Data Migration

Your new system is ready, but years of accumulated data is trapped in the old database. Schema incompatibilities, different data formats, relational integrity issues, and inconsistent records can make migration projects far more complex than anticipated. A poorly planned migration can result in hard-to-reverse data loss and a new system that launches on a completely non-functional foundation.

Our Solution Approach

At Barlas Dijital, we manage data migration not as a one-time transfer operation but as a controlled process woven with validation steps. Every project begins with an inspection of the source data: data quality, schema structure, relationships, and size analysis are performed. We customize the ETL process with Python or Node.js to match project requirements; a pilot migration is run in full in a test environment first, and the live cutover only takes place once it completes successfully.

Scope & Features

• Database migration — Transitions in any direction between MSSQL, PostgreSQL, MySQL, MongoDB, and SQLite
• Schema transformation — Structural conversion between different data models, field mapping, and type alignment
• Content migration — Transfer of CMS, blog, product catalog, customer records, and form data
• File and media migration — From server file system to S3 or CDN; transfer of large file repositories
• Data cleaning and normalization — Cleaning up duplicate, missing, and inconsistent records; improving data quality
• Pilot migration and validation — Full run in a test environment; data integrity verification in the target system
• Rollback plan — Snapshot and restore preparation for fast rollback if issues arise
• Post-migration validation — Row counts, aggregate values, referential integrity, and relationship checks

Technical Standards

Migration scripts are written in Python (Pandas, SQLAlchemy) or Node.js; operations are idempotent in design and can be re-run. Batch processing and checkpoint mechanisms are used for large datasets; even when migrating millions of rows of data, if the process is interrupted it can resume from where it left off. Every step is logged in detail and anomalies are reported in real time.

Who Is It For?

• Businesses migrating from an old ERP, CRM, or e-commerce platform to a modern system
• Companies with more than a decade of accumulated data who do not want to lose historical data when moving to a new platform
• Technical teams requiring data transfer or consolidation between different database types

Expected Outcomes

• The new system opens fully populated with historical customer records, order history, and content archives
• The system is not taken live until data integrity validation tests pass; zero-tolerance for data loss is the goal
• Dependency on the old system for data is eliminated; the team moves entirely to the new platform
• The migration process is managed transparently; what was done and what was validated at each stage is reported