We are living at a time when data has been dubbed ‘gold of the age’, with most of the largest businesses like Google, Facebook, Uber and others being in the data business. The tremendous growth in these organizations which are data driven has significantly inspired both small and large corporation to see the value of data. This is progressively inspiring the change in business perception towards use of data both operationally and strategically. Many organizations are now encouraging staff and executives on use of data to back their decisions. And large organizations with thousands of clients are launching analytical portals to keep their customers updated on different services from data point. However, to see the fruits of using data, you must win through communication first, your analytical products should be easy to read, interact and interpret.
Therefore, in this article I will explore eight ways which could highly impact your data story telling.
Note; This content has been generated in Tableau but is applicable in other business intelligence tools available in the market.
1. Choose your level of analysis
In many instances you will find data arranged in hierarchical manner depending by the nature of institution. For retail sector, this could be from product category to product sub-category to products. Or County to District to Location to Sub location for Country administration data. As a developer, it’s good to understand the level your persona will be interested and build your story just on that level. If your persona’s interest lies in the whole data, the best approach is to build your analysis at the course level (County for administration data) but still enabling users to drill down to lower level data (Sub-location data).
A good example is this dashboard on population and internet user’s statistics in Africa 2018. Users can view metrics at continent level as well as drill down to specific countries of choice.
Interact with the dashboard here.
2. Choose the right charts and graphs
With a good understanding of the level of analysis, it’s important to select charts or graphs which presents your data insights visually well. A good example to relate with, is when telling a story on distributions of data, a box plot and histogram will be the first charts to think of. But, be assured the two charts may not equally be suitable for your data at hand, that’s why its good to test the two and chose the most suitable chart. It is also advisable to test how your chart behaves when data is sliced to lower levels with fewer data points.
3. Avoid unnecessary marks
Space is critical in dashboard building process, and therefore anything that features in your dashboard MUST add value. A good example on instances where unnecessary marks get into your dashboard is displaying axis while at the same time having the charts labeled.
In such cases, the axis does not add value to your story as users can see the metrics themselves.
Minimizing much of these unnecessary marks will make your work neat and easy to read.
4. Be conservative with color
Color is good in our dashboard. It helps us have better memories; color can sway thinking, change action and cause reaction. However, use of color should be limited in dashboards; it’s advisable to use three to four colors in your dashboard (dashboard background included). In case you need to add more colors to your dashboard, you can play around with different gradients of the main color.
5. Add images and icons to enrich your story
At the heart of every developer, is the commitment to tell each data story right. While this may not be obvious to do, adding some images and icons related with the context of your story could help you enrich your story. A good example is in this dashboard, where the author uses icons of bird, mammal, reptile and plane to tell the story.
6. Avoid too much information
Have you ever found yourself with a well-designed information dashboard, only to realize you can’t use it to answer any business questions? If you have, you know how disappointing this is, both as a decision maker or as a developer for spending much invaluable time. To avoid these scenarios, it's good to stick to what your projects objective entails. Avoid adding too much information and charts in your dashboard which could distract users from the main objective. It’s good to note that any additional details consumes your resources (performance of your dashboard) - making your dashboard ineffective and inefficient.
7. Help users interact with your content
Have you ever visited a new suburb only to find yourself stuck not knowing how to navigate in the area, especially when you don’t have clear guideline? Could be a conference you attended, visiting clients or friends! Can you remember the experience? Probably you do. This is the same experience your users go through after visiting your well designed dashboard only to find themselves stuck with no information to guide them on how to interact with your dashboard. As a developer, it’s good to help your users by giving them guideline on how to consume your content.
8. Use of color legends and titles
It’s always good to ensure that your title resonates with your story. Also use of color legends should be looked at careful, especially in instances where different charts within the dashboard use different color legends. As a developer, it is important to evaluate the value of your color legend to the user, color legends which don’t necessary guide users interacting with the dashboard are not helpful and should be omitted. Using title color legend could help save space of your dashboard.
Related: How to use title color legends.
It’s good to note that, not everyone will be satisfied by what your dashboard offers, users will always have questions. That’s why, it’s good to help them know the contributor of your data (in case you’re using open source data/external data), author of the dashboard (in case they may need to reach you for more answers or for a customized dashboard) and of-course the source of the data and how to access it (if the license governing the data permits them).
A lot of factors may be the reason to your next great data story, but implementing the eight steps above in your next dashboard could make the smallest difference that counts.