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 Weather Data Points with Python

Weather data can be found everywhere. These datasets can be useful in determining weather patterns and predicting weather based on historical datasets. This chapter uses weather data points in Python to model it according to the tips and tricks learned in this book. We try to consume data in raw format, transform into the correct format, a model using Python, and interpret the model thus produced. In this chapter, you will be learning about the following:

  • How to discover the nature of weather data
  • Creating models from weather data with Python
  • Interpreting the data model discovered