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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

Table of Contents (14) Chapters

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 journey

Let's look at the journey of data from its creation to its usage:

  • Raw data creation: The observation, event, action, and manual entry are the key elements that contribute to data creation. This data is typically persisted as a raw data source for future usage. The persistent storage could be flat files, a database, a Kafka topic, AWS Kinesis Data Streams (KDS), or any other suitable storage.
  • Raw data extraction: Raw data extraction is the act of receiving or fetching raw data from a source. In an enterprise, raw data sources are internal as well as external. Some examples of commonly used external sources are currency exchange rates, stock prices, and weather data. A company's transactional data is an example of internal data.
  • Raw data ingestion: Raw data ingestion refers to the act of storing raw data in an organized form to support orderly data extraction...
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