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)

Importing Bitcoin data into iPython

In order to process the Bitcoin data, the first step is to get started with iPython. As mentioned in earlier chapters, iPython can be installed in different ways. One of the ways is described in Chapter 6, Modeling Structured Data, and Chapter 15, Modeling IMDb Data Points with Python, using Anaconda. Assuming you have iPython running, let's open a notebook and get started.

Importing required libraries

The first step is to import all the required libraries. This can be done as follows:

#import the packages
import math
import pandas as pd
import numpy as np
import os
from pandas import DataFrame
from sklearn.cluster import KMeans
from sklearn import preprocessing
import matplotlib.pyplot as...