data stories at every stage of the analytical journey

Analytics today is diverse, with many different tools at hand that can process and investigate data. With so many options, it’s helpful to think critically about what type of analysis you actually need to pursue.

One way of categorising different types of analysis is via the “core pillars” model. While you can find anywhere from three to seven pillars listed, depending on the source, I prefer a solid four—descriptive, diagnostic, predictive, and prescriptive—with each one building on the pillars before it.

Descriptive analytics is all about what happened—understanding and summarising past events. Diagnostic analytics goes a step further and asks why something happened, hoping to glean insight into the underlying reasons behind patterns. Predictive analytics aims to determine what will happen by forecasting future trends. Finally, prescriptive analytics is concerned with what we should do about what happened, offering solutions for optimised outcomes.

Your task, your program, and your organisation could be at identical or completely different pillars from one another. The location, accessibility, and security of your data, the maturity of your business’s analytical capabilities, and stakeholder relationships with data providers can all influence the speed and extent of progression through the stages.

In most cases, an organisation’s goal is to reach that final pillar of predictive analytics, capable of delivering explanatory analysis to audiences with clear recommendations on what actions to take. Before reaching this final stage, however, there are opportunities within each of the preceding pillars to adapt and enhance visualisations, creating an engaging experience for the audience.

Curious to learn more about moving through the analytical stages? Join our upcoming premium event (Wednesday, July 19th @ 11am ET), where we will share practical tips to enhance your communications, wherever you are in your analytical journey.