One thing that’s really struck me at the data school these past few days is the importance of asking the right questions right from the start before starting analysis and visualization. Let’s break it down into four key questions: Why? What? Who? When?
Why: It all begins with understanding the purpose behind our dashboards. What questions are we trying to answer, and what actionable insights are we aiming for? Also, should the dashboard be exploratory or explanatory? Exploratory meaning should we allow users to explore data themselves? Or explanatory when we are just telling them the insights so that they don’t have to search.
What: This is about understanding the specific needs of our audience. What do they really want to see? Is it a single dashboard, multiple dashboards, or a whole workflow? This helps us tailor our visualizations to meet their exact requirements.
Who: Knowing who will be using our visualizations is crucial. Sometimes, the stakeholders might be different from the end-users. Understanding their roles, whether they’re executives or analysts, helps us customize the level of detail accordingly.
⏰ When: Finally, timing is everything. When do our stakeholders need the data? When should the dashboard be updated? Are the dashboards monitoring weekly, monthly, quarterly, etc.? Do they data need to be in real-time? Answering these questions ensures our visualizations are always timely and relevant.
Preparing for Data Visualization: What Should You Do Before Getting Started?
This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.
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