Target Mapping
Every source component gets its target service, tooling lane and disposition, in a source-to-target map you keep.
Prepare the estate
before the first wave lands.
Your Fabric or Databricks target is built with its layers, environments and access designed together, ready before the first wave lands.
Clear data layers
Raw, validated and serving data each have their own place.
Separate environments
Development, test and production stay apart from the start.
Access built in
Permissions and lineage are set in the platform, not added later.
Scoped in the first working session · Fixed price · The configured estate is yours
A target ready for the first wave,
not an empty lakehouse.
A newly provisioned platform is easy to mistake for a ready one. The hard questions arrive with the first real workload: where data lands, how it is promoted and who can use it.
One path for the data
Bronze, silver and gold layers give every wave the same route through the estate.
Access agreed up front
Identity, permissions and network boundaries follow the agreed governance design.
Documented with the build
Your team inherits a system it can read, not resources whose purpose lives in a chat.
This is the right engagement when
- The target platform and governance direction are agreed.
- Every wave needs the same landing and serving path.
- Workspaces and permissions are being created case by case.
Layers for the data.
Boundaries for the estate.
Four steps take the target from provisioned to ready, and each ends in something you keep.
We map raw, validated and serving data onto bronze, silver and gold layers in OneLake or Delta.
You receive
Layer design
Where data lands, how it is promoted and where it is served.
What this is not.
This service builds the target for an agreed platform and governance design, and it ends when the serving path is proved.
Still deciding who owns the data?
That is Data GovernanceAdding a new source to an estate already running?
That is Data Integration
The story this service stands on.
An Australian building-materials manufacturer
Manufacturing · Building materials
- Warehoused data unified in one governed model
- Around 3 TB
- Automated SAP-to-BI integration, no manual steps
- 100%
SAP to Self-Serve Power BI, With Reporting 50× Faster Than MS SQL
The manufacturer ran reporting on spreadsheets and manual data pulls that were slow, error-prone and hard to explore. We automated the flow of sales and finance data from SAP ECC through Azure Data Factory into one governed Databricks Lakehouse model holding around 3 TB of warehoused data. SAP-to-BI integration now runs with no manual steps, and sales, accounts and finance work from self-serve Power BI.
Questions buyers ask.
What is a governed landing zone for Fabric or Databricks?
A governed landing zone is a target platform with its data layers, environments and access designed together before the first migration wave arrives. Raw, validated and serving data get bronze, silver and gold layers in OneLake or Delta. Development, test and production workspaces stay apart, and identity, permissions and the network baseline are configured against the agreed governance design.
Why build the target platform before migrating any data?
Because a provisioned platform is not a ready one, and the gaps surface with the first real workload. That is when teams ask where raw data belongs, how it is promoted, how development stays separate from production and who can use the result. Answering those questions once, in the target, gives every later wave the same landing and serving path instead of decisions made case by case.
Do you set up Unity Catalog and Microsoft Purview?
Yes, on whichever platform you have chosen. GovKit sets up Unity Catalog with users, permissions and jobs on Databricks, or workspaces, domains and Purview lineage on Fabric. Permissions and lineage are set in the platform from the start, configured against the governance design you have agreed, rather than added once the estate is already in use.
What has to be decided before the target estate is built?
The target platform and the governance direction have to be agreed first. Who owns the data, and who may use it, are decisions for Data Governance; this work implements them in the platform. The duration is scoped in the first working session, at a fixed price, and you keep the configured foundation with its layer, environment and access design documented alongside it.
More in Modernization.
Natural next step
Natural next step: Platform Modernization, Modernization
Prepare the logic and reports that will run on the new foundation.
Platform Modernization
Legacy mappings and report logic are converted where it is safe and redesigned where it is not. You keep the conversion inventory and retirement plan.
Migrations
Data moves in waves, and Migration Recon proves each one matches. You keep the evidence reports, cutover plan and rollback plan.
Cost Optimization
Cost is engineered into the move: what to retire, a measured target size and a cost case for each wave.
Give the migration
somewhere ready to land.
Bring the target architecture and your first wave to a 30-minute working session.