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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Outliers


In this chapter, we want to deal with the manipulation of big data sources to address data outliers. So let's have a quick reminder for the reader:

Outliers can be defined as:

  • A data point that is way out of keeping with the others

  • That piece of data that doesn't fit

  • Either a very high value or a very low value

  • Unusual observations within the data

  • An observation point that is distant from all others

Options for outliers

The options that are generally accepted for dealing with found outliers in big data are:

  • Delete: This includes the outlier values or even the actual variable where the outliers exist

  • Transform: This includes the values or the variable itself

Delete

If you have just a few outliers, you may decide to simply delete those outlying values (they then become blank or missing values, which usually are easier to deal with in a visualization). Also, if the variable just doesn't make sense, or if there are just too many outliers in that variable (or maybe you just don't need the variable...