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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

A unified approach to big data modeling and data management

As mentioned, big data can be unstructured or semi-structured, with a high level of heterogeneity. The information expressed in these datasets is an essential factor in the process for supporting decision making. That is one of the reasons that heterogeneous data must be integrated and analyzed to present a unique view of information for many kinds of applications. This section addresses the problem of modeling and integrating heterogeneous data that originates from multiple heterogeneous sources in the context of cyber-infrastructure systems and big data platforms.

The growth of big data swaps the planning strategies from long-term thinking to short-term thinking, as the management of the city can be made more efficient. Healthcare systems are also reconstructed by the big data paradigm, as data is generated from sources...

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