Course Overview

Well told data stories are change drivers within the modern organisation. But how do we find the most important insights in our business data and communicate them in a compelling way? How do we connect the data that we have to the key underlying business issue?

This course takes students from the fundamentals (what should we be measuring and why?) through to the elements of good visualisation design (what does a good chart look like?) through to proficiency in data storytelling. By the end of the course, students will know how to produce engaging, cohesive and memorable data stories using Excel and PowerPoint. The course also teaches attendees the importance of producing statistically robust visualisations and insights.

Is this course made for you?

Candidates who will benefit most from the course include:

  • Graduate hires who are on track toward a career in analytics or data science
  • Executives and managers who want to create more engaging and impressive presentations with Excel and PowerPoint
  • Candidates already working in analyst positions, including (but not limited to) positions involved with data preparation, data analytics, digital and marketing analytics, customer and market analysis
  • Any other business professional who would like to tell better stories with data

Course Objectives

  • Provide participants with visualization best practices for the most common charts used in business
  • Provide participants with industry best practices for the production of insights
  • Provide participants with guidelines on best practices for linking charts together into a cohesive story that concludes with actionable recommendations
  • Provide participants with applied examples regarding trend analysis
  • Provide participants with a grounding in sampling, confounding variables and the statistical aspects behind data storytelling

Participants who complete this course will be able to:

  • Create complete data stories and know how to present these stories in an engaging way to upper management
  • Generate statistically robust data driven insights that inform decision making in the business setting
  • Detect, illustrate and highlight trends, outliers and patterns in business data
  • Build stakeholder support for project initiatives using data
  • Know how to select the appropriate chart types for a given dataset (e.g. When to use a bar chart versus a pie chart or a line graph versus a bubble chart)
  • Know how to design aesthetically pleasing data visualizations that adhere to the principals of good design
  • Understand how to use a ‘data dictionary’ and metadata to facilitate data analysis
  • Open .dat and .txt datasets in Excel.

Prerequisites

  • None.

Required Laptop Specs

  • Intel i3 processor, 2GB RAM
  • Either Mac or Windows operating system

Software Requirements

  • Any data visualization software package (e.g. Excel, Tableau, PowerBI, Qlik, R, Python) and PowerPoint