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Hands-On Data Analysis with Scala

You're reading from   Hands-On Data Analysis with Scala Perform data collection, processing, manipulation, and visualization with Scala

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789346114
Length 298 pages
Edition 1st Edition
Languages
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Author (1):
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Rajesh Gupta Rajesh Gupta
Author Profile Icon Rajesh Gupta
Rajesh Gupta
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Table of Contents (14) Chapters Close

Preface 1. Section 1: Scala and Data Analysis Life Cycle FREE CHAPTER
2. Scala Overview 3. Data Analysis Life Cycle 4. Data Ingestion 5. Data Exploration and Visualization 6. Applying Statistics and Hypothesis Testing 7. Section 2: Advanced Data Analysis and Machine Learning
8. Introduction to Spark for Distributed Data Analysis 9. Traditional Machine Learning for Data Analysis 10. Section 3: Real-Time Data Analysis and Scalability
11. Near Real-Time Data Analysis Using Streaming 12. Working with Data at Scale 13. Another Book You May Enjoy

Organizing and storing

Once all of the processing related to data is completed, it is organized and stored in such a way that consumers of data can begin using the data. This act is equivalent to publishing data and making it available for usage.

Data usage generally drives how data is organized and stored. Time series data is generally organized by time dimensions. For example, we could organize data coming from Internet of Things (IoT) devices in the following hierarchy:

  • Year
  • Month
  • Day
  • Hour
  • Minute

In this context, year, month, day, hour, and minute are the functions of the event occurrence time. For example, if the occurrence time is 2018-10-31 15:30:45 UTC, then it will have the following values:

  • Year = 2018
  • Month = 10
  • Day = 31
  • Hour = 15
  • Minute = 30

Another way to organize the data could be by using the device type, or even a mix of both time dimensions and device type...

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