Data Migration Best Practices: 7 Steps to a Seamless Transition

How important is it to have a data migration strategy?

What are the best data migration practices?

Is it better to choose the big bang approach (all at once) or the trickle approach (phased migration)?

If all that you have are questions at this point, then let me address those and then some more. 

Let us start with the basics.

What is data migration?

Data migration involves relocating information between systems, such as shifting from on-premises infrastructure to cloud storage or across distinct databases. Beyond mere data transfer, the process requires meticulous selection, preparation, extraction, and transformation of data prior to its final relocation. Organizations typically undertake data migration during digital transformation initiatives, system upgrades, or efforts to optimize data storage and management frameworks. It is a strategic effort that affects cost, security, and performance. 

I am not just talking from my personal experience; here’s market research from some of the world’s leading consulting firms. In a world where 95% of CEOs follow a digital-first strategy [Why 95% of CEOs have a digital-first strategy, IDC, 2022] and over 72% of IT professionals work on both private and public clouds [In search of cloud value, McKinsey Digital, 2023], data migration sits at the heart of business transformation. Yet only 25% of enterprises report a solid return on investment from their cloud projects [Tangible business value from cloud transformation remains elusive, HFS Research in partnership with IBM, November 2023]. Slow adoption, unrealized use cases, and unchecked cloud sprawl are common hurdles when it comes to a lack of ROI progress [Getting ahead in the cloud, McKinsey Digital, 2023].  

In this post, we share practical steps backed by industry research and customer success stories to help your organization move data safely and cost-effectively.

Why Data Migration Matters 

If you thought that data migration is just about moving files from one system to another, then please think again. It affects several key business areas, such as 

• Cost Efficiency 

Shifting to modern systems can cut legacy maintenance costs. Cloud models with pay-as-you-go pricing help control spending. 

• Improved Accessibility and Analytics 

A streamlined data setup means teams can access information instantly, speeding up decision-making and insights. 

• Enhanced Security and Compliance 

New platforms come with advanced security features that meet strict regulatory standards and protect sensitive information. 

• Business Continuity 

With a well-planned migration, daily operations continue without disruption, keeping data accurate and available. 

Customer Success Story: #1 

Our client, a global credit bureau, modernized their data systems by moving large-scale data repositories to the cloud. By adopting a phased migration approach and upgrading the data quality tools, the company cut processing times, reduced time-to-market for new products, and lowered operational costs significantly.

Source: Migrate and Modernize— Best Practices and Anti-Patterns, AWS Builders Online Series, Blair Layton, 2024 

Key Challenges in Data Migration 

Even with clear benefits, migrating data poses several challenges: 

• Data Quality and Integrity

• System Compatibility

• Security and Compliance Risks

• Operational Disruption

Unplanned migration efforts can temporarily interrupt daily operations. 

Addressing these challenges requires a careful and structured approach, as demonstrated by companies that have successfully navigated their own migrations. 

Customer Success Story: #2 

One of our customers, a financial services organization specializing in consumer loans, faced challenges with multiple data sources and outdated systems. By following an incremental migration strategy, the customer was able to consolidate their data, which resulted in faster loan processing and better risk assessment. Loan approval times dropped drastically, and customer satisfaction improved markedly. This success highlights how a structured, phase-by-phase approach can transform operational efficiency in the financial sector. 

Best Practices for a Seamless Data Migration 

Adopting a structured approach can be the difference between a smooth transition and a costly setback. Here are seven key practices: 

1. Comprehensive Data Assessment and Planning

• Inventory Your Data: List data sources, volumes, quality, and dependencies. 

• Develop a roadmap: Define clear timelines, roles, and objectives. 

• Review Assets: Check existing software licenses, hardware, and support contracts to cut unnecessary expenses. 

2. Data Cleansing and Quality Assurance

• Clean Your Data: Remove duplicates and fix errors before starting. 

• Profile Your Data: Use tools to understand data structure and context. 

• Test in Parallel: Run both old and new systems side by side to catch issues early. 

3. Data Mapping and Transformation

• Map Formats: Align old data formats with the new system’s structure. 

• Use Automation: Apply transformation tools to adjust data formats quickly. 

• Collaborate: Involve both IT and business teams to verify the results. 

4. Robust Backup and Disaster Recovery Plans

• Back Up Everything: Make full copies of your data before migration. 

• Prepare for the Worst: Set up a disaster recovery plan and test it frequently. 

• Have a Rollback Plan: Be ready to revert changes if major issues arise. 

5. Incremental and Parallel Migration

• Phase the Migration: Transfer data in stages rather than all at once. 

• Run systems side-by-side: Compare results to validate accuracy. 

• Keep Analytics Running: Virtualize legacy data sources so that reporting and insights remain uninterrupted. 

6. Thorough Testing and Validation

• Automate Tests: Use both automated and manual tests to check data accuracy. 

• Validate Performance: Confirm that the new system processes data correctly. 

• Involve Users: Get feedback from end-users during acceptance testing. 

7. Change Management and Training

• Communicate Clearly: Inform staff about the migration plan and what to expect. 

• Train Teams: Provide practical training sessions on the new system. 

• Update Documentation: Keep user guides and procedures current to reflect the changes. 

Customer Success Story: #3 

An online retail giant needed to merge data from multiple sources, ranging from customer insights to supply chain details, into one cohesive platform. They embarked on a data migration project that integrated their systems and cleaned up outdated records. The result was a remarkable boost in data-driven decision-making and a significant drop in IT costs. This success story shows how a well-executed migration can streamline operations and sharpen competitive edge in the retail sector. 

Conclusion 

Data migration is a critical step in any company’s digital transformation journey. By following these best practices—comprehensive planning, data cleansing, robust testing, and agile execution, organizations can achieve a seamless transition that cuts costs and reduces risks. 

Our customer success stories demonstrate that with careful preparation and a clear roadmap, even complex migrations can yield remarkable results. At BBI, we recognize that each project has its own challenges and opportunities. Our expert team is ready to offer personalized guidance tailored to your needs. 

Contact us today for a free consultation and take the first step toward a successful data migration that transforms your data into a powerful business asset. 

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