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.).
Tomer covers the key use cases for using BI with Hadoop and NoSQL systems and discusses the types of data as well as the scale of data and ingestion/mutation rates for each. Tomer then explains the main categories of BI on Hadoop including general-purpose BI (Tableau, Qlik, MicroStrategy, etc.), combined with interactive SQL-on-Hadoop (Drill, Impala, Spark SQL), and on-Hadoop BI (Platfora, Datameer, Arcadia Data, etc.), highlighting the strengths and weaknesses of each category as well as the main options within the category based on the desired use case. You’ll leave with a solid understanding of the Hadoop BI landscape and an approach for structuring your own system evaluation.
Tomer Shiran is cofounder and CEO of Dremio, the data lake engine company. Previously, Tomer was the vice president of product at MapR, where he was responsible for product strategy, road map, and new feature development and helped grow the company from 5 employees to over 300 employees and 700 enterprise customers; and he held numerous product management and engineering positions at Microsoft and IBM Research. He’s the author of eight US patents. Tomer holds an MS in electrical and computer engineering from Carnegie Mellon University and a BS in computer science from the Technion, the Israel Institute of Technology.
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