This course prepares data analytics professionals to communicate analytics results to business audiences, in a business context while being mindful of the skills, incentives, priorities and psychology of the audience. It also equips analysts with an array of tools, skills, behaviours and insights into analytics audiences to achieve this aim. Data visualisation and communication skills are vital for today’s data analytics professional.
Data visualisation is a vital component of data analytics, as is the communication of its results to management. The use of advanced data visualisation tools for insights generation is a key and common skill of data scientists and other advanced data analytics professionals. What is often lacking in this skill set is a completely different use of visualisation: the communication of analytics results to other people, whose quantitative analysis and interpretation skills are typically not at the same level of data scientists.
These are the “dos” of the course, but the course also presents a range of “don’ts”, including advanced data visualisation methods that are terrific for actual analysis, but poor for communicating it to others.
The core of the course is concerned with methods to succinctly and impactfully share analytics insights with a business audience, primarily through visual means. It covers the use of various data visualisation methods, as well as presentation, layout, putting results in a business context, and telling the difference between key insights and detail.
The course touches on more complex issues in data visualisation, such as dashboards and interactivity, as well as the analysis and presentation of multivariate data. Throughout this section there is a continued focus on what is interesting? and what is impactful? from a business perspective.
The course also provides some examples and case studies.
Finally, the course provides an insight into “dark arts” of data analytics visualisation. This includes deceptive use of visualisation, the various incentives that audiences may have, including using data to make a case, or using data to entertain, or to leave an audience feeling they have learned something when in fact they may have not.
- The two disciplines
- Discipline 1 : Deriving insight visually – a very brief description – because this isn’t what the course is about
- Discipline 2: Communicating insight visually – what the course is about
- Visualisation and visual analysis methods for communication
- Visual analysis tools not for communication
- Visual analysis tools – grey area
- Multidimensional data
- Dos and dont’s
- Visual storytelling
- Communication methods
- Discipline 3: “The dark arts”
- Visualisation to deceive
- Communication vs persuasion
- Making a case
- Understanding vs feeling that one understands
- Fancy visualisation tools
Course content may vary from this outline, and will be driven by class learning needs. This course may also be offered under other names.