Kumar offers Data and Architecture expertise to help world-wide SAS customers solve business problems across various industries. Kumar provides field enablement and sales support leadership to SAS field teams in the areas of operationalizing analytics, data preparation, data integration, and data quality in 'big data' environments. Kumar's area of interest include, Data Discovery using ML/AI modeling. He holds a M.S. in Computer Science with Parallel and Distributed computing as his research from Illinois Institute of Technology and MBA from Boston University focusing on Business Strategy and Entrepreneurship.
In part 1 of this post, we looked at setting up Spark jobs from Cloud Analytics Services (CAS) to load and save data to and from Hadoop. Now we are moving on to the next step in the analytic cycle, scoring data in Hadoop and executing SAS code as a
This article is not a tutorial on Hadoop, Spark, or big data. At the same time, no prerequisite knowledge of these technologies is required for understanding. We’ll give you enough background prior to diving into the details. In simplest terms, the Hadoop framework maintains the data and Spark controls and
