MICROSOFT AZURE Enterprise DATA Directory
Sr. Lead UX, Interaction, Visual & 3D Designer
While working on both Microsoft’s Azure Data Catalog and Azure Data Factory we were tasked by leadership to work on future concepts around what a enterprises data landscape could look like from a broader picture. I teamed up with another designer and design researcher to explore concepts that could enrich a experience for the enterprise Data Architect.
Our initial approach was to develop design concepts and conduct a series of user research sessions to gain insights quickly so that we could iterate our designs based on user feedback.
We began by exploring key scenarios for the Data Architect and settled on the following:
We focused our efforts on setting up a series of user research sessions that we would use to engage with our target persona. We would use each session to present several design options to our participants and gather as much feedback as possible. Feedback would be used to further iterate our designs.
Our concepts targeted key areas for a Data Architect to explore their data landscape:
- Industrial Park - a view that allowed the user to see at a glance what was happening in their organization
- KPI’s - we explored what key metrics our user was most interested in drilling into
- Dashboard - a global view of KPI’s that would give users quick insights into their organization
- Pulse - a social component to a organization's data environment, allowing other users in a organization to engage with one another
Our team collaborated a great deal and I took the lead on designing concepts around the "Industrial Park" & "KPI's" sections.
The "Industrial Park" concept would allow a Data Architect to quickly visualize where their data was in the organization at a very high level . Concepts would focus in the following areas:
- Data relationships and flows between internal organizations
- How data changed over time
- Key metrics and the ability to drill in to particular areas to gain more insights
KPI's & Dashboard
We were very interested in understanding which KPI's resonated with our users. We conducted several exercises to better understand which KPI's mattered most and why. Below we asked our participants to rank a series of insights that they were most interested in. If they didn't see a metric they were asked to use the blank box to fill in.
After collecting stacked ranked KPI's from our participants during the first week we looked at which KPI's resonated most.
I mocked up actual visual KPI's to use in our second weeks exercise. Users were asked to evaluate KPI's and construct their ideal KPI dashboard. Again we asked users to notate any KPI's that were not available.
During the third week we presented users with design concepts that would have the consolidated and ranked KPI's. We concluded that users were split on having two distinct metric categories - Business and Operational.
Leadership was very happy with the results of our deep dive around these concepts. Many aspects and findings found their way into the work I would later do with both Azure Data Catalog & Azure Data Factory. We also filed and received three patents for the work we did during this project.