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Big Data Visualization

You're reading from   Big Data Visualization Bring scalability and dynamics to your Big Data visualization

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781785281945
Length 304 pages
Edition 1st Edition
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Concepts
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Author (1):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
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Chapter 4. Addressing Big Data Quality

In this chapter, we will talk about the categories of categorized data quality and the challenges big data brings to them. In addition, we will offer examples demonstrating concepts for effectively addressing these areas.

The chapter is organized into the following main sections:

  • Data quality categorized
  • DataManager
  • DataManager and big data
  • Some examples
  • More examples

To make programming a bit easier, programming languages categorize data into types or a datatype. These categories of data are a defined kind or a set of possible values allowed by the type and allow progress to be made or, specifically, solutions to be crafted.

The same concept may be applied to the challenge of data quality. By understanding the categories of data quality, it makes it easier (while using an appropriate tool choice) to identify and address issues with the quality of your big data.

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