There are (too?) many options for BI on Hadoop. Some are great at exploration, some are great at OLAP, some are fast, and some are flexible. Understanding the options and how they work with Hadoop systems is a key challenge for many organizations. Tomer Shiran provides a survey of the main options, both traditional (Tableau, Qlik, etc.) and new (Platfora, Datameer, etc.).

Ruhollah Farchtchi explores best practices for building systems that support ad hoc queries over real-time data and offers an overview of Kudu, a new storage layer for Hadoop that is specifically designed for use cases that require fast analytics on rapidly changing data with a simultaneous combination of sequential and random reads and writes.

There are (too?) many options for BI on Hadoop. Some are great at exploration, some are great at OLAP, some are fast, and some are flexible. Understanding the options and how they work with Hadoop systems is a key challenge for many organizations. Jacques Nadeau provides a survey of the main options, both traditional (Tableau, Qlik, etc.) and new (Platfora, Datameer, etc.).