A lot of innovation happens in the big data (data that needs distributed compute - spark etc.) like ability to blend data across sources, schemaless / schema on the fly, deploy analytical models to production etc. Is there a case for similar innovations in the small to medium data (working with ~10M dataset) blended across data sources, simple analytical models and such ? What percentage of usecases are in the bigdata realm vs. small/medium data.