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Hands-On Data Analysis with Scala

You're reading from  Hands-On Data Analysis with Scala

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781789346114
Pages 298 pages
Edition 1st Edition
Languages
Author (1):
Rajesh Gupta Rajesh Gupta
Profile icon Rajesh Gupta
Toc

Table of Contents (14) Chapters close

Preface 1. Section 1: Scala and Data Analysis Life Cycle
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 staging

Once the data is extracted or delivered, it is generally staged into temporary storage for further processing. It is generally a good idea to keep data extraction/delivery storage separate from staging storage, although there are instances where this won't be necessary.

The staging area cleanly separates the following two aspects of the data ingestion process:

  • Data that has been extracted or delivered
  • New data that has to be processed

Once the data is staged completely, when we reach the further processing steps, such as cleaning, we do not have to be concerned about new data arriving. We can think of staged data as something that, once created, never changes and is immutable. This means that, to an already staged piece of data, no more data can be added, deleted, or modified. This is a very important data property that is necessary for reliable data processing...

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