Why doesn’t Tableau know who I am?

“Why doesn’t Tableau know who I am and remember what views of the data I like to look at?” asked Patricia, a frustrated Head of People and Performance.

Patricia’s essential ask came next, and it is a good one:

“I only want to see scorecard metrics for my department. But every time I log into the Exec Scorecard dashboard, I have to apply the same 7 filters. It's really annoying! And the dashboard doesn’t jump to the most recent month or week of data — I have to tell the dashboard that every time. Surely, we can have some smarter software?”

What a terrific and profound user query. Spotify, Netflix, Amazon, etc etc go to great lengths to know who we are, what we are interested in, and better yet, sense what we might be interested in. They create intensely personalized experiences for each of their users. But in our world of analytics, and we might even complain more broadly about enterprise software in general, even the best data visualization and reporting software are still running traditional user experiences which can be described as: lots of folders, lots of reports.

So, our first challenge was to figure out how we can tell, in this case, Tableau, what date filters each report should snap to on a given day. In our case, our data warehouse creates monthly and weekly snapshots of the data, so how could we program the dashboard to snap to the date filters we want. Bring in the Tableau API.

By creating a web wrapper around dashboards and other analytic content, we can programmatically call dashboards from the Tableau Server and embed them into our new, and quickly growing analytics portal. Once our web layer was established, we explored the capability of the Tableau API and began writing new blocks of code to make the user experience more personalized and smarter.

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Why we created dablr.

Our final result was a demonstration to Patricia’s executive team with a new look Executive Scorecard dashboard that intelligently:

1. Automatically filtered the data on a rolling, 2-year basis

2. Defaults to the most recent weekly data refresh

3. By changing from a weekly perspective to a monthly view, the dashboard automatically snaps to the most recent month of data in the data warehouse

4. Each Executive can now view only their metrics, or create a custom view of the metrics they keep an eye on

More importantly, both the customer and us were onto something.

What else could we do programmatically to make the user experience easier, more relevant, create better access, and ultimately deliver more useful results for our users?

While Tableau and the like are great for data analysts that can rapidly move about a range of tools, what are we doing for our regular business users? How might we connect them to the metrics, interactive analysis dash-tools, and colleagues that can help them identify useful performance trends, anomalies and share insights with their teammates?

Our vision for dablr began with this amazing user question: Why doesn’t Tableau know who I am and what I should be looking at? While our day — to-day work at our company is no different to Business Intelligence teams globally and focuses on the data platform essentials:

· Operating data pipelines

· Governing our data

· Securing our data

· Working with our business users to profile and prepare new data sets

· Coordinating small teams to author insights

To what end is all this great work that provides terabytes of good data? How can we better engage our business users to interact with all the great work our BI teams are doing?

We now have this amazing capability that enables us to surface insights, recommendations, alerts, new content, news and so much more in a rich, personalized web experience that delights our users, and engages them. We can do this at scale, and across multiple BI systems, docs (think spreadsheets, slide decks), and communication methods. The end result is that we are connecting people and processes specific to data & analytics and creating more effective, data-driven teams. We are helping form a community of knowledge workers within our customers, and this is what enables a culture of data driven decision making.