Traditional Business Intelligence

**** Looking BACK to 2013 ****

This simple methodology has served the needs of Business Intelligence for decades.

As datasets increase in size, these traditional BI systems are challenged by:

1. Performance - Many relational operations require all records to be processed.  Joining or summing a billion records is problematic even with Hadoop.
2. Relevance - ETL often defines how data will be used.  ad hoc or new types of analysis will mean the data needs to repurposed and transformed.
3. Storage - Storage is cheap.  But saving several copies of a dataset each time it is repurposed is simply not possible. 

Tomorrow, I'll compare these traditional BI methodologies with those that are energizing the Big Data world.  Can they coexist?  And what are strategies for BI as Big Data evolves further.  The answer may surprise you.