The 7 Steps of Data Migration: From Key Considerations to Potential Pitfalls

Migration can be customized to your business needs—but these steps are crucial for establishing a clear, comprehensive understanding of your business’ objective.  

Step 1: Assessment and Planning

Before you migrate, you need a map. 

 A successful analytics platform migration begins with a clear understanding of where you are today—and where you want to go. This means conducting a detailed inventory of your current environment, defining the goals of your transition, and engaging every stakeholder involved. 

• Assess the Current State of Your Architecture 

Start by auditing your existing analytics environment. What assets are in play—dashboards, reports, data models, or third-party integrations? What platforms and workflows do different departments rely on? 

Go deeper than the front end: capture logic dependencies, custom scripts, scheduled jobs, and legacy data connections. Pay attention to performance issues or limitations—this will inform not just what needs to change but what needs to improve. 

• Define Clear Objectives and Scope 

Migration isn’t just a lift-and-shift—it’s an opportunity to reimagine how your organization uses analytics. Define clear goals: 

• What do you want to accomplish in the first 90 days post-migration? 

• What out-of-the-box features in Strategy One are critical to activate? 

• What does success look like for each team each quarter? 

Consider how your future-state semantic layer will enable reuse, alignment, and speed across teams.  

Establishing the scope, priorities, and a realistic timeline (and budget) will create alignment and prevent delays later. 

• Engage Stakeholders Early 

The most successful migrations are never IT-only projects. Gain buy-in across departments—primarily business users who rely on analytics daily. Ensure that everyone understands not only the migration timeline but also what is changing, what is improving, and how their input influences the process. 

Step 2: Data Considerations

Your platform is changing—but your data is the foundation. 

Before any dashboards are rebuilt or models restructured, you need to assess the integrity, scope, and compliance of the data behind them. This step ensures that what you migrate is clean, reliable, and aligned with your governance policies. 

• Build a Complete Data Inventory 

Start by cataloging all active data sources across your current environment. Which databases, cloud platforms, APIs, and file systems are in use—and by whom? 

Document the volume and types of data that need to be migrated and note any dependencies between sources, pipelines, or scheduled jobs. 

• Evaluate & Clean Your Data 

Migration is the perfect moment to improve—not just transfer—your data quality. 

Run profiling and cleansing routines to identify inconsistencies, null values, redundant fields, or outdated datasets. Align fields and formats with your future-state semantic layer structure. Strategy One’s semantic graph makes this easier—supporting federated joins, reusable logic, and downstream propagation.  

Clean input means cleaner insights, faster model deployment, and less technical debt post-migration.  

• Define a Data Migration Strategy 

Design your ETL (Extract, Transform, Load) workflows with data integrity in mind. Strategy One supports a range of flexible ingestion patterns—but consistency is key. 

Establish how source data will be mapped, transformed, and validated in the new environment. Define consistent rules for historical data: 

• What gets archived? 

• What gets purged? 

• What requires full fidelity? 

Test often. Validate early. 
 

• Align Security and Compliance 

Don’t wait until after migration to think about access control or audit trails. 

Review your current security protocols and ensure that your Strategy One instance can enforce existing permissions—or improve upon them. Confirm that all personal or regulated data adheres to compliance standards such as GDPR, HIPAA, or SOC 2 throughout and after migration. 

Step 3. Technical Considerations

Architecture matters. 

Even the most user-friendly analytics platforms require a solid technical foundation to perform at scale. Before the migration proceeds, you'll need to validate the underlying architecture and how Strategy One will integrate with your existing systems.

• Analyze Your System Architecture 

Start by comparing your existing architecture with Strategy One. What does your infrastructure look like today? Is it cloud-first, hybrid, or on-premises? 

Strategy One supports flexible deployment models, but it’s essential to assess: 

• What hardware or virtualized environments will be needed? 

• Are there operating system, networking, or storage constraints to address? 

• Can your current infrastructure support semantic modeling at scale? 

• Plan for Seamless Integration 

Strategy One doesn’t operate in a vacuum. You'll need to ensure compatibility with your: 

• Data warehouses 

• Relational databases 

• ETL tools 

• BI platforms 

• Productivity apps 

Assess any third-party systems that interface with your current analytics environment. Identify middleware, connectors, or APIs that will be required to maintain continuity.  
 
Strategy’s open architecture supports 200+ integrations—but mapping those connections proactively saves time and prevents disruptions. 

• Performance Tuning 

Early testing is key. Run load simulations to determine how your Strategy instance performs under real-world query volume and concurrency. 

Establish performance benchmarks and identify any potential bottlenecks in areas like: 

• Query execution time 

• Semantic layer caching 

• Cross-source joins 

• API responsiveness 

The goal isn’t just to match performance—but to improve it. 

Step 4. Skill Set and Training

Migration success doesn’t end with deployment—it depends on enablement. 
Even the most powerful analytics platform is only as effective as the people using it.  

• Assess Your Team's Current Skill Set 

Start by evaluating the technical proficiency of the teams that will be involved—from BI developers to analysts to IT administrators. Do they have experience with semantic modeling? Are they familiar with federated data environments or AI-assisted data prep? 

Identifying gaps early helps shape the training plan—and prevent friction later. 

• Build a Training Plan That Scales 

Equip users with the right resources based on their roles: 

• Administrators need deep dives into configuration, security, and data governance. 

• Data teams benefit from workshops on modeling, integration, and automation. 

• Business users need fast, intuitive onboarding to explore data confidently. 

Strategy One supports this with role-based enablement—offering structured training paths, live webinars, robust documentation, and self-paced online courses. Your teams don’t just learn the platform—they grow with it. 

Step 5. Testing and Validation

No migration is complete without rigorous testing. 

Before rolling out Strategy One organization-wide, it's essential to validate the platform's performance, functionality, and usability—starting small and scaling with confidence. 

• Start With a Controlled Pilot 

Begin by running a limited pilot using a subset of users, teams, and representative datasets. This allows you to test real-world workflows in a low-risk environment. Collect feedback early—on both technical functionality and user experience—and use it to fine-tune the configuration. 

A successful pilot is your blueprint for broader success. 

• Validate Data and Functionality 

Check that all dashboards, metrics, and semantic logic perform as expected. Strategy One’s semantic graph enables consistent logic validation across complex data environments.  

Confirm that data flows are complete and accurate across sources and outputs. Run end-to-end tests on key workflows: 

• Data ingestion 

• Semantic transformations 

• Report generation 

• Visualization accuracy 

Every function your users depend on should be tested before going live. 

• Conduct User Acceptance Testing (UAT) 

Engage your business users to validate whether the new environment meets their needs. UAT is about more than functionality—it’s about trust. 

Make space for questions, surface usability issues, and resolve blockers before rollout. Early engagement here builds momentum and confidence across teams. 

Step 6. Go-Live

Execution without disruption—that’s the goal. 

A successful go-live balances readiness with risk mitigation. With careful planning, communication, and real-time support, you can ensure a smooth transition to Strategy One without interrupting critical business operations. 

• Establish a Cutover Strategy 

Choose a go-live window that minimizes business disruption—often during off-peak hours or scheduled downtime. Finalize your cutover approach, whether it’s a phased rollout or a big-bang switch. 

Just as important: define backup and rollback plans. While not always needed, they’re essential for managing risk and ensuring business continuity. 

• Align Your Communication Plan 

Notify all stakeholders well in advance of the go-live schedule. Ensure users understand: 

• What’s changing and when 

• Where to access the new platform 

• How to report issues or ask questions 

Provide centralized documentation, FAQs, and support contacts to minimize confusion and empower users from day one. 

• Deliver Post-Migration Support 

Go-live is just the beginning. Monitor platform performance closely—especially query speed, access patterns, and dashboard load times. Be ready to address user concerns quickly and collect structured feedback that can guide future iterations. 

Enabling feedback loops isn’t just good support—it’s how you drive continuous improvement. 

Step 7. Potential Risks and Mitigations

Every migration carries a risk—but thoughtful planning keeps you in control. 

By identifying potential pitfalls early and implementing safeguards, you can reduce the likelihood of disruption, budget overruns, or adoption failures. Here are the most common risks—and how to mitigate them. 

• Data Loss 

Data integrity is non-negotiable. 

Maintain regular backups throughout the migration and perform validation checks at every phase—from extraction to final loading. This ensures that no critical data is lost in translation. 

• Downtime 

Minimize disruption by planning your cutover during off-peak hours or scheduled maintenance windows. 

Have failover plans and quick-response protocols in place in case unexpected issues arise. The smoother the transition, the faster teams regain productivity. 

• User Resistance 

Adoption is as much about perception as it is about performance. 

Combat resistance by clearly communicating the benefits of the new platform early—and often. Offer tailored training, responsive support, and concrete examples of what users will gain. When people feel prepared, they’re more likely to embrace change. 

• Cost Overruns 

Uncontrolled scope creep, delays, or misaligned expectations can quickly inflate your budget. 

Stick to a well-defined scope, track progress against milestones, and build contingency plans for unexpected requirements. Regular audits keep stakeholders aligned and prevent surprises. 

Why Migrate to Strategy One?

Strategy One is a leading business intelligence and analytics platform renowned for its AI-powered capabilities, scalable architecture, and enterprise-grade performance. 

Organizations migrate to Strategy One to unlock a modern, AI-powered analytics experience—one that supports better decision-making, improves operational agility, and scales insight delivery across the business. 

Whether your current platform is aging or simply falling short, now is the time to explore a governed, AI-powered alternative. With Strategy One’s dynamic semantic layer and integrated engines, migration isn’t just a move—it’s modernization. 

Conclusion

Migration is a critical opportunity to modernize your analytics environment—but success depends on strategic planning, technical alignment, and strong change management. 

By proactively addressing these steps and potential risks, your organization can make the transition to Strategy One seamless, secure, and future-ready. 

With governed data, flexible architecture, and unmatched AI + BI integration, Strategy One helps you unlock deeper insights—without compromise. 

Want to go deeper? Check out our comprehensive Migration Guide—a step-by-step resource for moving from legacy BI to a modern, AI-powered platform without compromising governance, security, or reporting depth.