Trends Report

Data, Data Everywhere!

Very Large Database Issues And Implications For Business Intelligence

July 23rd, 2007
Boris Evelson, Vice President, Principal Analyst
Boris Evelson Vice President, Principal Analyst
With contributors:
Noel Yuhanna , Erica Driver , Jamie Barnett , J. Paul Kirby , Rob Karel

Summary

The information revolution is producing mountains of digital data that are becoming more and more challenging to process and analyze. Not only are businesses generating more data every day, but our approach to data analysis (structured databases, indexes, and distributed data architectures) generates even more data. Furthermore, the volume of unstructured content is also increasing, adding to the proliferation. To help organizations get business value out of all this data, vendors — both platform vendors and business intelligence (BI) specialists — are offering multiple technology and architecture solutions for very large database (VLDB) BI. Understanding that BI for multiterabyte data sets may require different architectures and technologies than smaller data sets is key for successful VLDB BI implementations. Information and knowledge management professionals should implement the most appropriate VLDB BI option and plan for continued explosive data growth.

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