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)

Getting started with structured data

In Chapter 3, Defining Data Models and Chapter 4, Categorizing Data Models, we learned more about data structures, its sources, and examples. In this chapter, we are going to stick to structured data and employ modeling techniques using Python; we are going to use CSV data and create a model that can be used to predict house prices using Python.

In this mini-project, we are going to use four Python modules or libraries, which are explained in the next few sections.

NumPy

NumPy is the abbreviation for Numerical Python. Instructions for installing NumPy can be found at instructions. NumPy has built-in functions to support array objects and a collection of routines, which can be utilized...