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Big Data Analytics with Hadoop 3

You're reading from   Big Data Analytics with Hadoop 3 Build highly effective analytics solutions to gain valuable insight into your big data

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788628846
Length 482 pages
Edition 1st Edition
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Author (1):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Hadoop FREE CHAPTER 2. Overview of Big Data Analytics 3. Big Data Processing with MapReduce 4. Scientific Computing and Big Data Analysis with Python and Hadoop 5. Statistical Big Data Computing with R and Hadoop 6. Batch Analytics with Apache Spark 7. Real-Time Analytics with Apache Spark 8. Batch Analytics with Apache Flink 9. Stream Processing with Apache Flink 10. Visualizing Big Data 11. Introduction to Cloud Computing 12. Using Amazon Web Services

Visualization using Tableau

Whichever method we use to perform distributed computing on big data, its very hard to comprehend the meaning of the data without the aid of tools such as Tableau, which can provide an easy to understand visualization of data.

We can do visualization using many tools such as Cognos, Tableau, Zoom data, KineticaDB, Python Matplotlib, R + Shiny, JavaScript, and so on. We will cover visualization in more detail in Chapter 10, Visualizing Big Data.

The following is a simple horizontal bar chart in Tableau:

Figure: Screenshot showing a simple horizontal bar chart in Tableau

The following is a geospatial view of data in Tableau:

Figure: Screenshot of a geospatial view of data in Tableau
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