Technology and Data
One version of the numbers
Pipelines, integrations and data warehouses that pull scattered data into one validated source the business can run on.
The data exists. It just does not agree.
Most organizations have more data than they use. The trouble is that it is spread across systems that store it differently, key it differently and update it on different schedules. Reporting becomes a monthly reconciliation exercise, and every decision starts with the question of whose spreadsheet is right.
We fix that underneath. We work out how records should be identified and tied together across systems, validate each load against its source, and transform the data by clear rules into one warehouse or platform you can analyze with confidence. It is methodical work. Trust in data is built one validated load at a time.
Clean data often starts upstream of the warehouse. One client's system showed more than 8,000 drill bits in inventory when only 1,044 existed. Fixing that meant fixing the software feeding the data, not just the reports reading it. Once repair tracking ran on rules instead of hand-typed numbers, the data was finally good enough to forecast on.
Built to run without babysitting
We build event-driven pipelines with validation, logging and alerting, so a bad load gets flagged instead of flowing quietly into a report. We build them in the cloud your business already uses, and we run them alongside your internal team rather than around it.
How the work runs
1Inventory the sources
We map where the data lives, how each system keys and updates it, and which source is the system of record.
2Design the model
We design the warehouse or platform around the questions the business needs to answer.
3Build validated pipelines
Each load is validated against its source and transformed by rules you can read and audit.
4Monitor and alert
Failed or unusual loads are flagged to a clear owner, so problems surface before they reach a report.
5Hand off and extend
We document the pipelines and the model so new sources can be added without starting over.
What you leave with
A source inventory and system-of-record decisions
A data model and warehouse designed around your business questions
Validated, automated pipelines from each source
Monitoring, logging and alerts on every load
Documentation your team can extend
Selected work
One Platform, Every Vendor: Rebuilding How Wealth Data Moves
How SEQTEK gave a major U.S. regional financial services company's wealth management systems a single, governed way to talk to each other, replacing years of one-off connections with a reusable integration layer.
From the Wild West to End-to-End
How SEQTEK rebuilt Taurex's repair process, and gave the business data it could finally forecast on.
Honest answers
Our data lives in a dozen systems that do not agree. Where do you start?
With a reliable way to tie records together across systems, then validation by source before anything is trusted. The work is careful, and it is the part that makes everything built on top of it trustworthy.
Do we need a data warehouse?
Not always. If a few systems need to share data reliably, a well-built integration may be enough. If you need to analyze across the whole business and over time, a warehouse usually pays for itself. We will recommend the smaller answer when it does the job.
Which platforms do you work with?
We work where your data already lives, including AWS, Azure and SQL Server, and we fit the tools to the problem rather than selling you a migration you do not need.
Get the business on one set of numbers
Tell us where the data disagrees. We will tell you what it takes to fix it at the source.