Data Visualization

Learning Outcomes

  • Know the 3 C’s of data analysis
  • Understand how to clean your data effectively
  • Gain foundational knowledge of Data Viz tools
  • Know how to build robust dashboards that fulfill business needs
  • Master the Data Visualization within Excel
  • Understand the role and application of pre-attentive attributes

Discourse

One of the most fundamental parts of data analysis is providing business intelligence. This can only come through effective presentation and visualization of the data. Through this visualization, we’re able to tell an effective data story, which helps to guide business decisions. In this course, we cover how to tell an impactful, truthful, data story. We go on to cover how to avoid some of the biggest data pitfalls, to ensure the conclusions you draw from your data are correct. We conduct this analysis using readily available tools such as PowerPoint and Excel as well as more complex tools such as Power BI and Tableau, to take your data visualization to the next level. We would also explore more advanced techniques in data analysis to enable interactive visualizations.

Program Overview

Data Analysis
  • Data and statistics: fact or fiction
  • Understanding the data analysis question – what do I want from my data?
  • The 3 C’s of data analysis: Color, Contrast, and Contour
  • How to clean data – garbage in = garbage out
Telling a story
  • How to tell a data story – Data UX (user experience)
  • Data visualization in practice – choosing the right visualization for the right type of data
  • Building dash boards in Excel
  • An overview of big data and the need for big data strategies
Advanced tools: Power BI or Tableau
  • Software tool introduction
  • Working with a variety of data sources
  • Building data relationships to tell a story
  • Understanding data analysis – regressions and decision surfaces and trees
Advanced tools: Power BI or Tableau
  • Data visualization in practice II – choosing the right visualization for the right type of data
  • Learning how to prep, clean, and shape data
  • Building intuitive dashboards
  • Presenting your data to ensure impact

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