without Copyright, Techdirt, February 23, 2009.
  25. ^ "Wha Wha Wibble". metatalk.metafilter.com. Retrieved November 16, 2020.
  26. ^ Frazer, J.D. (February 23, 2009). "[Illiad] BEYOND THE PALE AND AN APOLOGY". User Friendly. Archived from the original on May 18, 2019. Retrieved November 16, 2020.
  27. ^ Frazer, J.D. (March 13, 2009). "[Illiad] FIXED, AND WILL CONTINUE FIXING". User Friendly. Archived from the original on June 21, 2019. Retrieved October 4, 2024.
  28. ^ "HEADS UP: We're Going Dark", Illiad, 2022-02-24
  29. ^ a b Zabel, Joseph ‘Joe’; et al. (September 30, 2005). "The Artistic History of Webcomics: A Webcomics Examiner Roundtable". The Webcomics Examiner. Archived from the original on November 24, 2005. Retrieved July 7, 2008.
  30. ^ Worthy (November 22, 2022). "User Friendly". Everything2. Retrieved March 2, 2024.
  31. ^ a b SolarWinds Worldwide (January 16, 2009). "7 tech comics that will put a big smile on your face". Pingdom. Retrieved March 1, 2024.
  32. ^ ""User Friendly" and "GPF" Creators on Comics and Operating Systems". Linux Today. November 8, 2005. Retrieved March 2, 2024.
  33. ^ a b Dolcourt, Jessica (September 10, 2007). "Sidesplitting tech comics". CNET. Retrieved March 2, 2024.
  34. ^ Francis, Carol (June 17, 2013). "The Best Entertaining Online Web Tech Comics". oneextrapixel. Retrieved March 2, 2024.
  35. ^ Holkins, Jerry; Mike, Krahulik (April 7, 1999). "Illiad: Not Funny". Penny Arcade. Retrieved November 16, 2020.
  36. ^ dragoon (August 20, 2000). "User Friendly Media". Everything2. Retrieved March 2, 2024.
  37. ^ Jensen, K. Thor (November 27, 2018). "The most influential webcomics of all time". Polygon. Retrieved March 1, 2024.
  38. ^ Dubey, Sarikaz (May 14, 2014). "Awesome Geek Comics Websites". FromDev. Retrieved March 2, 2024.
  39. ^ "20 Funny Web Comics You'd Love To Read". Brainz. Retrieved March 1, 2024.
  40. ^ Riskoptics (March 3, 2017). "6 InfoSec Cartoons & Webcomics to Brighten a Gloomy Week". RiskOptics. Retrieved March 1, 2024.
  41. ^ "Quake Funny Pages: >Byte Me_, Dilbert, Penny Arcade and User Friendly". DondeQ2. November 14, 2018. Retrieved March 2, 2024.
  42. ^ Trinos, Angelo Delos (August 8, 2023). "10 Great Webcomics That Aged Poorly". CBR.com. Retrieved March 2, 2024.
  43. ^ Charters, Lawrence I. (2002). "The Root of All Evil: A Review". Washington Apple Pi Journal. Retrieved March 2, 2024.
  44. ^ Glassborow, Francis (October 2003). "Even Grues Get Full - The Fourth User Friendly Collection". ACCU. Retrieved March 2, 2024.
  45. ^ "Entry 9: 'User Friendly'". Retro Activity. April 27, 2016. Retrieved March 2, 2024.
  46. ^ Kaltschnee, Mike. "User Friendly - A cartoon book for geeks". dacs.doc electric. Retrieved March 2, 2024.
  47. ^ Fenty, Sean; Houp, Trena; Taylor, Laurie (May 2005). "Webcomics: The Influence and Continuation of the Comix Revolution". ImageText. Retrieved March 2, 2024.
  48. ^ Puryear, Dustin (September 25, 2000). "A Review of Evil Geniuses In A Nutshell". 32BitsOnline. Archived from the original on April 9, 2001. Retrieved March 2, 2024.
  49. ^ Moellenberndt, Christine (May 6, 2022). "Requiem for a Community; What i learned about community from an online comic strip". LinkedIn. Retrieved March 2, 2024.
  50. ^ "Webcomics show at MoCCA". The Beat. September 5, 2007. Archived from the original on September 25, 2011. Retrieved November 16, 2020.

Story notes

[edit]
  1. ^ Frazer, JD ‘Illiad’ (November 17, 1997), "Cartoon with Strip Comments", UserFriendly.
  2. ^ Frazer, JD ‘Illiad’ (October 17, 2002), "Strip Comments", UserFriendly.
  3. ^ Frazer, JD ‘Illiad’ (July 18, 2006), "Strip Comments", UserFriendly.
  4. ^ Frazer, JD ‘Illiad’ (October 8, 1998), User Friendly (cartoon).
  5. ^ Frazer, JD ‘Illiad’ (December 3, 1997), "Dust Puppy's first appearance", User Friendly (cartoon), archived from the original on January 1, 2015, retrieved February 13, 2012
  6. ^ Frazer, JD ‘Illiad’ (September 15, 2005), "Nag strip", User Friendly.
  7. ^ Frazer, JD ‘Illiad’ (April 5, 1998), "Anatomy of a Crud Puppy", User Friendly (cartoon).
  8. ^ Frazer, JD ‘Illiad’ (October 18, 2000), User Friendly (cartoon), archived from the original on September 26, 2017, retrieved August 20, 2011.
  9. ^ Frazer, JD ‘Illiad’ (October 19, 2000), User Friendly (cartoon), archived from the original on November 27, 2002, retrieved August 29, 2011.
  10. ^ Frazer, JD ‘Illiad’ (October 4, 2001), User Friendly (cartoon).
  11. ^ Frazer, JD ‘Illiad’ (September 26, 2000), User Friendly (cartoon).
  12. ^ Frazer, JD ‘Illiad’ (September 27, 2000), User Friendly (cartoon).
  13. ^ Frazer, JD ‘Illiad’ (May 7, 2001), User friendly (cartoon), archived from the original on December 17, 2002, retrieved August 28, 2009.
  14. ^ Frazer, JD ‘Illiad’ (October 14, 2009), User Friendly (cartoon).
  15. ^ Frazer, JD ‘Illiad’ (August 30, 2001), User Friendly (cartoon).
  16. ^ Frazer, JD ‘Illiad’ (August 31, 2001), User Friendly (cartoon).
  17. ^ Frazer, JD ‘Illiad’ (March 17, 2000), User Friendly (cartoon), archived from the original on July 11, 2002, retrieved February 25, 2008.
  18. ^ Frazer, JD ‘Illiad’ (October 14, 2006), User Friendly (cartoon), archived from the original on May 5, 2019, retrieved November 13, 2008.
  19. ^ Frazer, JD ‘Illiad’ (January 14, 2005), "Strip Comments", User Friendly (UserFriendly).
  20. ^ Frazer, JD ‘Illiad’ (June 1, 2009), User Friendly.
  21. ^ Frazer, JD ‘Illiad’, "June & July", User Friendly (re-runs), archived from the original on May 14, 2019, retrieved June 1, 2009.
  22. ^ Frazer, JD ‘Illiad’ (August 2, 2010), User Friendly.
  23. ^ Frazer, JD ‘Illiad’, "Remembrance Day Story Arc & Other Matters", User Friendly.
  24. ^ Frazer, JD ‘Illiad’ (March 19, 2011), User Friendly.
  25. ^ Frazer, JD ‘Illiad’ (October 9, 2011), User Friendly.
  26. ^ Frazer, JD ‘Illiad’ (January 1, 2012), User Friendly.
[edit]

 

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Absolutely! Our web designing service includes comprehensive SEO strategies that are specifically tailored toward attracting more local traffic from Sydney residents looking for home painting services.
The time frame can depend on many factors including complexity of design, any special features required etc., however generally speaking it can take anywhere between 6-8 weeks to develop a fully functioning website.
Some of the top-rated web design companies in Sydney include G Squared, Digital Garden, and Magicdust.
These web designers typically offer a range of services including website design & development, eCommerce solutions, digital marketing strategies, SEO optimization, social media management and content creation.
The cost can vary greatly depending on the scope and complexity of the project. For a simple website design, prices may start around $1000 AUD while more complex projects could easily reach over $10,000 AUD. Its best to contact each company directly for a specific quote based on your needs.
You can find professional web designers in Sydney through various online platforms such as Upwork, Freelancer, or LinkedIn. Also, local networking events or business directories can be useful.
Yes, there are numerous well-regarded agencies such as Digital Garden, G Squared and Magicdust offering web design services in Sydney.
When hiring a web designer or agency, consider their portfolio to assess if they match your style preference, their reviews and testimonials for credibility check, pricing structure for budget compatibility and whether they offer post-launch website support/maintenance.
The cost of hiring a web designer can vary greatly depending on the complexity of the project. On average though, you might expect to pay anywhere between AUD $2,000 - $5,000 for basic website designs from freelancers whereas established agencies may charge higher rates starting from AUD $10,000 upwards.
The cost can vary greatly depending on several factors including the complexity of the project, the designers experience and skills, and their location. In Sydney, an average project could range anywhere from $2,000 to $10,000 AUD.
Both methods are common. Some freelancers charge by the hour which can range from $50 to $200 AUD per hour depending on their level of expertise. Others prefer to charge a flat rate per project which takes into account all aspects of the work involved.
Yes, most freelancers are open to negotiation as long as it reflects fair compensation for their time and effort. However, remember that lower prices may also mean compromises on quality or timeliness.
There may be additional costs such as hosting fees, domain registration, content creation (if not provided), SEO services etc. Its important to clarify these aspects before starting a project to avoid unexpected expenses later.
A freelance web designer in Sydney should have a strong understanding of graphic design, user experience (UX), user interface (UI) design, HTML/CSS coding, JavaScript, and SEO. They should also be familiar with web design tools like Adobe Creative Suite and WordPress.
Its extremely important. With the increasing use of smartphones and tablets to browse the internet, having a website that is mobile responsive can significantly improve user experience and engagement.
Yes, being able to work with various CMS platforms such as WordPress, Joomla or Drupal is crucial as these systems are commonly used for website creation and management. This gives clients more control over their websites once the project is complete.
Very relevant. A good freelancer doesnt just create visually appealing websites; they also need to ensure that those sites are optimized for search engines. An understanding of SEO best practices can significantly enhance the visibility of a clients website on Google.
Successful freelancers require excellent written and verbal communication skills. They need to understand their client’s needs and expectations clearly and translate those into an effective visual solution. Good communication also helps when explaining technical aspects to non-technical clients.
Some of the latest trends include Progressive Web Apps (PWA), Artificial Intelligence and Bots, Accelerated Mobile Pages (AMP), Single Page Applications (SPA), and API-first design.
AI is being used for creating intelligent chatbots for customer service, improving user experience through personalized content, predictive analytics, and automating routine tasks.
AMP helps to improve the performance of mobile web pages, making them load faster. This improves user engagement and contributes to higher search engine rankings.
SPAs provide a smoother user experience by eliminating the need for page reloads. They are becoming popular for building responsive websites and mobile applications.
API-first design means building your application based on the API, ensuring that all applications using this API have a consistent experience. It allows developers to work on multiple platforms simultaneously, increasing efficiency and coherence.
The latest web design trends have a significant impact on local businesses in Sydney. It influences how they present themselves online, their customer engagement and ultimately their sales.
Responsive web design plays a crucial role as it ensures that websites function seamlessly across all devices. That increases accessibility for customers, which can lead to higher traffic and potentially more sales for local businesses.
Advancements in SEO practices greatly increase the visibility of local businesses online. By optimizing website content, using relevant keywords and improving site speed, these businesses can rank higher on search engine results thereby reaching a wider audience.
Yes, having an updated and professional website design significantly influences consumer trust. A well-designed website signifies that the business is credible, modern, and cares about its consumers experience.
Incorporating e-commerce features can indeed boost sales for SMEs. This allows them to sell products directly from their websites, making shopping easier for customers while also expanding the potential market beyond just Sydney.
Sydney-based web designers use Local SEO by optimizing a websites content, keywords, and backlinks so it appears at the top of search results within its specific geographic area. They also ensure the business is listed on Google My Business and other local directories to increase visibility.
Local SEO is crucial as it helps businesses reach prospective customers in their vicinity. It increases online visibility and organic traffic from users searching within that location. This can be particularly beneficial for businesses serving a specific area like Sydney.
Techniques utilized include creating locally relevant content, using local keywords, ensuring the site is mobile-friendly, improving page loading speed, having consistent NAP (Name, Address, Phone number) across all platforms, and getting positive reviews on Google My Business.
Yes. While they specialize in optimizing websites for local searches in Sydney, these skills are transferable. A competent web designer can adapt their strategy to optimize a website for any geographical location based on the clients needs.
Website optimization services involve various strategies to improve a websites performance, accessibility, and visibility. These can include improving site speed, ensuring mobile-friendliness, optimizing for search engines (SEO), enhancing user experience (UX), and more.
Website optimization makes your site more visible on search engines like Google which means more traffic and potential customers. It also improves user experience which can lead to higher conversion rates. Whether youre targeting audiences in Sydney or globally, an optimized website can significantly enhance your online presence.
There are many reputable companies providing web design and optimization services in Sydney such as Webski Solutions, Magicdust, G Squared & Whitehat Agency etc. The choice depends on your specific needs, budget and business goals. Always look for a service provider with good reviews, proven results and excellent customer service.
Website optimization is crucial for several reasons. It improves the sites speed, usability, and accessibility, thus enhancing user experience. Moreover, optimized websites rank higher on search engine results which increases visibility and attracts more potential customers.
Website optimization significantly enhances your websites performance by reducing loading times, ensuring it displays correctly across various devices (desktops, mobiles, tablets), and making it easier for search engines to understand your content.
Key elements include responsive design (ensuring the site looks good on all devices), improving site speed (by optimizing images and code), SEO-friendly URLs and meta tags, as well as creating quality content that includes relevant keywords.
Web Design Sydney provides comprehensive services including SEO audits to identify areas of improvement, optimizing HTML codes for faster loading times, creating responsive designs for better mobile viewing experience, developing SEO-friendly URLs and meta tags to improve ranking on search engines like Google. They also offer content creation with targeted keywords that can draw more traffic to your site.
The firms generally offer services such as Search Engine Optimization (SEO), website speed optimization, conversion rate optimization and content optimization among others.
These services can improve your websites visibility on search engines like Google, enhance user experience by improving loading speed and navigability, and increase the likelihood of visitors becoming customers through strategic content placement and design.
It would be best to contact each firm directly for this information. Most established firms will have portfolios or case studies demonstrating their past work that they can share with you.
Optimization can significantly improve the speed and responsiveness of a website. It involves reducing file sizes, minimizing code, optimizing images, using efficient loading techniques such as lazy loading and implementing proper caching strategies. These all contribute to faster page load times which provides a better user experience.
Website performance is crucial in any location including Sydney because it directly impacts user experience and SEO rankings. A well-optimized website will load quickly, keep visitors engaged longer and rank higher on search engine result pages leading to increased visibility and potentially more business opportunities.
Some common techniques include minifying CSS, JS, and HTML files; compressing images without losing quality; leveraging browser caching; minimizing HTTP requests by combining files; using content delivery networks (CDNs) to deliver resources faster to users based on their geographical location; utilizing GZIP compression for smaller file size during transfer; enabling deferred JavaScript loading.
Optimizing a website doesnt necessarily mean compromising on its aesthetics or functionality. Instead, its about making smart choices regarding file types, sizes, coding techniques etc., that enhance both appearance and performance. For instance, you can use SVGs instead of bitmap images where appropriate as they scale better while maintaining a smaller file size.