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Make Data Work
Oct 15–17, 2014 • New York, NY

Big Data Anti-Patterns

Douglas Moore (Think Big Analytics)
11:50am Friday, 10/17/2014
Data Science
Location: 1D
Average rating: **...
(2.92, 12 ratings)
Slides:   external link

Big Data Anti-Patterns: Lessons from the Front Lines

The genesis of these popular anti-patterns come from three myths:

  1. “Oh, it’s a little bit in-efficient, just throw more machines at it” – Ruby vs. Java for ETL
  2. “It’s supported by the Hadoop vendor, let’s use that” – Flume vs. Spring Batch for bulk loads
  3. “It’s GA, let’s use that to replace our MPP database” – Impala vs. HBase for fast query

We will explore these myths and where they come from, the results and pain we’ve seen in real world projects, and what we did to correct the situation.

Photo of Douglas Moore

Douglas Moore

Think Big Analytics

Mr. Moore is Principal Big Data Architect for Think Big Analytics and architect of the system described in this presentation. Mr. Moore’s experience spans 25 years of integrating data collection, analysis, OLTP, OLAP, Data Warehouse and graphics systems. Mr. Moore has a Bachelors and Masters in Electrical Engineering and has worked for IBM, Sapient, SmartEnergy and Accius.