Unclear legacy data quality and hidden dependencies
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Data Migration
Move legacy data assets to cloud and warehouse platforms with controlled risk.
PostgreSQLMongoDBSnowflake
Overview
Data Migration
Data migration is a delivery program — not only an ETL job. We cover assessment, transformation, validation, cutover, and rollback so data remains usable for AI, analytics, and operations.
Migrations fail when source complexity is underestimated, transformation rules stay informal, validation is thin, or cutover day is improvised. We start with a clear assessment of systems, domains, dependencies, and risk, then lock mapping specs, validation criteria, and cutover procedures.
We combine ETL/ELT, phased moves, dual-run windows, and final cutover controls to reduce downtime. After go-live, we stabilize with monitoring and remediation so migrated data supports AI, analytics, and business systems with confidence.
Business Outcomes
- Lower migration risk and downtime exposure
- Validated data quality standards stakeholders can trust
- Reusable cloud/analytics-ready data assets
- Clear ownership after cutover
Service Detail
Key Challenges We Address
Missing transformation rules and validation criteria
Cutover downtime risk without a tested rollback path
Technologies & Tools
Technologies & Tools
Source systems, target platforms, pipelines, and controls for reliable data migration.
01
Source systems
Databases and systems we migrate from.
PostgreSQL
Reliable open-source relational database used for transactional and analytical workloads.
MySQL
Popular relational database used in SaaS and enterprise application backends.
Microsoft
Enterprise productivity and data stack including SQL Server, Power Platform, and Microsoft 365 integrations.
MongoDB
Document database for flexible schemas and modern application data models.
02
Target platforms
Cloud warehouses and platforms we migrate into.
Snowflake
Cloud data platform for storing, sharing, and analyzing enterprise data at scale.
Databricks
Lakehouse platform for data engineering, analytics, and machine learning on unified data.
Microsoft Azure
Microsoft cloud platform for AI services, data platforms, apps, identity, and enterprise infrastructure.
Amazon Web Services
AWS cloud services for compute, storage, data pipelines, AI, and global-scale infrastructure.
03
Migration pipelines
Orchestration and transformation tools for controlled cutover.
Apache Kafka
Distributed event streaming platform for real-time data pipelines and system integration.
Airflow
Airflow is part of our delivery technology stack for this capability.
Python
Primary language for data engineering, AI development, automation scripts, and APIs.
dbt
dbt is part of our delivery technology stack for this capability.
04
Governance & control
Infrastructure and process controls around migration programs.
Terraform
Infrastructure-as-code tool for provisioning cloud resources in a repeatable, versioned way.
Docker
Container platform that packages applications so they run consistently across environments.
Google Cloud
Google Cloud Platform for analytics, AI, data warehouses, and scalable cloud infrastructure.
Service Detail
Core Capabilities
01
Migration assessment
Map systems, domains, dependencies, and risk to define migration priority.
02
Transformation design
Specify mappings, cleansing rules, and business logic in reproducible form.
03
ETL / ELT execution
Move and sync data through cloud pipelines in controlled phases.
04
Quality validation
Validate counts, integrity, sampling, and business acceptance criteria.
05
Cutover & rollback
Finalize cutover runbooks, communications, and rollback procedures before go-live.
06
Post-migration stabilization
Monitor, remediate deltas, and hand over operations cleanly.
Service Detail
Our Delivery Process
01
Discovery & Alignment
We clarify business objectives, stakeholders, constraints, and success criteria — with clear stakeholder communication — before any build commitment.
02
Architecture & Design
Solution architecture, data models, integration patterns, and delivery plans are defined with quality gates and governance checkpoints.
03
Build & Validation
Iterative engineering with structured testing, security review, and transparent milestone reporting through to production readiness.
04
Launch & Operations
Controlled rollout, hypercare, monitoring, and ongoing enhancement so systems remain stable, measurable, and improvable.
What We Deliver
What We Deliver
Migration assessment and priority map
Data mapping and transformation specifications
ETL/ELT pipelines
Validation reports and acceptance criteria
Cutover and rollback plan
Operational handover pack
Ideal For
- Organizations moving legacy databases to cloud warehouses
- Teams preparing trusted data foundations for AI and analytics
- Enterprises needing phased migration with cutover governance
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Ready to discuss your Data Migration project?
Tell us about your objectives. We’ll help define scope, approach, and next steps.