Creating information solutions for a business requires an accurate analysis of the business issues involved. It doesn't matter if a project concerns a BI, EAI or an OLTP application, analysts should not be bothered by technicalities. And business people should be able to verify the relevance of the analysts' proposed solutions.

Enterprises continue to grow and so does the complexity of their data environment, including data terminology both internal and external to a particular enterprise. Consider a firm that builds computer chips for new devices. Each project may have its own Database System and Data Dictionary. Yet engineers, management, accountants, and customers need to speak the same language to understand one another. A Data or Business Glossary solves this complexity, by referencing vocabulary needed to run the company. A Business Glossary covers multiple Data Dictionaries and business segments.

Data modeling is described as a craft and once completed the results may even seem artful. Yet outsiders may see data modeling as abstract, time consuming or even unnecessary. In many cases the data modeler interviews business experts, studies piles of requirements, talks some more, and then, hocus pocus, presents a diagram with boxes, crow’s feet, arrows, etc… Then the slow process begins to keep the diagrams up to date, explain what the diagrams behold, and sometimes even data modelers themselves may get lost while maintaining a growing set of data models and requirements.

Data exchange is the core activity for automated systems in your business. These systems are in fact allowing business information to be exchanged in an automated way. So where did the knowledge to build this system come from? Sometimes one would think the IT department just knows and delivers. In a lot of cases IT doesn't know it well enough, and systems occasionally fail business requirements. Agile strategies try to counter that gap between IT and Business. But agility itself is no solid foundation for your information management either.

There may be numerous reasons for outsourcing or off-shoring your IT developments. We will not attempt to name these, but we will concentrate on the requirements to make this a success. Besides many management efforts, a sound information model for user requirements is an absolute must.

It is safe to assume nowadays that your business has multiple IT systems running. Hopefully they deliver the functions that your busines need. Requirements however change, and systems are updated, rebuild, or need integration with others. Having the right business knowledge to modify or integrate systems accurately can be a problem. Finding up-to-date business knowledge in a well documented and meaningfull form is rare. Having and maintaining that much needed business knowledge is crucial to make any adjustment with confidence.

All database models are derived from IT specifications. IT specifications come from analysts and designers which get their information from future IT users. Both software and database need input from users. A database design is in most cases technically oriented, using artificial keys, additional indexes and much more.

Software changes faster than data. Every few years applications get replaced, extended, upgraded or rewritten on a different technical platform. A proper software design can make a major difference in the application life cycle. But even the seemingly complete and popular UML design practice suffers from inexact workings.

Data warehouse is typically a requirement for Business Intelligence purposes. Providing numbers, statistics and hopefully the answers to management questions. Management, questions and answers are all about the meaning of data, also called information.