Data Architecture

Unlike the simplistic models used in individual applications, a real enterprise has very complicated data architecture. Most of the data will be held in large legacy or package systems, for which the details of data structure may be unknown. Other data will be held in spreadsheets and personal databases (such as Microsoft Access), and may be invisible to the IT department or senior business data administrators. Some key data may reside in external systems maintained by service providers or business partners. As you explore your own complex data architecture, you will come to accept two realities:

You have little control over the way high-level business data concepts are realized. Data is likely to be highly dispersed, often without adequate controls on quality.

Most data is duplicated across a number of systems, with significant variations in quality, format, and meaning. Some of the copies, maintained by Enterprise Application Integration (EAI) technology or careful business processes, may be good (but probably not perfect). Most are very poor, maintained only by occasional batch transfers and stressed or broken manual processes. Organizational and business process conflicts, or simple failures of trust, may get in the way of common sense improvements.

These conditions have several important consequences. For instance, poor copies may cause business or technical problems that become exacerbated when initiatives such as Customer Relationship Management (CRM) and Business Intelligence need to merge data from various sources. Some organizations work to harness various legacy systems in end-to-end processes. Either the business or IT may be driving changes to simplify business processes, streamline data flows, and reduce duplication. Although modelling can be of great benefit in meeting these challenges, most traditional modelling approaches cannot address them. They produce models that are either too detailed to be of use or not detailed enough, and they typically fail to focus on the difficult issues of the enterprise data architecture and the integration of its various components.

We believe it is important to create powerful, simple, and effective models of the data structure from an enterprise viewpoint -- a set of models known as the "EnDaArch". Call our representative to know more about our data architecture and warehousing solutions.

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