Learning Path: Big Data Visualization

Gain hands-on experience in creating effective visualizations of your data

What you'll learn

Find out how to utilize visualization best practices

Discover how to identify and understand your source data

Get to know how to match your dataset to the appropriate visualization type

See how to optimize basic chart types for maximum impact

Understand, validate, and optimize your data for effective visualizations

Find out the best ways to maximize the impact of basic chart types

Get to know to optimize map displays

Create, build, and optimize network graphs using connected data

Requirements

Basic knowledge of HTML, CSS, and JavaScript would be helpful, but is not manadatory

Some experience with database, spreadsheet, and presentation software will be beneficial

Description

Data visualization is becoming critical in today’s world of Big Data. If you are a data analyst or a Big Data enthusiast and want to explore the various techniques of data visualization, then this Learning Path is for you! This Learning Path focus on building a variety of data visualizations using multiple tools and techniques!
Packt’s Video Learning Paths are a series of individual video products put together      in a logical and stepwise manner such that each video builds on the skills learned in the video before it. The highlights of this Learning Path are:
Learn why data visualization is important, and how it can be used to manage Big Data Learn best practices in data visualization and apply them to your own displays
Let’s take a quick look at your learning journey. To start with, we will walk you through an overview of the basic principles of data visualization, why they are important, and how they can be used to make visualizations highly effective. We will then walk you through some of the basics such as how to build visualizations using best practices. You'll also learn how to identify data types and match them with the appropriate display formats.Then, we will focus on building a variety of data visualizations using multiple tools and techniques. This is where we will put the theory together with actual hands-on experience of creating effective visualizations. Our efforts will be spent on choosing the best display types for our dataset, and then applying best practice principles to our selected charts, maps, or network graphs. We will spend considerable time on some of the most useful chart types, followed by a section where we explore the multiple uses of maps as visualizations. Finally, we will focus on understanding network graphs, a powerful tool for displaying relationship data.
By the end of this Learning Path, you will have a strong understanding of how to effectively visualize your data.
About the Author
Ken Cherven has been creating data visualizations for more than 10 years using a variety of tools, including Excel, Tableau, Cognos, D3, Gephi, Sigma.js, and Exhibit, along with geospatial tools such as Mapbox, Carto, and QGIS. He has built many visualizations for his personal websites, especially utilizing Gephi and Sigma.js to explore and visualize network data. His experience in building data visualizations has intersected with many technologies, including a variety of SQL-based tools and languages including Oracle, MySQL, and SQLServer. His work is based on a thorough understanding of visualization principles learned through extensive reading and practice. He also uses his websites to display and promote visualizations, which he shares with a wider audience. He has previously authored two books on Gephi for Packt, and has also presented at multiple data visualization conferences.

Overview

Section 1: Learning Data Visualization

Lecture 1 The Course Overview

Lecture 2 Visualizing Is Critical to Understanding

Lecture 3 Taming Big Data through Visualization

Lecture 4 Utilizing Visualization Tools

Lecture 5 Introducing Visualization Best Practices

Lecture 6 Designing for Visual Clarity

Lecture 7 Driving User Focus

Lecture 8 Working with Element Sizing

Lecture 9 Employing Color Effectively

Lecture 10 Data Types Overview

Lecture 11 Categorical Data

Lecture 12 Time Series Data

Lecture 13 Point (X-Y) Data

Lecture 14 Geospatial Data

Lecture 15 Network Data

Lecture 16 Unstructured Data

Lecture 17 Line Charts

Lecture 18 Bar Charts

Lecture 19 Scatter Plots

Lecture 20 Distribution Plots

Lecture 21 Dot Plots

Section 2: Data Visualization Techniques

Lecture 22 The Course Overview

Lecture 23 Understanding the Data

Lecture 24 Preparing the Data

Lecture 25 Validating the Data

Lecture 26 Selecting the Best Display Option

Lecture 27 Creating Effective Line Charts

Lecture 28 Building Powerful Bar Charts

Lecture 29 Designing Effective Dot Plots

Lecture 30 Building Distribution Plots

Lecture 31 Creating Effective Scatterplots

Lecture 32 Working with Box Plots

Lecture 33 Mastering Bullet Graphs

Lecture 34 Understanding Your Map Data

Lecture 35 Building Dot Density Maps

Lecture 36 Creating Categorical Maps

Lecture 37 Designing Choropleth Maps

Lecture 38 Enhancing Your Map

Lecture 39 Sharing a Map

Lecture 40 Creating and Procuring Network Data

Lecture 41 Building a Network Graph

Lecture 42 Understanding Graph Metrics

Lecture 43 Styling the Graph by Sizing Elements

Lecture 44 Styling the Graph Using Color

Lecture 45 Sharing the Graph

This Learning path is for data analysts and data enthusiasts who are looking to learn what is data visualization and its different techniques.