Name: Big Data Processing Engines - Which One Do I Use?
Start: 2019-04-30T19:00:00-04:00
End: 2019-04-30T21:00:00-04:00
Location: The Garage at ROAM Buckhead

Abstract:
Columnar storage is an often-discussed topic in the big data processing and storage world today - there are hundreds of formats, structures, and optimizations into which you can store your data and even more ways to retrieve it depending on what you are planning to do with it. This plethora of options came about due to the need to not only ingest data quickly using On-Line Transactional Processing, or OLTP, tools, but because of the need to consume and analyze data with more and more speed using On-Line Analytical Processing, or OLAP, tools. Thousands of different use cases each have their own specific needs and thus, many options surface to choose from. For example, reading stock market ticker data requires a completely different mindset than analyzing quality metrics in a manufacturing line. With all these choices, it's easy to get lost when navigating to your end goal: choosing a tool that works for you.

Bio:
Ashish Narasimham is a Solutions Architect based out of Atlanta with a background in software consulting and product management. Before Hortonworks, he was working as a front-end, back-end, and full-stack software engineer throughout his last job consulting at Daugherty Business Solutions so he knows his way around the stack. He loves talking tech and has worked on many projects in the Hadoop ecosystem across the various technologies in the HDP, HDF, and DPS products, specializing in cloud technologies and Hortonworks’ integration with them. Please feel free to approach him with your Big Data (or anything else) questions!

Craig Warman

Big Data ATL

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Cloud Computing

Big Data

MapReduce

Hadoop

Business Intelligence & Data Warehousing

Data Mining

NoSQL

Machine Learning

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Data Analytics

Open Source

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Big Data Processing Engines - Which One Do I Use?

The Garage at ROAM Buckhead

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Big Data Processing Engines - Which One Do I Use?

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