Mike Ames, leads the product management and innovations efforts for SAS’ data integration product lines. He specializes in information architecture and applying advanced analytics to a wide variety of business and technical problems. His areas of expertise include data warehousing, real-time systems, and machine learning.
This is the first post of a multi-part series on EL-T integration. Lately I’ve been inundated with requests for information about SAS’ ability to do EL-T style (Extract Load then Transform) integration with Data Integration Studio, especially in Teradata shops that use SAS, so we thought it would be useful
Ask any data warehouse architect what is driving the “big data” craze and he’ll tell you it has to do with the cost of storage and the advancements in distributed computing and most likely will mention Hadoop. Most enterprise data warehouses are constrained by cost and scalability of relational databases.
The term “big data” is all the rage right now, however the term “big” is relative. At SAS we have been called on to do “big data” projects and more importantly “big analytics” projects for many years now. In fact, we are the pioneers of analytics on “big data.” There is
