Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788620901
Length 306 pages
Edition 1st Edition
Languages
Tools
Concepts
Arrow right icon
Authors (3):
Arrow left icon
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
Arrow right icon
View More author details
Toc

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

To get the most out of this book

To get the most out of this book, we assume that readers have the following prerequisite knowledge:

  • An understanding of DBMSes, data modeling, and UML
  • An understanding of requirement analysis and conceptual data modeling
  • An understanding of the concepts of data warehousing, data mining, and data mining tools
  • An understanding of the basic concepts of data management, data storage, data retrieval, and data processing
  • An understanding of basic programming skills using Python, R, or any other programming language

We also expect readers to follow the resources that are highlighted as further reading at the end of each chapter. In addition to this, all the code shared in the GitHub will not be the only solution. There can be multiple ways of modeling big data. What we have presented in this book is just one of these ways involving open source technologies.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packt.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-Big-Data-Modeling. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in the text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system."

A block of code is set as follows:

$ brew install python
$ python3

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

wordcloud = WordCloud(background_color="white",width=1000, height=860, margin=2).generate(text)
import matplotlib.pyplot as plt
plt.imshow(wordcloud)
rcParams['figure.figsize'] = 20, 10
plt.axis("off")
plt.show()

Any command-line input or output is written as follows:

C:\Users\Sureshhardiya\python3 --version
Python 3.6.1

Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Select System info from the Administration panel."

Warnings or important notes appear like this.
Tips and tricks appear like this.
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime