To help you navigate the large number of new data tools available, this guide describes 60 of the most recent innovations, from NoSQL databases and MapReduce 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:
NoSQL Databases-Document-oriented databases using a key/value interface rather than SQL
MapReduce-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
