Data Visualization Techniques [Video]

More Information
Learn
  • Understand, validate, and optimize your data for effective visualizations
  • Know how and when to use line charts, bar charts, dot plots, scatter plots, and distribution plots
  • Find out the best ways to maximize the impact of basic chart types
  • See how and when to use dot density, choropleth, and categorical maps
  • Get to know to optimize map displays
  • Create, build, and optimize network graphs using connected data
About

This course 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’ll 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. Our final section focuses on understanding network graphs, a powerful tool for displaying relationship data.

Style and Approach

In this course you will learn data visualization best practices starting with understanding, preparing, validating, and matching your source data to the most appropriate display types. We will then work through examples of how to create compelling charts, including simple types such as line and bar charts, followed by more advanced charts including dot plots, box plots, and bullet graphs. Following this, you will learn how to create exceptional maps for geographic data, with a focus on dot density, choropleth, and categorical map types. Our final section will teach you how to visualize connected data sets using powerful network graphs.

Features
  • Learn the best chart types based on your data source
  • Building effective maps with geo-based data
  • Creating engaging network graphs
Course Length 2 hours 35 minutes
ISBN 9781787280007
Date Of Publication 30 May 2017

Authors

Ken Cherven

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 uses Tableau on a daily basis in his current position, where he has built dozens of performance dashboards to track both marketing and operational metrics. He has also built many visualizations for his personal websites, especially utilizing Gephi and Sigma.js to explore and visualize network data.

He is very interested in tools related to the exploration of network data, typically using Gephi for most of his current output. He’s also interested in text analysis, where he’s used tools such as Aylien, RapidMiner, R, and Exploratory to begin understanding and visualizing underlying patterns in political speeches, email transmissions, and book content.

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. He frequently edits and styles network information using HTML and CSS, along with a bit of JavaScript.

He is also highly engaged in the world of data visualization, including but not limited to his daily work experience. 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