From customer observation, a team of typically 5 or fewer developers and 1 manager, have multiple data jobs in development and production. After design and deployment of data jobs, the team is also responsible for monitoring the data flow on a day-to-day basis.
The overview dashboard gives the data integration team a quick overview, or what I have termed the “Monday morning check” of data integration jobs.
I spoke with several dozens of customers prior to the design of this application, but the validation never stops and the best reaction after the product launch was this:
What are the “right kinds of metrics”?
Rows Processed and Number of Jobs are the two key metrics. Shown here are miniature visualizations of the data to be used on the overview dashboard. Hovering over the columns provide additional information. The Number of Jobs chart display an additional dimension of data by breaking down the count by ‘job status’, so a stacked column chart is the most appropriate visualization to show the states Success, Warning, and Failed.
Each of the key metrics can be correlated with a supporting metrics such as projects or tags. So the visualization is rows processed by Projects, Folders, and Tags. Using line charts lets user visualize and compare the data over time.
While interviewing and observing customers, I observed a variety of solutions that developers have pieced together to support their routine workflows.
This customer observation generated numerous ideas for data visualization and data reporting features, and also inspired new product strategies such as an Informatica Slack app for monitoring.
Utilizing Slack gives teams an impactful way to view Informatica operations data in a collaborative environment that they use daily anyway.
Big Numbers, 1st Glance
A key insight I discovered from observing users is that they want the first glance to contain large actionable numbers, or “fast facts”, rather than common visualizations such as pie charts and donut charts.
Analysis Views, 2nd Glance
Visualizations are the second glance for a more detailed analysis of the data.