In today's BI world there is data pulled from variety of Data sources. Once the data is pulled from the source they need to housed is what is called a Operational Data Store. Once data is housed here , then data is transformed/modelled for different reporting and analytical purposes. One of the key points to be considered is the cost of storage and the support personnel needed to maintain these data stores. The ETL's to perform such pulls can also be very complicated in certain cases. In the recent times the concept of Data Integration and federation has evolved and is being experimented in Master data management. One of the frequent requirement today in the business world today is that there is a need for a unified view of disparate data sources. Currently this requirement is being handled by an ETL Based approach and building data warehouses on top of them, at the same time tying disparate data sources together can be a challenging process. This is where the concept of data integration architecture kicks in, one can look at the following link to get an overview of data integration and data reingetration methodology:
http://www.strins.com/integrated-data-warehouse.html
This is an area to watch out for in the coming years as more and more disparate data sources are being used for data analysis.
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