Interesting data visualization is fundamental for making your reports as simple to comprehend as expected. Here we will share the seven most important things to consider and implement when designing an efficient data dashboard to improvise the presentation of your data.

Tips For Designing An Efficient Data Dashboard

1. Plan Interestingly

Before you add charts to a particular report, make sure that you have an obvious idea of its contents and layout. We recommend writing all the queries or questions you want to ask about your data. It should be your first task.

Make a list of all your queries for more ease. The list should contain:

  • the name of the query
  • the data source comes from
  • the fields in that data source
  • the visualisation type

Once you’ve made your list, then take a blank sheet of paper and a pencil and sketch out a rough drawing of how you would like your report to look. Nothing detailed, just a very rough sketch. It will truly be a great help.

2. Become A Storyteller

Always keep in mind, your viewers will read your report, most likely from top left to bottom right, like a page of a book. That is only how our brains are set up. So ensure there is some intelligibility to the report as far as which queries you’re showing where.

Consider gathering questions that contain information identifying with a similar region, action, or KPI. Most of the reports follow this pattern where each page is dedicated to a specific area. So this is the meaning of being a storyteller, i.e., try to correlate every point of your report just like a story.

3. Avoid Exaggeration Of Information

You can closely relate this tip to the first two, like Avoid TMI (“Too Much Information”). Please do not overload your report with charts and information, making it difficult to read and understand. Usually, in these cases, you either end up reducing the size of other charts, making them less easy to read.

Or then again, you move outlines around on the page to oblige more diagrams, which can mess with the story you’re attempting to tell. Maybe than over-burdening your viewers with information, you could even do the inverse, be more moderate.

Use however many pages as you need to ensure that the viewer can read your data appropriately. Keep in mind; the thought is to make your representations as simple to read and comprehend as possible.

4. Ink To Data Ratio

It is an idea presented by Edward Tufte, a data visualization master, in his 1983 book, The Visual Display of Quantitative Data. He says, “A large share of ink on a graphic should present data information, the ink changing as the data changes…..”

So essentially, he wanted to explain that most of the ink needed to display a visualization should be data-ink. For instance, the bars on a bar diagram or the line on a time series chart. Any place conceivable you should eliminate anything unimportant to the visualization.

It implies things like the grid on a chart, axis, and so forth. If the visualization data can be read and perceived without it, eliminate it. A good example would be in a time series chart. The values on the x-axis are dates and clear to the viewer. So you don’t have to have an x-pivot title mark that says “Date” since it’s repetitive.

 

5. Choose The Correct Visualisation

It’s important to make sure you choose the correct visualization tool and technique for the query you’re creating. Here are some questions to ask:

  • Are you comparing values? Then perhaps a column or bar chart would be the best.
  • Are you trying to visualize relationships or hierarchies? Then maybe a treemap.
  • Are you showing percentages of a total? A pie chart would probably be the best.
  • Are you working on dates? Then a time series or area chart is the way to go.

These questions will assist you with choosing which visualization type best suits what you’re attempting to pass on. The aim is to make your information as simple to understand for the viewer as expected, and visualization type assumes a major part in accomplishing this.

6. Color Selection Matters A Lot

I mean by this is don’t go wild and begin picking an alternate tone for every visualization. Keep your use of color simple and decent. Don’t use extremely dull or extremely bright colors.

You could use different colors to represent different areas in your report, so everything relating to sales in one color, marketing another, etc. However, just when it’s a good idea to do so. You see that the best-planned reports and dashboards keep the color plan simple.

7. Design for the Viewers

It relates to not only who is going to view your report but also how it’s going to be viewed. On this first question, who will have to bore down into the information or channel it? If they are, you’ll need to include these options when building your visualizations.

How recognizable are your dashboard viewers with the information that is being introduced? It will decide how many portrayals or unimportant data you have in visualization to clarify what is being introduced. How the report will be seen and devoured will affect things like the orientation and size of your dashboard.

Will you share it as a pdf that will be printed? Assuming this is the case, you’ll need to ensure that it prints appropriately. You would also, for this situation, maybe need to add more data like showing certain qualities in diagrams since you can’t drift over a graph with your mouse.

Conclusion

You can see that there are many things to consider for your audience. Now you have Thinklytics top 7 tips for designing an efficient data dashboard to help take your reporting to the next level.

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