Legacy BI tools and on-prem data warehouses are holding you back. We migrate your data, dashboards, and pipelines to modern cloud platforms — with zero data loss and minimal business disruption.
The Reality
Your data and BI infrastructure wasn't built for today's demands. Every month you delay migration, you're paying more for less — in licence fees, maintenance overhead, and missed opportunities that modern platforms unlock.
Your organisation is still running Cognos, MicroStrategy, or Crystal Reports. Licence costs are rising, talent is scarce, and the vendor roadmap doesn't align with your cloud strategy.
On-prem infrastructure, legacy ETL servers, and outdated BI licences are consuming 60–70% of your data budget — leaving nothing for innovation or new capabilities.
Your data warehouse can't scale elastically, doesn't support modern analytics patterns, and forces your team into batch-only workflows that are always a day behind.
Reports that used to take seconds now take minutes. Dashboards time out during peak hours. Your legacy platform wasn't built for the data volumes you're generating today.
The engineers who built your legacy platform have left or retired. New hires don't want to work on outdated technology, and finding specialists is getting harder every year.
Your legacy systems lack modern security controls, audit trails, and data governance. Every compliance review surfaces new gaps that are expensive and slow to remediate.
Different teams use different BI tools. Nobody trusts a single number. Executives get conflicting reports, and reconciliation takes days instead of seconds.
You know you need to migrate, but the risk of data loss, business disruption, and project overruns keeps the decision stuck in committee — while costs keep climbing.
Our Expertise
Migrate from Cognos, MicroStrategy, Crystal Reports, and other legacy BI tools to modern platforms like Tableau, Power BI, and Looker — without losing business logic or historical context.
Move your on-premises data infrastructure to Snowflake, Databricks, BigQuery, or Azure Synapse — with a structured approach that minimises risk and maximises cloud-native capability.
Replace legacy ETL tools like Informatica, SSIS, and Talend with modern orchestration frameworks — Airflow, dbt, and Fivetran — for faster, more reliable data pipelines.
Consolidate siloed data warehouses into a unified lakehouse or cloud warehouse — reducing duplication, improving governance, and enabling self-service analytics.
AI-Powered Migration
We don't just lift and shift. Our AI-powered migration toolkit automates the most time-consuming and error-prone parts of every migration — from schema mapping and complexity scoring to data validation and risk prediction.
Explore AI Migration ToolsAI-driven complexity scoring that analyses your existing reports, queries, and pipelines to estimate migration effort, risk, and priority — before a single line of code is written.
ML-powered column and table matching that automatically maps source schemas to target platforms — reducing manual mapping effort by up to 80% on large-scale migrations.
Automated testing and comparison frameworks that validate every row, column, and aggregation between source and target — ensuring zero data loss and complete accuracy.
Predictive analytics that identify potential migration failures before they happen — flagging data quality issues, dependency conflicts, and performance bottlenecks early.
Migration Ecosystem
Whether you're moving to a new cloud data warehouse, switching BI tools, or modernising your ETL stack — we have deep expertise across the entire modern data ecosystem.
+ migration support for 50+ legacy and modern data platforms
Our Process
We audit your entire data and BI landscape — cataloguing every report, pipeline, data source, and dependency — and deliver a prioritised migration roadmap with effort estimates.
We design the target architecture: cloud platform selection, schema mapping, ETL patterns, security model, and a phased migration plan that minimises business disruption.
Our engineers build the new platform in parallel with your existing systems — migrating data, converting reports, and replatforming pipelines with continuous validation at every step.
We execute the cutover with automated data reconciliation — comparing every row between source and target — and run user acceptance testing before going live.
Post-migration, we decommission legacy systems, optimise performance on the new platform, train your teams, and provide hypercare support to ensure a smooth transition.
Case Study
A global financial services firm was locked into IBM Cognos with 2,000+ reports, 15 years of historical data, and rising maintenance costs. We executed a full migration to Tableau and Snowflake — converting every report, validating every data point, and decommissioning the legacy platform in 12 weeks.
2,000+
Reports migrated
Zero
Data loss
60%
Cost reduction
3×
Faster reporting
Data loss across 2,000+ reports
Validated · Reconciled · Guaranteed
Real Results
60%
Average cost reduction after migrating from legacy platforms
Zero
Data loss guarantee across every migration we deliver
3×
Faster reporting and dashboard performance on modern platforms
One
Unified platform for data, dashboards, and pipelines
How We Work
Pick the model that fits where you are. All engagements include a dedicated migration lead and a clear outcome definition.
Ideal for: Teams planning a migration who need a clear roadmap
A 2-week deep dive into your current data and BI landscape — cataloguing assets, scoring complexity, estimating effort, and delivering a prioritised migration plan with risk analysis.
Ideal for: Organisations ready to migrate data, dashboards, or pipelines
A complete migration engagement — from architecture and parallel build through to cutover, validation, and legacy decommission — delivered by a dedicated migration team in 8–12 weeks.
Ideal for: Teams that want ongoing support after migration
We manage your new platform end-to-end — monitoring performance, optimising costs, resolving issues, and ensuring your migrated environment runs at peak efficiency.
Common Questions
Data migration is the process of moving data from one platform to another — typically legacy → cloud, on-prem → SaaS, or one cloud platform to another. Common patterns: Teradata → Snowflake, Oracle → Databricks, on-prem Hadoop → cloud lakehouse, legacy BI tools → modern visualisation. Distinct from data modernization, which migrates AND redesigns; pure migration preserves the existing model.
Five pillars: legacy BI and dashboard migration (Cognos / MicroStrategy / Business Objects → Tableau, Power BI, MCI); cloud data platform migration (on-prem → Snowflake, Databricks, BigQuery); ETL and pipeline replatforming (legacy ETL → modern ELT); data warehouse modernisation; automated migration assessment and smart schema mapping (AI-assisted to accelerate complex migrations).
Migration is lift-and-shift — same data model, new platform. Modernization re-architects during the move (new patterns, new governance, new capabilities). Sometimes migration is right (you've already modernised, you just need to switch hosts). More often modernization is right (you're moving anyway, so fix the technical debt while you're at it). See data modernization for the longer transformation play.
A focused single-platform migration (one source, one destination, basic data) runs 10–16 weeks. A complex enterprise migration (multiple legacy systems, hundreds of tables, parallel-run requirements) runs 6–12 months. Dashboard migrations specifically (BI tool to BI tool) tend to be faster — 6–10 weeks for 20–50 dashboards using our automated assessment tooling. Discovery call first.
Every migration we deliver assumes zero downtime. Parallel-run patterns where source and destination both produce data; reconciliation reports to validate parity; cutover windows scheduled in low-traffic periods; rollback paths in place for every step. For regulated environments, dual-write periods of 30–90 days before fully decommissioning the legacy system are standard.
We've delivered enterprise data migrations across Teradata → Snowflake, Oracle → Databricks, on-prem Hadoop → cloud lakehouse, Cognos → Tableau, MicroStrategy → Power BI, and dozens of other paths since 2004. Snowflake Select Partner, Databricks Premier Partner, Salesforce SELECT. AI-assisted migration tooling accelerates schema mapping by 40–60% on large migrations.