RebuildData engineering and migration
We design data platforms your teams trust, build the pipelines that feed them, and migrate data out of ERPs and legacy systems with reconciliation built in. Nothing is switched off until the numbers reconcile.
Data problems rarely announce themselves. They show up as arguments, delays and workarounds.
Finance, sales and operations bring different figures to the same meeting.
Teams keep their own versions because the official reports can't be trusted.
Someone exports, cleans and stitches data by hand before every review.
A new ERP, a cloud move or a system retirement means years of data must move safely.
AI ideas stall because the data they need is scattered, inconsistent or unsafe to use.
From the first pipeline to a platform the whole business relies on.
Warehouses and lakehouses on AWS, Azure, Google Cloud or Oracle Cloud, designed around how decisions get made.
Batch and near-real-time pipelines that pull from ERP, CRM and operational systems, with monitoring built in.
ERP and legacy migrations with profiling, cleansing, mapping and record-level reconciliation.
Self-service dashboards on shared definitions, so every team reads the same number the same way.
Quality checks, lineage and access controls that make data safe to share and easy to trust.
Clean, well-described data, plus the vector and graph stores that retrieval and agents depend on. See the AI we build
Most migration failures are invisible at go-live: a mapping error that surfaces months later as a number nobody trusts. Our method is built to catch them first.
Measure the quality of the source data before promising anything.
Agree mapping rules with the business and fix issues at the source where possible.
Run repeated trial loads until every run is clean and predictable.
Match counts, totals and individual records, and get business sign-off.
Switch with a parallel run and a rollback plan ready.
| Data set | Source | Target | Status |
|---|---|---|---|
| Customers | 48,210 | 48,210 | Matched |
| Suppliers | 6,934 | 6,934 | Matched |
| Open invoices | $12.84M | $12.84M | Matched |
| GL balances | 1,284 accts | 1,284 accts | Matched |
| Item master | 21,406 | 21,398 | 8 to review |
Nothing is signed off until every line is matched or explained.
When three teams have three versions of revenue, every meeting starts with an argument. We fix the definitions first, then the dashboards.
Key metrics are defined once, agreed with the business and reused everywhere.
Failed or late loads raise alerts before anyone opens a stale report.
Every number can be traced back to the system and the record it came from.
People see the data they need, and access to sensitive data is controlled.
It usually sits next to another change. The same team can cover both.
Reliable reporting and data extracts from Oracle Fusion, supported by our managed services team.
Oracle Cloud and managed services Modernizing an applicationMoving on-premises databases to managed cloud databases as part of the rebuild.
Application modernization Adding AI to a productPreparing the data that assistants, retrieval and agents need to give trustworthy answers.
Product engineeringWe work with the databases, clouds and reporting tools you already have, and recommend changes only when the business case is clear.
From data platform and migration work.
“Vanna consolidated reporting across multiple systems into a single data platform, significantly improving executive decision visibility.”
“Their team handled both data migration and analytics setup during our system transition, which prevented operational disruption.”
Pick the one that matches the problem in front of you.
When you're not sure where the problems are
We profile your key data sets and reports, and show where quality, definitions or pipelines are letting you down.
For an ERP change or system retirement
Profiling, mapping, rehearsals and reconciliation through to a signed-off cutover.
For a platform the business relies on
A dedicated team that builds and runs your pipelines, platform and reporting, month after month.
We reconcile counts, totals and individual records between source and target on every trial load, and the business signs off before cutover. Anything that doesn't match is explained or fixed.
It's normal. We profile it first, so the issues are known up front, then agree which to fix at the source and which to clean during migration.
Not always. Sometimes shared definitions and a few reliable pipelines are enough. We recommend a platform only when the reporting and AI needs justify it.
We plan the reporting switch as part of the cutover, run old and new side by side, and compare results before retiring anything.
Access is scoped and reviewed, sensitive fields are masked in non-production environments, and work happens in environments you control.
Yes. We document pipelines and definitions as we build, and your team can take over, or we can keep running it.
Tell us about your data and what's coming next. We'll suggest a practical first step.