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Hands-On Big Data Modeling

Book Name

This is the code repository for [Hands-On Big Data Modeling](Packt UTM URL of the Book), published by Packt.

Effective database design techniques for data architects and business intelligence professionals

What is this book about?

Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements.

This book covers the following exciting features:

  • Get insights into big data and discover various data models
  • Explore conceptual, logical, and big data models
  • Understand how to model data containing different file types
  • Run through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modeling
  • Create data models such as Graph Data and Vector Space

If you feel this book is for you, get your copy today!

https://www.packtpub.com/

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

wordcloud = WordCloud(background_color="white",width=1000, height=860, margin=2).generate(text)
import matplotlib.pyplot as plt
plt.imshow(wordcloud)

Following is what you need for this book: This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.

With the following software and hardware list you can run all code files present in the book (Chapter 1-15).

Software and Hardware List

Chapter Software required OS required
1-15 Python, R, Jupyter Notebook Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

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Get to Know the Authors

James Lee is a passionate software wizard working at one of the top Silicon Valley-based start-ups specializing in big data analysis. In the past, he has worked at big companies such as Google and Amazon. In his day job, he works with big data technologies, including Cassandra and Elasticsearch, and is an absolute Docker technology geek and IntelliJ IDEA lover with a strong focus on efficiency and simplicity. Apart from his career as a software engineer, he is keen on sharing his knowledge with others and guiding them, especially in relation to start-ups and programming. He has been teaching courses and conducting workshops on Java programming / IntelliJ IDEA since he was 21. James holds an MS degree in computer science from McGill University and has many years' experience as a teaching assistant in a variety of computer science classes. He also enjoys skiing and swimming, and is a passionate traveler.

Tao Wei is a passionate software engineer who works in a leading Silicon Valley-based big data analysis company. Previously, Tao worked in big IT companies, such as IBM and Cisco. He has intensive experience in designing and building distributed, large-scale systems with proven high availability and reliability. Tao has an MS degree in computer science from McGill University and many years of experience as a teaching assistant in various computer science classes. When not working, he enjoys reading and swimming, and is a passionate photographer.

Suresh Kumar Mukhiya is a PhD candidate currently associated with Western Norway University of Applied Sciences (HVL). He is also a web application developer and big data enthusiast specializing in information systems, model-driven software engineering, big data analysis, and artificial intelligence. He has completed a masters in information systems from the Norwegian University of Science and Technology, along with a thesis in processing mining. He also holds a bachelor's degree in computer science and information technology (BSc.CSIT).

Other books by the authors

Suggestions and Feedback

Click here if you have any feedback or suggestions.

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781788620901

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