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Hands-On Big Data Modeling

You're reading from   Hands-On Big Data Modeling Effective database design techniques for data architects and business intelligence professionals

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788620901
Length 306 pages
Edition 1st Edition
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Authors (3):
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James Lee James Lee
Author Profile Icon James Lee
James Lee
Tao Wei Tao Wei
Author Profile Icon Tao Wei
Tao Wei
Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
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Table of Contents (17) Chapters Close

Preface 1. Introduction to Big Data and Data Management 2. Data Modeling and Management Platforms FREE CHAPTER 3. Defining Data Models 4. Categorizing Data Models 5. Structures of Data Models 6. Modeling Structured Data 7. Modeling with Unstructured Data 8. Modeling with Streaming Data 9. Streaming Sensor Data 10. Concept and Approaches of Big-Data Management 11. DBMS to BDMS 12. Modeling Bitcoin Data Points with Python 13. Modeling Twitter Feeds Using Python 14. Modeling Weather Data Points with Python 15. Modeling IMDb Data Points with Python 16. Other Books You May Enjoy

Why is streaming data different?

Big data is composed of massive databases, and millions or even billions of document files. One of the possible ways to generate insights from these datasets is by batch processing. One of the classical approaches of batch processing is called Hadoop's MapReduce paradigm. The processing time can take anywhere from minutes to hours, or even more—it all depends on the size of the job. But if we are thinking about insights in real time, we are more concerned about streaming data.

Streaming data can be defined as a sequence of digitally-encoded coherent signals that are used to send or receive information that is in the process of being transmitted.

Formally, it can be defined as any ordered pair (S, Δ) (S, Δ), where S is a sequence of tuples and Δ is a sequence of positive real-time intervals.

In order to humanize the...

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