NEW GUIDE

Big Data

Volume, Variety, & Velocity

Regardless of data type, company size, or industry, the three Vs of big data – volume, velocity, and variety – continue to be a challenge. For the 2019 Big Data Guide, we surveyed developers to learn how they meet these challenges. What tools are in their technology stack? And what processes and languages do they rely on? Some of their answers were expected. Some will surprise you.

Discover how to master challenges from defining a performance management strategy to designing big data building blocks to understanding which open-source tools work best for computation and analytics.

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What You'll Learn
 

Get More from Your Big Data Stack

Learn how to refit your performance management strategy to include full-stack data collection, event-driven data processing, and AI-driven insights. Download Guide

 

Why Spark is Exploding onto the Big Data Scene

In addition to an increasing use of Python and R, more survey respondents reported using Spark as part of their data science, data streaming, and data processing ecosystem. Why the uptick? Flexibility. Check out the use cases to gauge its fit for your machine learning, stream processing, data integration, and interactive analytics. Download Guide

 

Getting Out of a Python Pickle with HDF5

Python users love pickle files. They're convenient, built-in, and easy to save and load. But they bog down when faced with large amounts of data. HDF5 is a data storage system designed for huge geospatial data sets and picks up perfectly where pickle files leave off. Download Guide

 

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