In this course I will make all of the datasets publicly available to encourage students to walk through the actual analysis with me! Links to each set will be provided at the beginning of each section (**links to the datasets are located in lectures 3, 7, and 11**)
Tableau is a rapidly growing data visualization and analysis software application. Developing this skill set early will give you a differentiated advantage in searching for jobs and displaying data you may currently work with.
This Tableau course is meant for anyone looking to get an overview displaying the software's capability. I will be working with different types of data to show you when and how to use the different views Tableau offers, including Maps, Parameters, Calculated Fields, Bar Charts, Line Charts, and Tables (with heat map variations). I will walk through 3 separate analyses using different data sources to highlight the software's functionality.
Link to shared drive folder containing the publicly available data, download if you want to analyze with me!
We'll be analyzing data from the game show "The Price is Right". In this lecture I show you where I got the data source, and how to load it into Tableau.
In this lecture I highlight the best and worst game types and seasons by win % for the Price is Right. (Bar charts, formatting axes, coloring charts, labels)
Creating a heat map of game types and win %'s to see when I'd be most/least likely to win. (Tableau table, coloring labels, formatting labels, displaying multidimensional data cleanly, winning The Price is Right)
Showing you the data source, the logic behind the exponential decay formula, and how to load into Tableau
I'll show you how to plot out exponential decay of multiple caffeinated beverages on the same chart (a tricky task in Tableau), and I'll also show you how to implement an unconventional date parameter (hours passed since caffeine consumption) by tricking Tableau using the date field.
(multiple measures on same axis, modifying date field to suit our needs, line chart, basic formatting)
In this lecture I show you how to create your own tool that calculates how long a given caffeine value will remain in someone's system X hours after consumption.
(user parameters, calculated fields, line chart, pairing parameters and measures, learning exactly what insane amounts of caffeine you may have in you at any given time)
Showing you how to use Tableau's built in geographic capabilities to quickly map out cities!
Showing you how to tell a story with your data! (through Tableau's story line feature)
Exploring Tableau Public profiles, embedding our awesome work into a website, and sharing our profile through links.
Giving you some valuable references for further learning & my contact information
Hi! My name is Erik. I currently work as an analyst at Google. I have a strong interest in data visualization and analysis, so the content I publish here will be more or less related to that.
Feel free to reach out via email with any questions, hope you find the courses useful!