Building great dashboards

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The purpose of any dashboard is to tell a story. Thus, all basic principals of story telling applies to building a great dashboard. This mainly includes – knowing your audience, preparing a story and finally, presenting a story through visual design. Let us focus on each one briefly.

Know your audience[edit]

This is the first and most important part of great dashboard building. You must know the type of audience, their intent and finally, the context under which they will consume your dashboard. Your audience might be focused on strategic areas or interested in operational aspects . Dashboard should address these needs differently. VP of Sales might be interested in sales trend in certain territory or products, whereas Customer Service org leader might be interested in agent productivity. Similarly, an airline executive may look for state and position of aircrafts at any given time vs. trend in utilization of aircrafts in past few quarters.

In addition to insights, your audience might be looking for suggestion for actions to achieve / correct business outcomes. Dashboards must understand and cater to such diverse intentions.

Lastly, difference audiences operate under different context. Your dashboards might be consumed in variety of environments – ranging from a large screen in executive board room to a factory floor. It might even cater to mobile audience on a small screen of cell phone or tablet. Most importantly, one must understand consumption patterns – whether is it presented in meetings, send it over email or glanced during transit. Such synchronous or asynchronous consumption may lead to various interpretations by your audiences.

Prepare a story[edit]

Once you know your audience, their intent/needs and context under which they will consume dashboard, next step is to prepare for a story. There is no one “right way” to prepare for your dashboard stories. The trick lies in staying atomic in scope. Less is more when it comes to conveying a crisp message. You should stick to the purpose of the dashboard and keep it relevant.

Most of the dashboard generate questions like “so what” or “why” in your audience’s mind. You must be able to anticipate and address such questions in your dashboards. This is where data becomes insights. Lastly, your dashboard should smoothly and appropriately present exceptions, trends and recency effects.

Focus on a visual design[edit]

Visual representation of your story is equally (if not more) important as your story. One must consider these dimensions during visual design of your dashboard. First - ensure relevancy. Currency, decimals, text are presented appropriately per context. Second – validate accessibility. This is very important if you have varied audience consuming dashboard under different context. Size and placement of widgets, color combinations, scrolling should ensure consistency and readability. Third – emphasis on aesthetics. Selection of your widgets and color pattern should attract attention of audience and not distract them from the main story.

Type of visualization you chose impacts all three aspects of visual design. Bar charts are used to give absolute impression of quantity dimension, vs line charts implicitly depict trends over prior data points. Bubble charts gives you deeper control by letting you choose position, size and color of bubble. Maps makes clear sense as backdrop when you want to plot data against spatial / geographic dimensions.

Technical design considerations[edit]

So far, we have talked about story telling thru dashboards. Correct technical implementation ensures smooth functioning of your dashboard. Product owners and engineers (mainly DB designers) are accountable for simple and cleaner design.

While there are a lot of factors for technical design (commonly referred as -ilities in architecture pattern), key aspects to watch out for are captured below:

Performance: No one likes to wait for systems to stall or slow down during interactions. Interactive dashboards must respond to every click in less than 3 seconds in various environments (data volume, network considerations etc.). Appropriate schema design (e.g. star schema) and denormalized data structure will help reduce query load and improve performance.

Agility: Very rarely, dashboard once designed, will meet all business needs. New demands to see data in various ways will raise curiosity in your audience. This necessitates need for agility in maintaining your dashboard. You should be able to add or alter new visualizations with minimum engineering or deployment effort. Your dashboard should truly be no code solution.

Data Latency: Your transactional data schema will likely to be different than reporting data schema (or DataMart schema). Data transformations are inevitable while copying transactional data to reporting schema. This puts burden of data refresh timings and creates data latency. While this might not be a concern in strategic dashboards, but it certainly is a showstopper in operational dashboards. Incremental event driven refreshes, with optimized data schema may help resolve this to certain extent. One can choose either ETL (Extract-Transform-Load) or ELT (Extract-Load-Transform) to get data from transactional to mart. ELT is a modern alternative as storage and compute resources are being separated .

Integrated experience: Finally, dashboard’s integrated visual experience is very important in larger enterprises environment. Your dashboards should be developed as loosely coupled components and can be seamlessly embedded into any enterprise systems.


There are a lot of data visualization tools available in market today. You should ensure you opt in for ones that support no code dashboard creation and maintenance and offers connectivity with varied data sources. Microsoft Power BI and Tableau are prominent ones that offers SaaS offerings as well.

Additional References[edit]