Move to Azure without
breaking what runs on it.
We are data migration specialists. Legacy warehouses, on-premise estates and ageing SAS platforms, moved to Azure one workload at a time, with every number tested against the original before anything is switched off.
A migration you can defend to a regulator.
Most migrations stall in the same place. Nobody has a clear picture of the estate, so the order of work becomes an argument rather than a plan. We start with the inventory, score every workload, then move in a sequence that holds.
Estate inventory first
We catalogue every workload: what it does, how often it runs, and who owns it. Nothing moves until we know exactly what we are moving.
Scored, not guessed
Each workload is scored against business criticality, complexity, data dependencies, and regulatory risk. The migration order is transparent and consistent, not a matter of opinion.
Dependencies mapped
We map what each job reads from and writes to, so workloads migrate in an order that actually holds together, not one that only looks tidy on a plan.
Validated against the original
Rebuilt logic is run alongside the system it replaces and reconciled row by row. The numbers match before the old platform is turned off, and you see the comparison.
Azure, set up properly
the first time.
A migration is only half the job. What you land on decides whether the next five years are cheap or expensive, so we build the destination before we fill it.
Landing zone before workloads
Subscriptions, networking, identity and access laid out to your governance rules first. Migrating into an estate nobody designed is how cloud bills and audit findings both start.
The right Azure services
Data Factory, Synapse, Fabric, Databricks, Azure SQL and ADLS Gen2 are tools, not a strategy. We pick per workload and tell you when a cheaper one does the job.
Cost modelled before you commit
Storage tiers, compute sizing and what it costs to run each workload monthly, estimated up front and tracked afterwards. No surprise in month three.
Lineage and cataloguing
Purview or the equivalent wired in as we go, so by the end you can answer where a figure came from without anyone reading pipeline code to find out.
Still running SAS?
It is the migration we are asked about most, and the one with the most ways to go wrong. SAS is proprietary, costly and ageing, but the business logic inside it is usually load-bearing: credit models, regulatory returns, and reports that somebody signs their name to every quarter.
We move you off it in a controlled, auditable way, one workload at a time. SAS logic is refactored to Python and modern Azure tooling, then run in parallel against the original until the output reconciles. Orphaned and undocumented jobs are a priority rather than an afterthought, because those are the ones that take the knowledge with them when the person who wrote them leaves.
The same method works on Teradata, Oracle, Informatica, a warehouse nobody has touched in a decade, or a folder of scheduled scripts. SAS is simply where it gets tested hardest.
The controls are part of the work.
Explainable models
Where models feed credit or eligibility decisions, we keep them explainable and auditable, so FCA and Consumer Duty obligations are met, not bolted on later.
Data stays where it belongs
We design around your data residency and cloud rules from day one, including which Azure regions are acceptable. Nothing sensitive moves to a place your governance would not allow.
Full audit trail
Every migration decision is recorded and reconstructable, with retention and deletion handled correctly across each data layer.
No loss of knowledge
Orphaned and undocumented jobs are a priority, not an afterthought. We capture the logic before the people who understand it move on.
Momentum early, risk controlled throughout.
Tap a step to see what happens in it.
We catalogue every workload: what it does, what it reads, how often it runs, and who owns it. Nothing moves until we know exactly what we are moving.
Each workload is scored on business criticality, complexity, data dependencies, and regulatory risk, so the migration order is transparent and defensible, not a matter of opinion.
We map what each job reads from and writes to, so workloads migrate in an order that actually holds together, not one that only looks tidy on a plan.
Workloads are grouped into waves: quick wins first to prove the landing zone, then the core migration, then the complex and regulated workloads last.
Logic is rebuilt on Azure and tested against the original output, so the numbers match before anything is switched off.
Discover
We catalogue every workload: what it does, what it reads, how often it runs, and who owns it. Nothing moves until we know exactly what we are moving.
Ready to cost your migration?
Book a free 30-minute call and we will map the first move, honestly, before any commitment. If your problem turns out to be something other than a migration, we will tell you that too.
Book a discovery callNot sure this is the piece you need? The about page covers how we work, and where we work covers the rest.
