Learn how to unlock value from data with crystal clear visualizations — and create an end-to-end data story for a real business!
Join Kevin Hartman, Google, for this hands-on exploration of effective data visualization and storytelling.
Learn how to plan out a story you want to tell, identify the data you will need, analyze data and find patterns. Start getting the most out of data viz tools to create clear, effective visuals for your audience.
Discover the role of dashboards and other tools for communicating data insights effectively. Practice presenting your own data story, backed up by supporting evidence.
How do the other guys get their dataviz to look so good? Learn how to leverage advanced tools like R Studio and Jupyter Notebook (Python) to tell compelling data stories.
But since you know it doesn't, why not get help landing the right data message from a Google data leader?
This course teaches expert approaches to visualizing patterns in data and coaxing out clear stories that stand up to scrutiny. You'll finish with a client-ready dataviz, dashboard, and presentation.
Learn data visualization in the course that combines live instruction from a proven analytics leader with live labs and instructor office hours!
Upgrade your technical skills with live training. This course lets you add to your toolbox requisite tools for professional data visualization like Excel, mySQL, R Studio, Jupyter Notebook, and Tableau.
Get introduced to the major pillars of successful data visualization.
Assignment #01: Explore the provided dataset for Divvy. What stories do you anticipate unlocking here?
Learn how to create a planning guide for yourself and other analysts before starting a visualization.
Assignment #02: Data Story Plan
Use the provided dataset to help Divvy rebalance their bike system, or tackle your own business challenge. Your deliverable will be a Minto-style plan for your data story.
Get familiar with software tools used to analyze data for patterns indicating the presence of a story.
Assignment #03: Respond to the provided questions to better understand your organization's data analysis priorities and opportunities.
Kevin explains how software tools R and Python are used to reveal and visualize sophisticated patterns in complex data.
Assignment #04: Produce a data visualization based on a provided Divvy dataset (or, use data from your own company) using R or Python.
Use software tools (including SQL, Google Sheets, Tableau, and R) to gather and analyze data from the Divvy database. You will first perform exploratory data analysis to look for patterns in Divvy data that indicate the presence of a story. Then, you will use visuals to inform their interpretation of the Key Questions in a plan. Convert your plan into a solid outline for a data story.
Assignment #05: Exploratory Data Analysis
Refer to the Divvy case study and database to analyze data for patterns indicating the presence of a story. Use the tools demoed in class to create exploratory analysis charts.
Understand a framework for evaluating dataviz and the first pillar of that framework: the sophisticated use of contrast.
Understand the second pillar of the framework for evaluating dataviz, clear meaning, and learn how to spot and counter bad practices that lead to the manipulation of a chart’s meaning.
Understand the third and final pillar of the framework for evaluating dataviz, refined execution.
Assignment #06: Evaluate a provided Divvy dataviz (or, alternatively, a dataviz from work at your own company) using the framework introduced during lecture. Offer recommendations for how the dataviz can be improved.
This lab focuses on converting the efficiently generated, yet visually lacking, visuals produced during the Exploratory Data Analysis lab into “client-ready” visualizations that effortlessly communicate insight.
You will be challenged to demonstrate a sophisticated use of contrast to attract the audience’s attention to important patterns in the data. Use this technique to create a clear expression of meaning through the effective use of common chart elements, and a level of refined execution that minimizes distractions.
Then, generate visuals using tools including Excel, R, Tableau, and/or Power BI. A presentation software, such as Google Slides, PowerPoint, or Keynote, will serve as the canvas for your output.
Assignment #07: Client-ready Dataviz
Start working on your presentation for the Divvy executive team. Use the provided data set to create a series of client-ready charts from provided Divvy data (or, alternatively, data from your own company).
Learn the skills needed to effectively present dataviz and persuade stakeholders at every level of the organization.
Assignment #08: Data Storytelling Presentation Practice
Write a McCandless Method-style narrative for one of the dataviz you've created for the Divvy executive team (or, alternatively, a dataviz you created from your own company’s data). Record yourself presenting the narrative and submit to Kevin for feedback.
Understand the fundamentals of good dashboard design and approaches used to create dashboards in popular tools like Tableau and Power BI.
In this lab, you'll gain a practical understanding of the proper (and improper) use of dashboards, as well as the basics elements of effective dashboard design. Get hands-on with Tableau or Power BI to build a dashboard and apply the rules of effective dashboard design to create a “client-ready” deliverable for Divvy.
Assignment #09: Dashboard
The Divvy executive team believes it's important to stay on top of the patterns and trends you've found in the data. Bring together all the work you've done so far to create a dashboard for Divvy built in Tableau, Power BI, or another dashboarding tool of your choice.