DATA VISUALIZATION | A live online course with a Chief Analytics Evangelist at Google | ELVTR



18 OCT - 29 NOV 2022 6 WEEKS
Kevin HARTMAN Chief Analytics Evangelist / Google
Kevin Hartman


  • You want to build advanced visualizations
  • You want to tell compelling end-to-end data stories
  • You want to present data through dashboards and other visualizations



Chief Analytics Evangelist at GOOGLE


  • 01

    TUE (10/18) at 5 PM PST/8 PM EST

    Why Data Storytelling Matters

    Get introduced to the major pillars of successful data visualization.

    • Introducing data visualization
    • Why this skill?
    • Major frameworks
    • Major tools

    Assignment #01: Explore the provided dataset for Divvy. What stories do you anticipate unlocking here?

  • 02

    THU (10/20) at 5 PM PST/8 PM EST

    Planning a Data Story

    Learn how to create a planning guide for yourself and other analysts before starting a visualization.

    • Building a successful data story
    • Minto Pyramid Principle
    • In-class exercise: Planning a data story for Divvy

    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.

  • 03

    TUE (10/25) at 5 PM PST/8 PM EST

    Finding Stories  Through Exploratory Data Analysis

    Get familiar with software tools used to analyze data for patterns indicating the presence of a story.

    • Preparing data for analysis with Excel, SQL, and R/Python
    • Finding patterns in data
    • Converting plans to story outlines
    • In-class exercise: Interpreting patterns in Divvy visuals

    Assignment #03: Respond to the provided questions to better understand your organization's data analysis priorities and opportunities.

  • 04

    THU (10/27) at 5 PM PST/8 PM EST

    Conducting Advanced Exploratory Data Analysis

    Kevin explains how software tools R and Python are used to reveal and visualize sophisticated patterns in complex data.

    • Understanding data visualization in R
    • Understanding data visualization in Python
    • Advanced data visualization techniques
    • In-class exercise: Interpreting patterns in advanced Divvy visuals

    Assignment #04: Produce a data visualization based on a provided Divvy dataset (or, use data from your own company) using R or Python.

  • 05

    TUE (11/1) at 5 PM PST/8 PM EST

    Lab #1: Exploratory Data Analysis

    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.

  • 06

    THU (11/3) at 5 PM PST/8 PM EST

    Client-Ready Dataviz, Part 1: Contrast

    Understand a framework for evaluating dataviz and the first pillar of that framework: the sophisticated use of contrast.

    • Brain science & visual interpretation basics
    • The components of good visual form
    • Understanding contrast in dataviz
    • In-class exercise: Improving the use of contrast in data visualizations
  • 07

    TUE (11/8) at 5 PM PST/8 PM EST

    Client-Ready Dataviz, Part 2: Clear Meaning

    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.

    • What makes clear meaning in dataviz
    • Spotting bad dataviz: Biases and manipulations
    • In-class exercise: Improving unclear data visualizations
  • 08

    THU (11/10) at 5 PM PST/8 PM EST

    Client-Ready Dataviz, Part 3: Refined Execution

    Understand the third and final pillar of the framework for evaluating dataviz, refined execution.

    • Refined execution in dataviz
    • Why prioritize?
    • In-class exercise: Improving refined execution in data visualizations
    • In-class exercise: Improving all elements of good dataviz

    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.

  • 09

    TUE (11/15) at 5 PM PST/8 PM EST

    Lab #2: Creating Client-Ready Dataviz

    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).

  • 10

    THU (11/17) at 5 PM PST/8 PM EST

    Presenting Information with Conviction & Persuasion

    Learn the skills needed to effectively present dataviz and persuade stakeholders at every level of the organization.

    • The ‘McCandless Method’ of data storytelling
    • Stakeholders needs & methods of persuasion
    • Ensuring a successful presentation
    • In-class exercise: Writing a ‘McCandless Method’-style narrative for a dataviz

    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.

  • 11

    TUE (11/22) at 5 PM PST/8 PM EST

    Building Dashboards

    Understand the fundamentals of good dashboard design and approaches used to create dashboards in popular tools like Tableau and Power BI.

    • Dashboard fundamentals
    • Tableau & Power BI for dashboards
    • Understanding the proper role dashboards should play
    • Building a communication plan around the dashboard
  • 12

    TUE (11/29) at 5 PM PST/8 PM EST

    Lab #3: Creating Dashboards

    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.


For more information about the course and the participation fee, please register!

By registering and clicking “ENROLL”, you agree to our Terms of Use, Privacy policy and Cookie Policy