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Data Literacy

This Data Literacy training course teaches attendees how to effectively navigate data to ask the right questions and define the right metrics with a focus on interpretation, context, and...

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Course Code DATA-100
Duration 2 days
Available Formats Classroom

This Data Literacy training course teaches attendees how to effectively navigate data to ask the right questions and define the right metrics with a focus on interpretation, context, and communication. Participants optionally work with their own data (or can work with data we provide) to make improvements and create more impactful data-driven narratives.

Skills Gained

  • Ask questions to get the right context for any analysis
  • Determine which metrics are important
  • Analyze and visualize metrics appropriately
  • Identify common pitfalls of data analysis and visualization
  • Apply best practices of data visualization and storytelling
  • Communicate insights in a clear, simple way that tells a story to drive action

Prerequisites

All students should have prior experience working with corporate reporting.

Course Details

Training Materials

All Data Literacy training attendees receive comprehensive courseware.

Software Requirements

Software Needed on Each Student PC
  • Microsoft Excel 2016 or later
  • Internet access
  • Related data and lab files that Accelebrate would provide

Outline

  • Introduction
  • What keeps the CEO up at night
  • Obtaining Context
    • Focus on the why
    • Challenging assumptions
    • Identifying key metrics
    • Tying back to measurable business impacts
  • Exploratory vs. Explanatory Analysis
    • Digging deeper in your data to find key insights
      • Finding meaning in the noise
      • Summary statistics vs disaggregated exploration
    • Identifying the appropriate audience and how best to communicate to them
      • Best practices of data visualization
      • Common pitfalls of analysis and visualization
  • Using the 5 Types of Analyses
  • Interpreting Charts in Context
  • Interpreting Summary Statistics
  • How to Make Your Work Present Itself When You Aren’t There to Explain It
  • How to Present Your Analysis to Different Types of Audiences
  • Conclusion