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6 min read

90-Day BI Migration Playbook: Moving 800 Dashboards Without Breaking the Business

Game Lounge’s 90-day migration from Looker to Omni transformed 800+ dashboards into a lean, future-proof BI ecosystem. With careful auditing, phased rollout, and intensive training, the team rebuilt its entire analytics stack—cutting clutter by 85% while keeping the business running smoothly.

At Game Lounge, data isn’t a nice-to-have. It is something that is embedded in our daily decision-making, from performance marketing to product development. But like many companies with years of BI usage behind them, our setup had become bloated: hundreds of dashboards, inconsistent governance, and overlapping metrics across departments.

In 2024, we decided to migrate from Looker to Omni. What followed was a 90-day, full-scale migration involving 800+ dashboards, new user training, AI feature integration, and a full semantic layer redesign. And we did it all without disrupting day-to-day business operations.

Why Migrate Your BI Platform at All?

We didn’t take the decision lightly. Looker had been our primary BI tool for years. But three key reasons drove us to move:

For a more detailed understanding of why we decided to migrate BI tools, kindly refer to the blog post that we published earlier this year.

Preparing To Migrate: Managing Legacy BI Sprawl

Our biggest challenge wasn’t technical; it was historical.

Over the years, dashboards had been created ad hoc by different teams. Many were outdated, duplicated, or simply abandoned. Ownership was often unclear. Some dashboards served similar purposes but with different definitions, making trust in certain metrics inconsistent.

We knew that migrating everything 1:1 would only replicate the problem in a shiny new tool. So we decided to migrate with intention.

Starting With an Audit: What’s Worth Keeping?

The first step was a full audit. We wanted to know:

  • What dashboards were actively used?
  • Which ones had business value but were poorly designed?
  • What could be safely archived?

To answer this, we sent out a mandatory Google Form to every department, asking them to flag what they still used and why. We paired this bottom-up feedback with a top-down strategy that prioritised dashboards for executives, product leads, and key internal metrics.

Based on the feedback that was received, we then categorised dashboards into:

  • Must Migrate
  • Skip / Archive
  • Redesign with Improvements

Backups Before Breaking Ground

Before touching anything, we created a full backup of our Looker instance. This included dashboards, models, and saved queries, as well as PDF version exports. The PDF exports were crucial given we were on a tight deadline, as they would have provided enough context to understand the dashboards’ appearance, numbers, filters, and underlying metadata, even if Looker had been switched off. While we never needed to restore from it, this gave us the confidence to move fast without the fear of losing anything permanently.

Phased Migration: Prioritising Business Continuity

The migration took place across six phases from September to December 2024:

  1. Preparation & Audit
  2. Omni Setup & Permissions
  3. Phase 1: Core Dashboards
    • Company metadata, performance, Google Analytics, and other high-importance datasets
  4. Phase 2: Secondary Dashboards
    • Jira datasets, HR data, and other datasets that won’t break the business if not migrated by the deadline
  5. Training & Stakeholder Demos
  6. Final Cleanup & Sunset Plan

During migration, Looker remained fully operational. We only phased it out after complete validation and approval from stakeholders.

Designing for the Future 

Reducing clutter: From 800 to 100 dashboards 

By the end of the migration, we had reduced over 800 dashboards to just under 100. This wasn’t about cutting access, it was about surfacing what truly mattered, cleaning up the semantic layer, and rebuilding with intent. We did this by:

  • Archiving outdated or duplicated dashboards
  • Redesigning key dashboards from scratch for better UX and governance
  • Rebuilding filters, KPIs, and visual styles to ensure consistency across teams

This massive cleanup not only improved performance but also helped users regain confidence in the platform.

Building a stronger foundation

We treated the migration as more than just a tool switch. We also:

  • Rebuilt user roles and data access permissions based on actual needs that we uncovered from the user survey and how our organisation is structured
  • Created a dashboard verification system to flag trusted, business-wide content
  • Added usage analytics from Omni’s in-app analytics to allow for ongoing monitoring of what dashboards  and features were adopted (or ignored)
  • Established naming conventions in Omni’s semantic layer and governance guides to keep things clean going forward

Training, AI Features, and Adoption

Change is only successful if people embrace it. We ran dedicated onboarding sessions for all business units, supported by Omni’s team. These included:

  • Hands-on workshops
  • Team-based onboarding guides
  • Quick reference materials for filters, topics (curated datasets in Omni), and terminology
  • Video training track material that was provided by our partners at HawkFry, offering guidance on how to maximise your use of Omni as a user or viewer

Omni’s AI features also helped reduce friction for non-technical users. They could use AI to explore curated datasheets, see our documented business logic to improve metric trust, and ask questions in natural language as an easier entry point into self-service.

Lessons Learned

We made sure to work on both BI tools in parallel. This approach ensured that users never lost access to reports or dashboards during the migration. This was critical to keep confidence high and avoid blockers.

Redirects from Looker to Omni were only introduced once each department had fully signed off on their content.

Every migration teaches you something. Here’s what we learned:

  • You don’t need to migrate everything, so use the moment to be intentional
  • Governance isn’t a post-migration step, it should guide the rebuild
  • Training and adoption matter more than you think
  • Build dashboards for how people will use them, not how they used to

Also note that overlooking is part of the process. No migration plan can account for everything. We encountered unexpected challenges along the way, but having agile problem-solving and very skilled and hard-working data team members made all the difference.

What’s Next?

Even after the migration, our work continues. In 2025, we’ve focused on:

  • Automated deliveries for reporting
  • Continuing to refine performance and semantic modelling
  • Adding more AI context into Omni’s semantic model to make for even easier exploration across datasets and dashboards

Final Thoughts

Migrating a BI platform is no small feat. But with the right planning, stakeholder alignment, and mindset, it can be an inspiration for something much bigger.

This migration helped us clean house, rebuild with purpose, and empower over 140 Game Lounge employees to use data with more confidence and speed than ever before.

Should you be interested, our Senior Data Architect, Robert Cassar Pace, will also be covering this topic in more technical detail at BIG DATA LDN 2025 this month.

Let’s Connect

We welcome and highly encourage feedback from other professionals in the data field. If you have any questions regarding BI migrations or would like to learn more about Omni, please contact us. We can facilitate a direct introduction to the Omni team for a better overview of the platform.
For more on our data team’s journey, check out: Game Lounge Data Team gain trust. Platforms gain relevance.

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