Fundamentals of Data Science and Visualization

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Course Summary

A picture is worth a thousand words. Use data to state your case using easy-to-understand data visualization tools. Give your audience the freedom to adapt your data in new ways in interactive dashboards that answer immediate questions and uncovers new insights. Data visualization tools can help you communicate better both internally and with your partners.

With a deeper understanding of data visualization software packages, your organization can produce more intuitive data visualizations in less time and identify the best software solutions to optimize your team’s workflows. In this course, we will review best practices in data visualization design and use cases for Excel, Tableau, and R (programming language).

Learn how to clean and format data in Excel, create interactive dashboards in Tableau, and clean and visualize data in R. This course will help participants identify use-cases for each software package that maximize impact with minimal effort, expanding participants’ toolbox as an analyst. Join us to learn about how your organization can better leverage data visualization software!

Training Prerequisites:  

None! This course is designed as an introduction these software packages and data visualization methods. All participants need is to be ready to learn, ask questions, and overcome challenges.  

Tools: Laptop, wired/wireless mouse, Microsoft Excel, Tableau Desktop (personal, professional, or public version), and R Studio Cloud. Please install all applications and do any set-up before class. We will provide instructions for setting up R Studio Cloud before the first session.  

  • Microsoft Excel Online (free) is available at: Create an account/log in for access.  

  • Public version of the Tableau desktop is available at:  

  • Tableau Desktop 14-day free trial is available at:  

  • R Studio Cloud 

  • Download R: 

  • Download R Studio IDE:  


(all times in Eastern)  

Introduction to Data Science and Visualization in Excel 

November 9th 2:00-4:00 PM 

  • Before Class: Come prepared and ready to learn. Have Microsoft Excel pre-installed on their computer. 
  • Covering: Tall vs Wide Data; Database Design Elements; Understanding Microsoft Access; Excel Power Pivot; Querying and Loading Data; Transforming Data; Merging Data in Power Query; Pivot Tables and Pivot Charts; Chart Types; Creating a database; Useful Plug-Ins; Creating forecasts with the Analysis ToolPak. 
  • Key Takeaways: Participants will learn how to clean data in Excel using Power Query/Pivot and create a dashboard that visualizes IPEDS completer data by CIP code, matched with SOC data for their LDD.  

Introduction to Tableau 

November 10th 2:00-4:00 PM 

  • CoveringTableau basics and workspace; Connecting to a file; Creating a text table; Creating Sets and ParametersInserting a sheet in a tooltip; Creating an interactive map; Formatting – Mark Labels, Detail, Coloring; Actions; Creating an interactive drill down map. 
  • Key Takeaways: Participants will learn how to create a drilldown map that uses parameters, sets, and actions to rotate between county-level and multi-county-level views of migration into and out of a geography using IRS Statement of Income data 

Dashboard Design and Interactive Visualizations in Tableau 

November 16th 2:00-4:00 PM 

  • Before Class: Have a great Veteran’s Day. If you have not already, familiarize yourself with all materials listed in the Tableau Basic Pre-Recorded Sessions. (Download zip file here.)
  • Covering: ‘Case, When’ and ‘If, then’ functions; Converting data types; Using parameters across data sources; Creating a line chart; Creating a zoomable chart; Using Level of Detail Expressions; Formatting Dashboards. 
  • Key Takeaways: Participants will learn how to create an interactive dashboard that allows users to visualize population projections data and migration data for a selected county or Economic Development District using interactive features. 

Introduction to R and R Packages 

November 17th 2:00-4:00 PM 

  • Before Class: Complete R Studio Primer 1 and Primer 2. 
  • Covering: Introduction to R; Assigning Objects; Object Names and Syntax; Data Types; Installing R Packages; Importing Data with readxl; Pipe Operator; Introduction to Tidyverse; Selecting data; transforming data and splitting/merging columns; Mutate data with dplyr; Creating summary statistics; Calculating difference between rows; joining data; Converting data types;  
  • Key Takeaways: Participants will learn how to perform basic operations in R, load R packages, and join and mutate data to transform data to produce unemployment rate summary statistics.  

Visualizing your data in R with ggplot 

November 19th 2:00-4:00 PM 

  • Homework: Complete R Studio Primer 3 and Primer 4 and explore the remaining R primers!   
  • Covering: Introduction to GGplot; Loading ggplot;AES to define aesthetics; Changing axis labels and titles; faceting data; Installing the blscrapeR package; importing data; cleaning data; bar charts; histogram; box plots; month to month line plots; plotting maps. 
  • Key Takeaways: Participants will learn how to visualize and map LAUS data for their LDD using the blscrapeR package. 


Course Content

Expand All
Day 1 Overview and Resources
Day 1, Section 1 - Querying and Loading Data
Day 1, Section 2 - Analyzing Data Using Pivot Tables and Pivot Charts
Day 1, Section 3 - Further Analyzing Data
Day 1, Section 4 - Forecasting Data
Day 2 Overview and Resources
Day 2, Section 1 - Navigating the Tableau Workspace and Creating Our First Chart
Day 2, Section 2 - Creating a Table and a Map
Day 2, Section 3 - More on Map Creation in Tableau
Day 2, Section 4 - Further Analysis of Population Data in Tableau
Day 2, Section 5 - Interactive Map Creation in Tableau
Day 3 Overview and Resources
Day 3 Section 1 - Getting Started
Day 3, Section 2 - Adding a Zoomable Chart
Day 3, Section 3 - Dashboard Design
Day 4 Overview and Resources
Day 5 Overview and Resources