The course introduces the characteristics of dashboards and the principles of data visualization. It also covers how to select KPIs, identify dashboard content requirements, design and implement dashboards and scorecards, and apply data visualization techniques. In addition, you will learn how to identify and select the software tools used to create dashboards and their visual content, as well as common mistakes, tips, and best practices relevant to dashboards and data visualization.
You will learn how to choose data sources, extract required data, perform data analysis using an example tool, and visually present the results on a dashboard using tables, charts and maps. As a course project, you will identify and specify dashboard requirements (including selecting the appropriate KPIs), design the dashboard views, reports, layout and navigation, as well as create the dashboard and the data visualizations to be incorporated in it. You will learn new visualization techniques like ‘word cloud’, ‘Sankey dashboards’,’Tooltip visualization’, and about the HYPER data format that enhances performance. In addition to these, you will also learn the newer features of the Tableau software. Your grade will be based on the project, in-class participation, a midterm and a final exam.
- Key performance indicators (KPIs)
- Understanding dashboards and scorecards
- Data visualization principles
- Advanced data visualization techniques
- Dashboard planning, design and implementation
- Best practices, common mistakes and tips
- Identifying and selecting dashboard tools and vendors
Course Note: The Tableau software is available to students for learning purposes only for approximately three months. Students are required to install software on own computers (Windows Vista or newer or Mac OSX 10.8.1 or newer) and are encouraged to bring laptops to class. Also note that this is not a specific tool usage training course. Tableau is introduced as an example tool for data visualization.
Skills Needed: Knowledge of database concepts and any business experience related to decision-making.