Cover for Data Simplification

Data Simplification

Taming Information with Open Source Tools

Book2016

Authors:

Jules J. Berman

Data Simplification

Taming Information with Open Source Tools

Book2016

 

Cover for Data Simplification

Authors:

Jules J. Berman

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Book description

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification ... read full description

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Table of contents

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  2. Book chapterAbstract only

    Chapter 1 - The Simple Life

    Pages 1-44

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    Chapter 2 - Structuring Text

    Pages 45-89

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    Chapter 3 - Indexing Text

    Pages 91-133

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    Chapter 4 - Understanding Your Data

    Pages 135-187

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    Chapter 5 - Identifying and Deidentifying Data

    Pages 189-231

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    Chapter 6 - Giving Meaning to Data

    Pages 233-284

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    Chapter 7 - Object-Oriented Data

    Pages 285-319

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    Chapter 8 - Problem Simplification

    Pages 321-360

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    Index

    Pages 361-366

About the book

Description

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools.

This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data.

Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user.

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools.

This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data.

Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user.

Key Features

  • Discusses data simplification principles, methods, and tools that must be studied and mastered
  • Provides open source tools, free utilities, and snippets of code that can be reused and repurposed to simplify data
  • Explains how to best utilize indexes to search, retrieve, and analyze textual data
  • Shows the data scientist how to apply ontologies, classifications, classes, properties, and instances to data using tried and true methods
  • Discusses data simplification principles, methods, and tools that must be studied and mastered
  • Provides open source tools, free utilities, and snippets of code that can be reused and repurposed to simplify data
  • Explains how to best utilize indexes to search, retrieve, and analyze textual data
  • Shows the data scientist how to apply ontologies, classifications, classes, properties, and instances to data using tried and true methods

Details

ISBN

978-0-12-803781-2

Language

English

Published

2016

Copyright

Copyright © 2016 Elsevier Inc. All rights reserved.

Imprint

Morgan Kaufmann

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Authors

Jules J. Berman