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© All rights reserved 2018, Southern Data Science, LLC

Data Analytics with Tableau

Time and Location

Apr 18, 2020 at 9:00am - 3:00pm EDT

Cobb Galleria Center

Details and Agenda

Workshop Requirements

 

  • Have Tableau downloaded prior to class (Tableau offers 2-week free trial – make sure not to download outside of two-week window) https://www.tableau.com/products/desktop

  • Be able to download course material (data extracts, .csv and .xlsx files) from an external site

  • No prior knowledge of Tableau is necessary, but this workshop will move quicker than a traditional training. The ability to pick things up conceptually is very beneficial.

  • An external mouse makes things a lot easier, but not a requirement.

 

Who Should Attend?

 

  • People interested in learning best-practices around data visualization

  • People wanting a high-level overview of Tableau

  • People curious about Tableau’s analytical capabilities such as clustering, forecasting, and R/Python integrations

  • People who are more focused on business intelligence as opposed to the technical operations

Who Should NOT Attend?

 

  • Tableau Zen masters looking to dive into the advanced realms of Tableau’s data-padded, triple nested LOD calculated, custom geo-coded capabilities. 

 

 

Who Is Your Speaker?

 

Nian Yan, Data Scientist, Core Recommendations at Home Depot Online

Received a Ph.D. degree in Information Technology with a concentration in machine learning from the University of Nebraska Omaha, Nian has a decade of successful experience working as an R&D practitioner using advanced analytics to solve business problems. Prior to his current role, he served as a data scientist leading the research and product development in Identify Fraud Solutions at Equifax. Nian has more than 10 years of experience using Tableau as a communication tool to the business as the showcase of machine learning and analytical solutions. Nian also loves photography and he develops films by himself.

 

1. Tableau introduction

 

  • Development environment

  • Data connections

  • Dimensions, Measures, and Shelves

  • Groups and hierarchies

 

2. Basic Exploratory Analysis

  • Charts

  • Marks

  • Page

  • Filter

  • Calculated Measures

  • Table Calculations

  • Parameters

       

3. Advanced

  • Data Blending

  • Time Series

    • Trends and forecasts

    • Percent change, moving averages

Maps 

  • Plot Maps

  • Data Layers

  • Use Cases


4. Dashboards

  • Actions/Passing Parameters

  • Navigation

  • Storyboarding

  • Best practices