Building a Central Data Warehouse (CDW) is a long and expensive process. At the end of this process we often find that the initial requirements were either not completely met, incorrectly specified or they had changed dramatically. In fact Business Intelligence (BI) requirements are as fluid and volatile as the business itself. This talk outlines a new BI architecture based on the concept of Data Lakes, which are unstructured data landing areas that allow experimentation, analysis and creating usable data much more quickly than standard data warehouse methods. The proposed architecture eliminates and/or reduces deficiencies in other models. It is similar in concept to the CDW model with dimensional Data Marts but with the advantages available now through the use of new technologies such as Hadoop and MapReduce.

ABOUT SPEAKER:
Cas Apanowicz is one of the co-founders of Infobright, Inc.. He works actively in the areas of data processing, data warehousing and ETL. He is a highly-recognized expert concentrating on DW/BI implementations for large companies in US and Canada. His research is also focused on new methods that would enhance ETL processes.