In simple terms, if data management was about ingestion, enrichment and storage of data so that data was harmonized, cleansed and stored in a way that analytics can run efficiently on top of it in a secured way then why is “Modern Data Management” not doing the same in the platform. After all, one could argue that the same requirements if served up through open source technologies reduces the Total Cost Ownership (TCO).

Given the cost of the skills, and a still maturing platform, this statement only holds true at very large volumes. There are inherently new capabilities in this platform which enables something new and that also needs to be understood to appreciate “Modern Data Management”.

The key to understanding and appreciating the capability of modern platform is to think of disjointed, error and failure prone environments from which we want to aggregate the data (edge sources like geo location, sensors, fitness devices, machine logs, social) as opposed to enterprise data.