Managing a Successful Data Platform Migration

We have worked with many clients to successfully migrate their business intelligence (BI) and enterprise data warehouse to a new platform. The projects that delivered the most value all had a common set of characteristics in how the client approached and managed the migration. In this article we’ll discuss the key factors to making a data migration successful.

Never just replicate, always re-architect

Many organisations that approach us asking for assistance with a migration want to simply replicate what they have in their legacy system in the new platform. The motivation being to simplify the migration and save cost, however, this is a false economy. This typically leads to a sub-optimal implementation and an unsatisfied user base who question the purpose of the migration if they just get what they had before.

Limiting the migration to just copying the system “as is” results in carrying over all the old inefficiencies, duplications and technical debt into the new platform. Successful migrations go beyond pure lift-and-shift — they take the opportunity to re-architect and optimise. Rather than replicating inefficiencies, they streamline data models, eliminate redundant data, and modernise ETL pipelines. They redesign the warehouse for cloud best practices (for example, adopting a lakehouse architecture on Databricks or a star schema on Snowflake with elastic compute). In the BI layer, they redesign reports to leverage new interactive features and ensure performance.

Successful projects ensure that once the migration is “done,” the new BI and cloud warehouse deliver better data quality and performance, and more business value to the organisation.

User buy-in is vital

We often see organisations focus purely on the technical delivery of their migration and forgot to include end-users in the migration project. Organisations that don’t get buy-in from their users will face low uptake of the new data platform, undermining the ROI of the whole project.

User adoption can be hindered by a lack of training, or simply user resistance — for instance, business users who spent years building reports in Excel or a legacy BI tool might be reluctant to switch to new software if they don’t see immediate value. There is often fear of the unknown (“Will I still get the data I need?”) or loss of familiar features. If the migration isn’t communicated and managed well, users might bypass the new systems (e.g. exporting data to CSV and analysing offline, negating the benefits of a governed BI platform).

Ensuring adoption requires a comprehensive change management effort: communication about why the change is happening, how it benefits users (faster insights, better tools), and assurance that sufficient support and training will be provided.

Organisations must consider data literacy among users — if users are already comfortable with self-service BI concepts, they will adapt to a new tool like Power BI faster. Conversely, if the company is new to broad BI usage, adoption might require more fundamental data literacy efforts.

Involving business users and domain experts in the migration process (co-designing solutions, participating in testing) also ensures the end result actually meets business needs, which in turn drives user satisfaction and adoption.

These measures significantly mitigate resistance and ensure that once the new system is live, it is actually utilised to its full potential. Technology change is only effective if users embrace it. Stakeholder buy-in is critical.

Rationalise the scope

To maximise the ROI of your migration you need to focus the scope to only where value is added. Before beginning any migration you need to assess your existing data and BI platform to understand the current state of your assets and what the desired future state looks like.

Enterprises often have decades of accumulated data and reports to contend with. An inventory of a legacy BI environment may reveal thousands of reports and dashboards, many of which are redundant or outdated. In practice, companies find a large portion of legacy reports aren’t even actively used — a client of ours discovered ~40% of 1200+ dashboards were unused “junk” that would be a waste to migrate.

Rationalising the scope of a migration to only focus on assets that need migrating will typically reduce the scope of the migration by over 50%. Significantly reducing the time and effort required, and therefore the cost.

We always begin our migration projects with a thorough planning phase: auditing existing data assets, reports, and usage to determine what should (or should not) be migrated. The above diagram illustrates the process we use when planning a BI tool migration.

Strong Executive Leadership

Moving large volumes of data from on-premise systems to the cloud is often complex and time-consuming, requiring careful planning to maintain data integrity. Transferring mission-critical ETL workloads and schema to a new platform (e.g. Teradata or SAP to Snowflake/Databricks) can be resource-intensive, especially if decades of historical data are involved.

Executive leadership provides the vision, urgency, and resource commitments needed to push through challenges and organisational inertia. These sponsors champion the project’s importance, communicate progress to other execs, and help remove organisational roadblocks (for example, resolving inter-departmental conflicts or securing additional funding for unplanned needs).

Executive support also lends credibility to the change: when top management consistently messages that “we are becoming a data-driven, cloud-powered organisation,” it helps overcome cultural resistance at lower levels.

When the migration is championed by executives then it is not treated merely as an IT project but as a business transformation. This means articulating clear objectives (what business outcomes and improvements are expected) and using those to guide technical decisions. In successful cases, business stakeholders are involved from day one — for instance, power users might help test the new Power BI reports and give feedback on design, or data scientists might validate that the new cloud platform (Fabric/Databricks) can support their advanced analytics. This collaboration fosters a sense of ownership and alignment between IT and business, smoothing the path for adoption.

Deliver quick wins

Conduct a proof of concept (PoC) or pilot migration early. For instance, migrate a small department’s data or a subset of reports to the new BI tool to validate the approach, uncover issues, and refine processes before scaling up. This incremental approach allows learning and adjustment with minimal risk.

A proof of concept provides an opportunity to incorporate user feedback early on. When users feel heard they become more positive about the change. Rolling out in stages to specific user groups, gives them time to adjust. A good tactic is to pilot the new platform with a friendly department and incorporate lessons learned before broader roll-out.

For some clients we have chosen to start with greenfield deliverables before beginning the migration of the legacy data warehouse and reporting. We delivered a quick win that didn’t require reverse engineering existing code beforehand and it gave us the flexibility to define the architecture to best fit the new environment without being prejudiced by the legacy way of doing things.

Finally, delivering a quick win provides a case study that executive sponsors can use to champion the migration when advocating for it across the firm. Demonstrating tangible business value early on greatly assists with user and stakeholder buy-in.

Successful migrations are well-planned, phased, and transformational to the business (versus big-bang lift-and-shift).

TLDR

To summarise the key factors to managing a successful data platform migration are:

• Never just replicate, always re-architect
• User buy-in is vital
• Rationalise the scope
• Strong executive leadership
• Deliver quick wins

There are other elements to managing a migration project, but all of the above are critical. Skip any of them and your migration is likely to not deliver the business outcomes you hoped for.

If you’re about to embark on a data platform or BI migration and would like some advice on how to make it a success, please get in touch info@peraison.com.