Information engineering

Information technology engineering used to be known more commonly as information engineering; this changed in the early 21st century, and information engineering took on a new meaning.

Information technology engineering has a somewhat checkered history that follows two very distinct threads. It originated in Australia between 1976 and 1980, and appears first in the literature in a series of Six InDepth articles by the same name published by US Computerworld in May – June 1981.[3] Information technology engineering first provided data analysis and database design techniques that could be used by database administrators (DBAs) and by systems analysts to develop database designs and systems based upon an understanding of the operational processing needs of organizations for the 1980s.

Clive Finkelstein is acknowledged as the "Father" of information technology engineering,[4][5] having developed its concepts from 1976 to 1980 based on original work carried out by him to bridge from strategic business planning to information systems. He wrote the first publication on information technology engineering: a series of six in depth articles of the same name published by US Computerworld in May – June 1981. He also co-authored with James Martin the influential Savant Institute Report titled: "Information Engineering", published in Nov 1981. The Finkelstein thread evolved from 1976 as the business driven variant of ITE. The Martin thread evolved into the data processing-driven (DP) variant of ITE. From 1983 till 1986 ITE evolved further into a stronger business-driven variant of ITE, which was intended to address a rapidly changing business environment. The then technical director, Charles M. Richter, from 1983 to 1987, guided by Clive Finkelstein, played a significant role by revamping the ITE methodology as well as helping to design the ITE software product (user-data) which helped automate the ITE methodology, opening the way to next generation Information Architecture.

Strategic business planning

Business objectives that executives set for what's to come are characterized in key business plans, with their more noteworthy definition in tactical business plans and implementation in operational business plans. Most businesses today recognize the fundamental need to grow a business plan that follows this strategy. It is often difficult to implement these plans because of the lack of transparency at the tactical and operational degrees of organizations. This kind of planning requires feedback to allow for early correction of problems that are due to miscommunication and misinterpretation of their business plan.

Data modelling

The ideal basis for data models is to be based on directions made by management for the future of the business. These directions are defined within business plans. Data models can provide a clear insight into future business needs, when business plans become unavailable or out of date. Data models can be developed from any statement of a policy, goal, objective, or strategy for a business and its needs. Data that has been consistently updated over time can be useful within a business to see how things have changed and how the needs of the business are different going forward.

Process modelling

Process modelling is similar to data modelling in the sense that it is taking a broad look at the processes a business has required outlined by its business plan. Using an information engineering approach, processes can be linked to data and needs, to get a better sense of why the process exists and how it must be carried out. This allows for a business to get an overview of what it is currently doing, why it is doing the things it is doing, the importance of each thing, and how these things are being done.

Systems design and implementation

The fourth and last phase of information engineering is systems design and implementation. After setting a business plan, data models are used to create process models, which are then used to design systems so they are ready for implementation. This phase is the finishing phase. The systems design and implementation phase takes what has been created by the previous three phases of information engineering and wraps it all into one final product, so that it is available to be implemented. This is where businesses can see the culmination of their information engineering phases and efforts. [6]

There are several tools supporting information technology engineering such as Bachman's Data Analyst, Excelerator,[7] and more.

• Information technology
• Software engineering
• Computer science

Wikimedia Commons has media related to Information Engineering.

• The Complex Method IEM
• Rapid Application Development
• Enterprise Engineering and Rapid Delivery of Enterprise Architecture