Interactive Data Science and BI on the Hadoop Data Lake

Interactive Data Science and BI on the Hadoop Data Lake

For most companies have deployed data lake strategies the original motivation was to replatform their analytics onto a more modern architecture, taking advantage of commodity infrastructure and open source software in hopes of processing greater volumes of data at a lower cost. However, most projects have failed to deliver on this vision, and today companies find their data lakes are a complement to the traditional data warehouse and data mart rather than a replacement.

What went wrong?

In this whitepaper, we cover:

  • Key challenges with complexity, performance, and data quality on a datalake
  • Data-as-a-Service and how DaaS can resolves these key challenges
  • Common usecases for Data-as-a-Service

See how you can get started on transforming your data lake strategy.