This is the code repository for Big Data Visualization, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
When it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations to improve better decision making.
This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore “big data oriented” tools such as Hadoop and Tableau.
We will show you how data changes with different variables and how to visualize data in real time and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics, the work arounds to typical big data visualization challenges, and the most popular libraries that work with big data.
The choice of visualizations depends on the most suited techniques for big data, and we will show you the various options for big data visualizations based upon industry-proven techniques that are most suited for big data. You will then learn how to integrate popular visualization tools with graphing databases to see how huge amounts of certain data can be visualized. Finally, you will find out how to display the integration of visual big data with BI using Cognos BI.
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
The code will look like the following:
for row in reader:
if (row['Denomination']) == 'Penny':
if int(row['Coin-in'])<2000:
x += int(row['Coin-in'])
row_count += 1
Most of the tools and technologies used in this book are open source and available for no charge. All of the others offer free trials for evaluation. With this book, and some basic exposure to data analysis (or basic programming concepts) the reader will be able to gain valuable insights to the world of big data visualization!
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