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Rapid Data Exploration and Analysis with Apache Superset

Published by O'Reilly Media, Inc.

Beginner to intermediate content levelBeginner to intermediate

Learn to rapidly explore and visualize data with open source tools

An ever-increasing number of organizations and industries are realizing the immense value of their data, but many still struggle to extract value from the data they collect. While there are countless tools to assist in this effort, many are quite complex, costly, or both. Luckily, there’s Superset, an extremely powerful open source BI tool that can enable anyone from a nontechnical business analyst to a data scientist to rapidly explore and analyze their data.

Join expert Charles Givre to learn how to use Superset to more effectively extract insights from your data, efficiently and cost-effectively. You’ll discover how to query your data and create interactive visualizations (and even dashboards)—all without writing code. And if you’re comfortable with SQL, you’ll see how you can use Superset’s SQL Lab for even more advanced functionality.

What you’ll learn and how you can apply it

By the end of this live online course, you’ll understand:

  • How to connect Superset to various data sources
  • How to explore and visualize that data
  • How to share your insights by creating interactive dashboards

And you’ll be able to:

  • Configure Superset to connect to a data source
  • Create views of tables and customize the presentation of these tables
  • Create visualizations of the data from your data source
  • Create interactive dashboards
  • Use Superset’s SQL Lab to create new datasets and tables

This live event is for you because...

  • You work with data.
  • You want to explore your data more efficiently and effectively.
  • You want to become a better data analyst or data scientist.

Prerequisites

  • A computer with course setup completed (installation instructions forthcoming)
  • Familiarity with principles of data analysis and visualization
  • A basic understanding of SQL (see recommended preparation for ways to level up your knowledge)

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Introduction to Superset (15 minutes)

  • Presentation: Overview of Superset; walk-through of Superset examples
  • Q&A

Connecting data sources (40 minutes)

  • Presentation: Superset’s data model; adding a database; uploading a CSV file; exploring the database schema; adding a table; customizing the table; viewing and customizing the fields
  • Hands-on exercise: Create a table from a CSV file
  • Q&A

Break (5 minutes)

Visualizing single dimensional data (30 minutes)

  • Presentation: Walk-through of Superset’s data explorer interface; creating a table with curated columns; creating a bar chart; visualizing a distribution with a histogram; adding a visualization to a dashboard; customizing the appearance of a visualization
  • Hands-on exercise: Create a visualization
  • Q&A

Complex visualizations (25 minutes)

  • Presentation: Time series visualizations; multiple time series; network diagrams and force-directed graphs; chord diagrams; annotating a chart
  • Hands-on exercise: Create a visualization of computer network activity
  • Q&A

Break (5 minutes)

Geospatial visualizations (30 minutes)

  • Presentation: Overview of Superset’s geospatial capabilities; configuring Superset for geospatial visualizations; creating population density maps; drawing arcs; paths
  • Hands-on exercise: Create a geospatial visualization
  • Q&A

SQL Lab (15 minutes)

  • Presentation: Overview of SQL Lab; executing a query; querying diverse data sources; using templates in queries; creating a view from SQL Lab; visualizing a view
  • Hands-on exercise: Create a visualization of network activity
  • Q&A

Dashboards (15 minutes)

  • Presentation: Overview of Superset dashboards; adding visualizations to dashboard; adding tabs; filtering data on a dashboard
  • Hands-on exercise: Create an interactive dashboard using a series of visualizations
  • Q&A

Your Instructor

  • Charles Givre

    Charles Givre is a lead data scientist in the Cybersecurity Technology and Controls Group at JPMorgan Chase, where he works at the intersection of cybersecurity and data science. Previously, he was a senior lead data scientist at Booz Allen Hamilton on one of the firm's largest analytic programs, where he led data science efforts and worked to expand the role of data science in the program, and worked as a counterterrorism analyst at the Central Intelligence Agency for five years. One of his research interests is increasing the productivity of data science and analytic teams; to that end, he’s been working extensively to promote the use of Apache Drill in security applications and has contributed to the codebase. He’s also a coauthor of Learning Apache Drill from O’Reilly.

    Charles is passionate about teaching others data science and analytic skills and has led data science classes all over the world for clients, universities, and conferences, including Black Hat and the Center for Research in Applied Cryptography and Cyber Security at Bar-Ilan University. A sought-after speaker, he’s also delivered presentations at major industry conferences such as Strata-Hadoop World, Open Data Science Conference, and others. He recently served as program chair of the Strategic Analytics Program at Brandeis University's Graduate School of Professional Studies and is currently a member of the advisory board. He holds a master’s degree in Middle Eastern studies from Brandeis University as well as both a bachelor of science in computer science and a bachelor of music from the University of Arizona. Charles speaks French reasonably well and plays trombone. He lives in Baltimore with his family and in his nonexistent spare time is restoring a classic British sports car.

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Skill covered

Data Engineering