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Are Your Dashboards Intuitive?

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Are Your Dashboards Intuitive?

Your dashboard may be flashy and good-looking, but that's not the sole purpose of dashboards. Learn how to make dashboards that both look good and provide great insights.

· Big Data Zone ·
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We start with a basic question: "Are our dashboards intuitive?" Let's think about it for a while. Most of the time, our dashboards are flashy and good-looking. However, that's not the purpose of dashboards. Dashboards should provide us with as much information as needed to perform our job well. A few decades back, when we didn't have these BI tools, spreadsheets were widely used and provided more than enough detail for capturing right information. Even now, spreadsheets are a preferred tool for personal use — making pivots and graphs and filtering data is damn simple and provides uncomplicated visualizations. Some organizations still use spreadsheets for their dashboards. However, with the data eruption, many new dimensions have been added — and we have to capture them all for better business visibility.

The emergence of big data made the field of dashboard design and data visualization even more complex and challenging. It is becoming increasingly difficult to infer the right information, and we need a better way to glean knowledge from our data. Even with so many people making so many dashboards, most of the time, these dashboards are just a data dumping ground serving as nothing more than a mix of sketches, charts, and figures. So, it's important to prepare a dashboard that gets the most of the information out of the data. It might not be showy, but it will be a simplistic and intuitive way to discover insights. With all the varied data that can solve different analytical needs and questions, we want to take all this complexity and make it simple.

Here are few important points for creating better dashboards. While they aren't extensive, they can assist you in designing your dashboards.

  1. Prepare a scope of work document listing the problem statements, stakeholders, scope areas, expected results, and references to other related existing dashboards, if any. 

  2. There are various ways to create different charts for a dataset. However, not all may be ideal for the target audience. Therefore, choose the right charts to meet the end user's needs.

  3. Most of the time, we try to make dashboards look flashy. This is not necessary. It's better to keep the dashboard simple with consistent, simple colors and a legend explaining its purpose.

  4. Provide parameters to filter the content so that users can play around with the data. Choose the fields as parameters that are frequently used for slicing data.

  5. Have consistent format for the areas within the same data type so that users don't get confused. Truncate the numeric fields to one or two decimal places.

  6. Tell a clear story by arranging the pieces of a dashboard in a layout as per the business context.

  7. It's better to start with a dashboard summary and then drill down to the granular details as needed.

  8. Implement at least basic level of interactions between different dashboard panels so that users can play around with the dashboard and get a clear picture of the information they want. Construct an interactive experience that blows away the legacy methods that enterprises have relied on for too long to communicate their data.

  9. Avoid 3D charts as much as possible. It's hard to get insights out of them, as appealing as they are.

  10. Avoid using bright colors for charts; use them only to highlight relevant information.

These are only some of the ways to impress dashboard users, answer their questions, and give a clear picture of the insights they need. Below are some of the articles that can also support you in preparing better dashboards:

Happy dashboarding!

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Topics:
big data analytics ,dashboards ,data visualization ,big data

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