Data Analytics & Visualization

After this development track you will be able to

• Tailor the effort, type of illustration & purpose to the situation, related to available time, data & the audience of the message
• Make data presentable in MS programs
• Choose the right illustration type based on the available data and purpose
• Communicate key messages w. data for decision making
• Apply statistical measures & forecasting techniques to drive decision-making in projects

Learning objectives

• Understand the 4 key concepts of analytics
• Familiarize yourself with fundamental data analytics methods
• Apply statistical tools such as ABC analysis and R^2 & P values in real-world scenarios.
• Familiarize yourself with the process of creating heatmaps, ABC analysis and other visualization techniques.
• Evaluate the most suitable visualization type
• Evaluate which tool is suitable for making the illustration
• Identify & remove clutter and ambiguity in a visualization

The development track is especially designed for

• Project portfolio managers
• Consultants
• Data Analysts

Development track methods

• Workshops
• Group work with real life cases
• Plenum exercise walkthrough
• Individual studying

Development track material

• Analytics
  • CPC Application & Data Points Overview
  • Forecasting/Simulation Method & Example
  • ABC Analysis Method & Example
  • Heatmap Method & Example
• Visualization
  • Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic
  • The Visual Display of Quantitative Information by Edward R. Tufte
  • Best practices for Visualization
  • “Graph Type bank” for best CPC visualizations in Excel

Facilitators

• Bram Rosendahl Christiansen
• Magnus Gilsborg Jensen