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

Definitions and explanations

This is providing additional information or attributes about a data point.


This is adding a comparable value to a particular data point. For example, you might compute and add a national ranking to each total by state:


This is almost like adding an opposite to a data point to see if it perhaps determines a different perspective. An example might be reviewing average body weights for patients who consume alcoholic beverages versus those who do not consume alcoholic beverages:


These are the typical mathematical calculations (or summaries) on the data as a whole or by other categories within the data, such as mean, median, and mode. For example, you might add a Median Heart Rate for Age Group that each patient in the data is a member of:


Again, these are mathematical calculations (or summaries), such as range, variance, and standard deviation, but they describe the average of a dataset (or group within the data). For example...