Simplifying Analytics on Big Data Infrastructure

Fragmented, disparate backend data systems have become the norm in today’s enterprise, where you’ll find a mix of relational databases, Hadoop stores, and NoSQL engines, with access and analytics tools bolted on every which way. This mishmash of options presents a real challenge when it comes to choosing frontend analytics and visualization tools.

How did we get here? In this O’Reilly report, IT veteran Rich Morrow takes you through the rapid changes to both backend storage and frontend analytics over the past decade, and provides a pragmatic list of requirements for an analytics stack that will centralize access to all of these data systems. You’ll examine current analytics platforms, including Looker—a new breed of analytics and visualization tools built specifically to handle our fragmented data space.

  • Understand why and how data became so fractured so quickly
  • Explore the tangled web of data and backend tools in today’s enterprises
  • Learn the tool requirements for accessing and analyzing the full spectrum of data
  • Examine the relative strengths of popular analytics and visualization tools, including Looker, Tableau, and MicroStrategy
  • Inspect Looker’s unique focus on both the frontend and backend

Rich Morrow

Rich Morrow is a 20 year veteran of IT, and an expert big data technologies like Hadoop. He has been teaching Cloudera (Hadoop) and AWS for nearly 3 years, retains all certifications for both, and uses these technologies in his day to day consulting practice. He is a prolific writer on Cloud, Big Data, DevOps/Agile, Mobile, and IoT topics, having published many works for companies like GigaOM and Global Knowledge.