Simplify Big Data Processing
Big data projects mean moving lots of data between multiple cloud and on-premises environments for normalization, consolidation, and finally, analysis. Speed and reliability are crucial, and manual processes are painful.
Assembling a bunch of “free” tools to orchestrate complex big data workflows across multiple cloud and on-premises environments can quickly get expensive and time-consuming for data scientists and IT staff.
I’m planning to streamline big data processing in: