Big Data Glossary (Paperback)

"margin-top: 0px; margin-bottom: 14px; padding: 0px; font-family: Arial, sans-serif; background-color: rgb(255, 255, 255);"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."margin-top: -4px; margin-bottom: 14px; padding: 0px; font-family: Arial, sans-serif; background-color: rgb(255, 255, 255);"This handy glossary also includes a chapter of key terms that help define many of these tool categories:

NoSQL DatabasesDocument-oriented databases using a key/value interface rather than SQL

MapReduceTools that support distributed computing on large datasets

StorageTechnologies for storing data in a distributed way

ServersWays to rent computing power on remote machines

ProcessingTools for extracting valuable information from large datasets

Natural Language ProcessingMethods for extracting information from human-created text

Machine LearningTools that automatically perform data analyses, based on results of a one-off analysis

VisualizationApplications that present meaningful data graphically

AcquisitionTechniques for cleaning up messy public data sources

SerializationMethods to convert data structure or object state into a storable format
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.