To help you navigate the large number of new data tools available, this guide describes 60 of the most recent innovations, from No SQL databases and Map Reduce approaches to machine learning and visualization tools. Descriptions are based on first-hand experience with these tools in a production environment.This handy glossary also includes a chapter of key terms that help define many of these tool categories:No SQL Databases Document-oriented databases using a key/value interface rather than SQLMap Reduce Tools that support distributed computing on large datasets Storage Technologies for storing data in a distributed way Servers Ways to rent computing power on remote machines Processing Tools for extracting valuable information from large datasets Natural Language Processing Methods for extracting information from human-created text Machine Learning Tools that automatically perform data analyses, based on results of a one-off analysis Visualization Applications that present meaningful data graphically Acquisition Techniques for cleaning up messy public data sources Serialization Methods to convert data structure or object state into a storable format
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