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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

Cleaning and normalizing

Staged data is considered to be immutable. Immutability in this context implies that staged data, once created, never changes. Now, the data cleaning and normalizing process can start. This step could also involve determining the degree of errors in the data received. In particular, it is expected that big data will have a certain amount of errors.

Raw data coming from external sources comes in a variety of formats. These formats are generally designed for data delivery and are not suitable for use by systems consuming data. It is also very common for some of the information to be clubbed together as part of data delivery; however, the consumer of the data needs to have more fine-grained access to the information.

An example of this is the address part of the data. The data producer might provide a free-form address. The contained information, such as...

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