Home Data Confidence Data Warehouse & BI Testing
Data Confidence · 02
Data Warehouse & BI Testing
End-to-end assurance of your analytics stack. We prove that what lands in the warehouse is complete and accurate, that business logic transforms it correctly, and that every dashboard the business reads reflects the truth.
Overview
Prove every dashboard the business reads is telling the truth
Data Warehouse and BI Testing is independent assurance across your whole analytics stack, from the source systems that feed the warehouse to the dashboards leadership reads each morning. We prove that what lands in the warehouse is complete and accurate, that business logic transforms it correctly, and that every report reflects the underlying truth. It is built for regulated and high-growth organisations where decisions rest on the numbers, and where a single unnoticed transformation error can quietly send a whole quarter’s reporting off course.
Most analytics problems are not visible until someone challenges a figure in a board pack and no one can say where it came from. Baknet stands behind all of it as one partner covering security, data assurance, software QA and people, so the question of who owns a data defect never bounces between teams. Our method is evidence-led: each finding reproducible, each fix verified, one retest round included and daily updates as we go. As an organisation certified to ISO/IEC 27001 and ISO 9001, we hold our own testing to the same standard of rigour we ask of your estate.
What it includes
Four capabilities, one accountable service
Source-to-Warehouse Validation
We reconcile source systems against warehouse tables to prove completeness and accuracy, so nothing is dropped, duplicated or silently altered on the way in. Row counts, control totals and field-level comparisons confirm the warehouse is a faithful copy of the systems that feed it, and where gaps appear we trace them back to the exact load or mapping at fault.
Transformation and Aggregation Checks
Business logic is where correct data turns into incorrect answers. We validate calculations and aggregations across fact and dimension tables, checking that every derived measure, join and roll-up behaves as the business intends. Each rule is expressed as a repeatable check rather than a one-time spot inspection, so the same logic can be reverified after any change.
OLAP and Semantic Model Testing
Cubes, measures and hierarchies sit between the warehouse and the people using it, and errors here reach everyone. We verify semantic models for analytical correctness: that measures sum the way they should, that hierarchies drill cleanly, and that the same question returns the same answer wherever it is asked.
BI and Report Validation
We give assurance that dashboards and reports reflect correct, consistent data from the warehouse. We check headline figures against validated sources, confirm filters and date logic behave predictably, and make sure two reports built on the same data cannot disagree. The result is a reporting layer the business can quote with confidence.
How we deliver
A disciplined path from source to dashboard
We map the landscape, design reusable checks, execute layer by layer and report with evidence, capturing findings and confirming fixes at every step.
01
Map the Landscape
We map sources, models, mappings and the BI layer, agreeing the critical data elements and thresholds that matter most to your business.
02
Design Reusable Checks
We build reconciliation, business-rule and aggregation test cases as SQL and tooling assets that live on after the engagement.
03
Execute Layer by Layer
We validate source-to-warehouse movement, transformations, semantic models and reports, capturing evidence at every step.
04
Score and Report
Quality scorecards, variance extracts and root-caused defects routed to accountable owners, with daily updates and one retest round included so verified fixes are confirmed, not assumed.
It is the same disciplined path we use across the practice. See how we work on How We Engage.
Why it pays off
Why Data Warehouse & BI Testing pays off
Decisions You Can Trust
Executives act on dashboards proven to match source-system truth, which ends the recurring argument over whose number is right. Every figure traces back to a validated source, so leadership can commit without hedging on the data beneath the decision.
Analytics Credibility Restored
Independent validation rebuilds business trust in the warehouse and BI estate. Teams that drifted into keeping their own spreadsheets come back to the shared platform once they can see its outputs stand up to scrutiny.
Regression-Safe Releases
Reusable check suites catch breakages every time models or pipelines change. Regressions surface before they reach production, so a routine change never quietly corrupts the reports the business depends on.
Faster Insight Delivery
With validation running on every release, data teams ship changes confidently instead of firefighting report discrepancies after the fact, spending their time building new analytics rather than defending old numbers.
Every report the business reads becomes a report the business can trust.
What you receive on every engagement
Daily Progress Updates
Quality Scorecards
Reproducible Evidence
One Included Retest
Questions, answered
Frequently asked
Which warehouse and BI platforms do you test?
The approach is platform-agnostic, covering modern cloud warehouses, traditional databases and every mainstream BI layer. Checks are built as reusable SQL and tooling assets against your specific stack, so nothing depends on a single vendor’s technology.
Do we need to give you production access?
Read-only access to the layers in scope is sufficient. We agree exactly what is needed during discovery, alongside the critical data elements and thresholds, so access stays minimal and appropriate to the work.
What happens to the test assets after the engagement?
They are yours. The reusable reconciliation and rule suites remain with your team, so every future release can be regression-checked long after we have finished.
Can you work alongside our existing data engineers?
Yes. We operate as an independent assurance layer, giving your engineers reproducible findings and verified fixes they can act on directly, without duplicating or disrupting their work.
How does an engagement begin, and what do you need from us?
We start with a short discovery to map your sources, models and BI layer and to agree the critical data elements that matter most. From you we need read-only access to the layers in scope and a point of contact who understands the estate. Everything else, the checks and the evidence, we build.
What are critical data elements and thresholds?
Critical data elements are the fields and measures the business genuinely relies on, the figures that reach board packs and regulatory returns. Thresholds define how much variance, if any, is acceptable before a check is treated as failed. Agreeing both up front keeps testing focused on what matters rather than checking everything indiscriminately.
How do you handle confidentiality and data security?
We work under NDA and to the controls of an organisation certified to ISO/IEC 27001 and ISO 9001. Access is read-only and scoped to the layers under test, and we favour working against non-production or masked data wherever it is available. Evidence is handled and stored in line with your own data-handling requirements.
What deliverables do we receive?
You receive quality scorecards, the results of every executed check, variance extracts and root-caused defects routed to the accountable owners. Daily progress updates run throughout, and one retest round is included so verified fixes are confirmed rather than assumed. The reusable test assets remain with your team afterwards.
How is the work priced?
Engagements are scoped to your stack and your critical data elements, so pricing reflects the layers in scope and the depth of checking agreed. We return a clear, obligation-free proposal after discovery rather than quoting a figure blind. Because checks are built as SQL and tooling assets you keep, there are no per-seat tool licences to buy.
Also in Data Confidence: Data Migration Testing · Data Quality & Validation · Data Advisory & Strategy · Data Pipelines & Continuous QA
Ready to trust your reporting again?
Share your context and constraints and we will return a clear, evidence-driven proposal, scoped to your stack and your critical data elements, with no obligation.