Report

Part 8 of 9, Big Data/Data Lake Platforms: Removing Silos & Operationalizing Your Data

Table of Contents

  1. Summary
  2. Strategy & Business Considerations
  3. Technical Considerations
  4. Technology Evolution & Landscape
  5. Key Players
  6. About Andrew Brust
Part 10 of 11 in a series Removing Silos & Operationalizing Your Data Beginning

Summary

We’ve spent a lot of time working our way through foundational analytics technology categories. But we haven’t yet addressed the one that is perhaps the most celebrated in the current market: big data and data lake technology.

Initially, Apache Hadoop and related technologies were representative of the big data analytics category.  Data lakes are merely an architectural approach that big data analytics enables, so the two terms are not, technically, equivalent.

But, these days in the industry, the terms tend to be used interchangeably.  One reason for this is most organizations use big data tech for the construction of data lakes.  Another reason is because many early Hadoop big data initiatives were perceived to be only minimally successful, leaving the industry in need of a new headline term, with “data lake” winning out.

Access Report

Available to GigaOm Research Subscribers

Subscribe to
GigaOm Research