5 MUST-DO Things to remember when you’re making Dashboards!

Dashboards are all around us today in the world of Data Science and it is no doubt that there’s essentially no data story that completes without the use of dashboards. Data Science enthusiasts today use various tools like Tableau, PowerBi, Looker, QlikView, etc. to make appealing and effective dashboards that communicate information easily.

The best part about a dashboard is also that it is easy to consume for any individual in the audience whilst having the added context that would be required for an in-depth understanding of the numbers/visuals being portrayed by the Data Scientist.

While it is easy to make a dashboard, there are a few pointers, that from my experience, make dashboard-ing way more fun and effective. Let us go over a list of 5 things you must do when making your own dashboard.

Feel free to skip to any section of the blog;

1. Keeping it to the point
2. Sensory concentration
3. Freedom of Choice
4. Context
5. Variety

Keeping it to the point

What usually happens with dashboards is that all of us have one day or the other, over-done it. Consider this, a company may want to show its profits in one dashboard and the source for the profits. The data for the entire company is massive and although there may be 100 elements that the company can show on the dashboard, it's best to stick to the 10 that make up the effective sources.

Think of it like the Pareto Analysis but for dashboards. Important to avoid an information overload. Follow the 80–20 rule and ensure you’re keeping it to the point and not giving your audience unnecessary baggage to carry when viewing a dashboard.

Sensory concentration

This can be a follow-up to the previous point, that after your dashboard is crisp and to the point, have a thorough check of where your senses or eyes (since that’s the only sense organ in use) going. Are your eyes being directed toward the one number that you know should stand out on your dashboard?

Are you having a sensory overload too with the correct information but no idea of what you should see first which leads to confusion?

That’s your cue to ensure that the colors you use in your dashboard are playing their part in taking the viewer around the dashboard in just the way you want them to go through it.

Size, colors, and contrast, it’s all keys to having the right sensory concentration.

Freedom of Choice

Ensure that your viewer, when they access the dashboard, have freedom of choice because they can choose to see specific elements on the dashboard clearly or apply any filter that you think will be useful in their understanding of the data point.

For a sales company, it can be anything from the territory where the sales are happening or just the different channels of acquiring customers, or the most basic filter but the most effective — time or dates.

Give your audience enough to play around and find out exactly what they’re looking for, even if it means going into a microscopic analysis of the data.

Context

Probably the most important aspect of dashboards that all of us tend to forget is context. You have given the audience enough tools to play around and find out exactly what they need, you may also have given them enough filters to filter the data to their precise need. But what if they have no idea, what are they looking for?

Or simply, what if you don’t know why you are looking at a certain KPI instead of something else?

This is a simple case to understand the fact that instead of giving your customer an information overload, just guiding them to the context of what you’re trying to tell them with particular KPIs or dimensions in your analysis, they can weave a better story that might correlate more to your lines of analysis too.

Variety

Variety in a dashboard relates to how the data is offered to be consumed by the viewer. You may read one number easily which may depict total sales, for example. You may also be able to show territory-wise segmentation in a bar chart, daily trends using a line chart, an area chart to show cumulative sales, etc.

There are many ways to show numbers beyond a table and I recommend that you try out as many ways as possible to see what works best for your dashboard.

Note: It is important to remember who is your audience. While a hypothesis test results would be something that researchers understand easily, it may not apply to the general audience who don’t understand complex information as such.

Additional Resources for you:

Conclusion:

Hope this article helped you make your dashboards at least 1% better. It is equally important to tell the data story effectively. It is always good to have your checklist to decide what works best for your audience when they see your dashboard. It may be easier for them to digest simpler graphs and not too complex visuals, with not too many colors.

P.S. There are many checklists available online if you ever find yourself in a pickle about remembering things. Here is an example;

Do check out my previous articles here, if they interest you!

The Simplest Guide to Data Storytelling — Elements & Examples!

For all my articles:

Data Science Simplified

Yash Gupta — Medium

~ P.S. All the views mentioned in the article are my sole opinions. I enjoy sharing my perspectives on Data Science. Do contact me on LinkedIn at — Yash Gupta — if you want to discuss all things related to data further!