--- title: How to Build a Dashboard That Tells A Data Story description: Learn a different approach to designing dashboards. Make dashboards more intuitive, impactful, and tell a better story. Incorporate user feedback early in the design process. image: https://blog.arcusdata.io/hubfs/dashboard-sketch.jpg --- - [206-247-6655 ](tel:+12062476655) - [hello@arcusdata.io ](mailto:hello@arcusdata.io) [![Arcus Data](https://blog.arcusdata.io/hs-fs/hubfs/arcus-header-logo1.png?width=400&height=90&name=arcus-header-logo1.png "Arcus Data")](https://arcusdata.io) - [Splunk](https://blog.arcusdata.io/topic/splunk) - [Arcus Data](https://blog.arcusdata.io/topic/arcus-data) - [Data Visualization](https://blog.arcusdata.io/topic/data-visualization) - [Dashboard Design](https://blog.arcusdata.io/topic/dashboard-design) - [Data Onboarding](https://blog.arcusdata.io/topic/data-onboarding) - [Uber](https://blog.arcusdata.io/topic/uber) ## [What Came First: The Dashboard or the Data?](https://blog.arcusdata.io/which-came-first-the-dashboard-or-the-data) [Joshua McQueen](https://blog.arcusdata.io/author/joshua-mcqueen) - February 2019 - [**](http://www.linkedin.com/shareArticle?mini=true&url=https://blog.arcusdata.io/which-came-first-the-dashboard-or-the-data) - [**](https://www.twitter.com/share?url=https%3A%2F%2Fblog.arcusdata.io%2Fwhich-came-first-the-dashboard-or-the-data) - [**](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fblog.arcusdata.io%2Fwhich-came-first-the-dashboard-or-the-data) ![brainstorm-graphic-1](https://blog.arcusdata.io/hs-fs/hubfs/brainstorm-graphic-1.jpg?width=1369&height=931&name=brainstorm-graphic-1.jpg) During the Holiday Season I was doing what a lot of professionals in my industry do. I was enjoying some well deserved time off, spending time with my family, and closing out one particular task that I despise more than anything: **submitting expense reports.** While slogging through *hundreds* of e-mail receipts, cancelled rides, and surge pricing statements I started to think, “man, I sure do take a *lot* of Uber rides”. Then a brilliant idea struck me! **I should make an Uber Splunk App.** What follows is a three-part series dedicated to showing you *how* the sausage is made. How to go from a tiny inkling of an idea to a full-fledged use case. Why you should leverage a powerful data visualization tool (like [Splunk](https://medium.com/r/?url=https%3A%2F%2Fwww.splunk.com)) for rapid prototyping. Instead of focusing on the technical [nuts-and-bolts](https://medium.com/r/?url=http%3A%2F%2Fdev.splunk.com%2Fview%2FSP-CAAAE8T) we’ll explore “big ideas” like design, approach, and how to incorporate user feedback. Follow these guidelines and your next Splunk App will be more *intuitive*, tell a more *impactful* story, and increase the value from your big data solution. --- ### Part One — What came first? The data or the dashboard? The most obvious (and completely wrong) place to start is the data. I often hear engineers thinking along the lines of “give me the data and I’ll build you a dashboard”. **This approach is fundamentally flawed.** In fact, years of this approach have led to incredibly poor designed dashboards, non-intuitive interfaces, and mass frustration from end users. It’s no wonder that dashboards have evolved to look *more* and *more* like the data underneath. Instead, I argue the best approach is the start with the end in mind. ##### What questions are you trying to answer? Who is the audience? What story are you trying to tell? **Back to the Uber example.** I knew I’d taken a lot of rides, but *what* *exactly *did I want to know? I sat down and brainstormed a long list of burning questions: - How much money did I spend on Uber this year? - How many miles did I ride in an Uber? - What city do I use Uber the most? - What was my most expensive ride? - What time of day is most popular? Month? - Am I using their ride share service more, or less? - What’s the breakdown of Uber X vs XL vs Pool? - *…. and the list went on for over 30 questions…* ### **Step 1 — Mockup a Dashboard** ### ![dashboard-sketch](https://blog.arcusdata.io/hs-fs/hubfs/dashboard-sketch.jpg?width=1000&name=dashboard-sketch.jpg)  I’m a visual learner. If you’re anything like me your notebooks are *filled* with sketches, designs, and scribbled down notes. During the creative process I like to visualize and document the following: - Who is the audience that will be using my dashboard? Skill level? - What pieces of information are most useful? (Display at top) - What device will be used? (Laptop? TV Display? Smartphone? Tablet?) ### Step 2- Getting The Data In Now that we have well defined requirements in place, it’s time to work backwards to solve for X. I spent time digging into the problem and came up with three viable options: 1. Mine / parse the e-mail receipts in my inbox 2. Use the API key to collect the data 3. **Request a data download from Uber directly** The first option would have taken time to instrument but could be automated. The second method (API) is easy to implement but the information returned is *very* limited. As it turns out, [Internet Privacy Laws](https://medium.com/r/?url=https%3A%2F%2Fen.wikipedia.org%2Fwiki%2FInformation_privacy_law) force companies like Uber to hand over all personal data upon request. We have our winner!  ![json](https://blog.arcusdata.io/hs-fs/hubfs/json.jpg?width=1110&name=json.jpg) Now that we have our questions written down, dashboard sketched up, and data available for analysis — it’s time to actually build the damn thing! --- In the next blog post I’ll explore the ins-and-outs of building interactive dashboards, the pros and cons of data visualizations, and how to make your dashboard really stand out! Thoughts? Feedback? Please comment below and let’s start a dialog. Thanks for reading.  --- Want more insight like this? Make sure to follow us on [LinkedIn](https://www.linkedin.com/company/18560042/), [Twitter](https://twitter.com/arcusdata) and [Facebook](https://www.facebook.com/ArcusData/)! 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