| Introduction to Dynamic Data Integration |
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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.
The Philosophy behind the DDW begins with the following assumptions:
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