Ask any data team and they’ll tell you: maintaining analytics is a nightmare (especially at scale).

Teams create dashboards for one off uses and then never delete them. At Ollie, that meant alternate versions of existing dashboards, one-off charts, and copies of copies of copies.

That mess was partly a side effect of something good: that everyone at Ollie had access to Lightdash. People could explore governed data whenever they needed to and could build whatever they wanted. But the data team had to deal with all the leftovers. 

Cleaning it up meant manually reviewing content, tracking down owners, and deciding whether each chart was useful - which is why it rarely happened. 

Autopilot turned dashboard cleanup into a scheduled process

Earlier this year, we launched a new feature: Autopilot. 

Lightdash Autopilot is a scheduled AI agent that automatically cleans and maintains a Lightdash project on your behalf. It finds stale or broken content, fixes what it safely can, and flags the rest for your data team to review. Anything it removes is soft-deleted, so admins can restore it, and every action appears in an activity log with the reason it was taken.

Ollie configured Autopilot around a 90-day stale-content rule, meaning Autopilot could delete or modify anything that hadn’t been viewed or touched by a member of the team in 90 days.

The ability to easily recover content also made it easy for the data team to trust Autopilot. Now, the team could use the agent to do the cleanup instead of creating a queue of dashboards for someone to review.

In just one run, Autopilot surfaced about 43 stale charts. And after several weeks of scheduled cleanup, nobody at Ollie had complained that anything important was missing.

“Before Autopilot, dashboard cleanup was a manual job that rarely happened. Now it runs in the background. We can restore anything it removes, and after months of scheduled cleanup, nobody has complained that anything important is missing.”
- Ben Pannell, Data Engineering @ Ollie

For Ollie, using Autopilot meant that the data team no longer has to spend time manually cleaning up their projects. The clean up process now ran on a schedule, and the data team no longer had to spend time deciding whether to delete one dashboard at a time.

Lightdash replaced a Looker setup Ollie couldn't build on

Ollie became a Lightdash customer more than two years ago, when the team was refactoring its data lineage. At that time, the team were on Looker, but the tool’s development felt deprioritized and overlapping Explores and duplicate metric definitions had made its LookML difficult to untangle.

“It was clear that we weren't able to iterate as quickly as we wanted, and the self-service was confusing.” 
- Ben Pannell, Data Engineering @ Ollie. 

When the team came across Lightdash, it was a clean fit for their data stack. Instead of maintaining a separate LookML layer, the team could keep metric logic with its dbt work and use one governed semantic layer for charts, dashboards, and exploration.

The Lightdash team helped translate Ollie's existing LookML into starter YAML, getting around 80% of the initial migration in place before the deeper cleanup work. Ben described it as “a much easier lift for a lean team.”

“Having an opportunity to create a semantic layer and have one definition for a metric was a game changer.” 
- Ben Pannell, Data Engineering @ Ollie. 

One governed metric layer now serves the whole company

Today, the whole team at Ollie can access Lightdash. Business users can explore governed data and share their findings without needing to understand the SQL underneath, while analysts keep edit access to core dashboards and can inspect the generated SQL when they need to go deeper.

For the data team at Ollie, the strongest proof is what they don't hear.

“Almost everyone at Ollie has access to Lightdash, and we hear almost no complaints. That's the best sign it's working: people can explore trusted data without bringing every question back to the data team.”
- Glenn Schechter, Senior Director of Data & Analytics @ Ollie

Ollie's next step is to let more people ask questions conversationally, without removing the guardrails that keep its most important analytics correct. Autopilot gives the data team a way to keep the project clean as access expands.

When we started building Autopilot, we asked ourselves: why should a lean data team spend its time cleaning up stale dashboards by hand? Now, they don’t have to. 

Interested in automating your dashboard cleanup? Get in touch with our team today to try Autopilot for free.