The Teksouth Enterprise Consulting (TEC) Group

Introduction to Dynamic Data Integration PDF Print E-mail

For nearly twenty years, our industry has viewed data architecture as a fractured set of separate yet related components. At the heart of this collection of capabilities we often find what is referred to as an ‘Enterprise Data Warehouse’ (EDW). For the last decade though, the EDW has been evolving into something more – a more flexible yet comprehensive approach to the complete data layer. Making this transition involves not just technical improvements but a philosophical re-evaluation as well in regards to how data management, discovery and exploitation are viewed. This new philosophy and solution approach can be referred to as the Dynamic Data Warehouse, this is the basis of our DDI practice.

The Dynamic Data Integration (DDI) represents more than the evolution of the EDW approach. The DDI is a paradigm shift for data architecture, but this shift is made possible by an evolution in our thinking. Many in our industry now realize that the data layer is more than sum of its pieces; it is a continuum of capabilities managed within a single unified lifecycle. Data resources can be logically integrated and holistically managed and the primary activities related to data are intricately inter-related. Data management, discovery and exploitation are part of the same process, same lifecycle and support the same business goals.

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The Philosophy behind the DDW begins with the following assumptions:

  1. That distributed capability can be managed centrally.
  2. That all aspects of data architecture belong within a single, unified Lifecycle framework.
  3. That data stored without regard to anticipated value through exploitation is useless.
  4. That data architecture must be user-centric, responsive and Agile.
  5. That data transformations can occur anywhere within the architecture, as long as they are understood and managed through policy.
  6. That performance and usability always outweigh perceived solution manageability. (if the custom doesn’t use it, nothing else matters, period)
  7. That change is inevitable and attempting to create a static, perfectly defined enterprise will end in failure.
  8. That the Right solution is the one that works for the customer, not the one that comes closest to adhering to prescriptive industry definitions.
  9. Recognition that there are now two clouds to consider, the one inside the enterprise and the one outside.
  10. That all parts of data architecture represent a pool of data resources or services. This pool comes closer than the original concept of EDW to representing the true single data management framework. The DDW is the logical counterpart to EDW without the restrictions and with added interoperability across elements that had previously been managed separately. The DDW is a single solution – but is also the complete solution needed to ensure enterprise success.
 

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