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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

Data Ingestion

In this chapter, we will look into the data ingestion aspects of the data life cycle. Data ingestion is a very broad term; however, we will concentrate on some of the most important aspects of it. Data is generally considered to be ingested when it is ready for usage in enterprise systems. In reality, a significant amount of effort is required to perform data ingestion effectively and efficiently.

Data ingestion typically involves the following key tasks, which are also the topics that will be covered in this chapter:

  • Data extraction
  • Data staging
  • Data cleaning
  • Data normalization
  • Data enrichment
  • Data organization and storage

At times, there are more tasks involved as part of data ingestion. There are also situations where some of these tasks might not be necessary and two or more could be combined into a single task.

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