Book Image

Hands-On Big Data Modeling

By : James Lee, Tao Wei, Suresh Kumar Mukhiya
Book Image

Hands-On Big Data Modeling

By: James Lee, Tao Wei, Suresh Kumar Mukhiya

Overview of this book

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. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently.
Table of Contents (17 chapters)

Modeling with the IMDb dataset

Most of the libraries used in this hands-on exercises must be familiar to you by now. The libraries used in modeling the dataset are as follows:

  • pandas: For data structure and data analysis in an easier way
  • NumPy: For adding support for large, multi-dimensional arrays and matrices
  • scikit-learn: For most machine learning algorithms
  • Matplotlib: For generating graphs

Starting the platform

Let's start modeling the data using Python. The first step in any modeling is getting your system started. I am using IPython Jupyter (http://jupyter.org/) to run the code. The easiest way to get started with Jupyter is to install it using Anaconda (https://anaconda.org/). Download the right platform from...