Book Image

Big Data Visualization

Book Image

Big Data Visualization

Overview of this book

Gain valuable insight into big data analytics with this book. Covering the tools you need to analyse data, together with IBM certified expert James Miller?s insight, this book is the key to data visualization success. ? Learn the tools & techniques to process big data for efficient data visualization ? Packed with insightful real-world use cases ? Addresses the difficulties faced by professionals in the field of big data analytics
Table of Contents (15 chapters)
Big Data Visualization
About the Author
About the Reviewer
Customer Feedback

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.