Four ways SAS makes Hadoop easy
Clark Bradley explains how SAS can make Hadoop approachable and accessible.
Author
Clark BradleyRSS
Principal Technical Architect
Principal Technical Architect
Clark Bradley provides field enablement and sales support leadership to SAS field teams in the areas of data management, data integration and data quality in big data environments. His responsibilities include analyzing data architecture, analyzing complex SQL, investigating Hadoop technologies, and system and subsystem tuning across SMP and MPP platforms.
Provisioning data for advanced analytics in Hadoop
The data lake is a great place to take a swim, but is the water clean? My colleague, Matthew Magne, compared big data to the Fire Swamp from The Princess Bride, and it can seem that foreboding. The questions we need to ask are: How was the data transformed and
The snap, crackle and pop of data management on Hadoop
Data. It's everywhere. It can reside in many places through replication, accessibility needs or infrastructure costs. For reporting, that same data can be structurally changed (denormalized or aggregated) into additional reporting and analytic data repositories. Over time, new sources of enrichment of that data become available through traditional data sources