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Data Advisory & Strategy
Strategic guidance that connects data quality to business priorities. We assess your risks and readiness, define the testing strategy, establish ownership and chart a pragmatic path to automation and observability.
Overview
Turn data quality from a recurring headache into a governed, funded programme
Most data problems are not really tooling problems. They persist because no one owns the critical datasets, effort is spread evenly across data that carries very different consequences, and there is no agreed sequence for what gets fixed first. Baknet Data Advisory & Strategy puts one accountable partner behind security, data assurance, software QA and people, so the plan you leave with connects data quality to the outcomes your leadership already cares about.
We assess your risks and readiness, define a testing strategy aligned to your priorities, establish ownership that holds, and chart a pragmatic path to automation and observability. The work is led by certified, senior practitioners, and it sits inside a consultancy certified to ISO/IEC 27001 and ISO 9001, so the way we handle your information and run the engagement is held to a documented standard. You get a defensible view of data risk, not a shelf of unread recommendations.
What it includes
What it includes
Risk and readiness assessment
We identify data risks across your platforms, pipelines and the downstream reporting layers that leadership actually reads. Rather than auditing everything to the same depth, we find where a failure would hurt most, in revenue, in regulatory exposure or in decisions taken on wrong numbers. That map becomes the spine of everything that follows.
Data testing and quality strategy
We define a testing approach that matches your business priorities and your current data maturity, not a generic maturity ladder borrowed from someone else’s estate. The strategy sequences work by consequence, so the first things tested are the things that matter, and it stays realistic about the skills and capacity you have today.
Governance and ownership model
We define data ownership, a clear RACI and end-to-end quality accountability, so every critical dataset has a named owner. This is the part that ends the cycle of unowned data, where defects drift between teams because raising them is nobody’s job. When issues have an owner, they get assigned and resolved instead of quietly persisting.
Automation and observability roadmap
We produce a phased adoption plan for test automation and continuous production monitoring. It is built to deliver value at each step rather than as one large programme that stalls before anything ships, which means momentum and confidence build as you go.
How we deliver
How we deliver
Every engagement follows a clear line from evidence to plan, and you are never guessing where it stands. Findings are reproducible, recommendations are traceable to what we saw, and you receive daily progress updates so the work is visible day by day.
01
Assess risk and maturity
Map data risks across platforms, pipelines and reporting, and benchmark where your quality practice sits now.
02
Define the strategy
A testing and quality approach sequenced by business priority rather than technical convenience.
03
Establish ownership
A RACI and governance model that makes data quality a specific person’s job from end to end.
04
Roadmap the automation
A phased, realistic plan for adopting test automation and production observability at a pace your teams can absorb.
It is the same disciplined path we use across the practice. See how we work on How We Engage.
Business value
Why it pays off
You invest where it matters
Quality effort targets the data that drives revenue, risk and regulatory exposure first. Scarce testing capacity goes where failure would cost the most, instead of being spread thinly across data that carries little consequence.
Accountability that sticks
Clear ownership and a working RACI break the pattern of unowned data. With a named owner behind every critical dataset, issues get raised, assigned and resolved rather than passed between teams.
A credible automation path
A phased roadmap avoids the big-bang tooling project that consumes budget and delivers nothing until the very end. Value lands at each phase, so the organisation gains confidence as it goes.
Risk visibility for leadership
You get a defensible view of data risk across the estate, expressed in business language. Leaders can weigh data exposure against every other risk they manage and direct investment knowing exactly what is at stake.
A data quality programme with strategy, owners and momentum.
What you receive on every engagement
Daily Progress Updates
Detailed Data Quality Reports
Results of Executed Checks
One Included Retest
Questions, answered
Frequently asked
We already have data tools. Why do we need strategy?
Tooling without ownership and sequencing is where most data quality programmes stall. Strategy connects the tools you already own to the risks that matter and to the people accountable for them, so the investment you have made starts to pay back.
How long does an advisory engagement run?
A focused risk and maturity assessment typically lands within weeks. The strategy, governance model and roadmap follow as agreed deliverables on a defined timeline, so you know what arrives and when.
Who inside our organisation needs to be involved?
Data platform owners, the teams producing and consuming your critical data, and a leadership sponsor. The governance model we deliver makes those roles explicit from that point on.
How does advisory connect to the rest of our data assurance?
The strategy sets the direction that hands-on services then execute, from validation through to continuous QA in your pipelines. We can carry the plan into delivery or hand it to your teams, whichever suits.
What do we receive at the end of the engagement?
You receive a documented risk and maturity assessment, a testing and quality strategy sequenced by business priority, a governance and ownership model with a clear RACI, and a phased automation and observability roadmap. Each deliverable is written to be used by your teams, not filed away.
How do you handle the confidentiality of our data and findings?
The engagement sits inside a consultancy certified to ISO/IEC 27001 and ISO 9001, so information handling follows documented controls. We are happy to work under your non-disclosure agreement, and access is limited to the people who need it. Findings are shared with your nominated stakeholders only.
How does this work alongside our in-house data team?
The strategy is built around the skills and capacity you already have, so it complements your team rather than replacing it. Your people stay close to the work throughout, and the governance model names owners inside your organisation so accountability stays with you.
What does an advisory engagement cost?
Pricing is scoped to the size of your estate and the depth of assessment you need, so there is no fixed list price. Once we understand your context and priorities, you receive a clear proposal with defined deliverables and no obligation.
Do you only advise, or can you help deliver the roadmap?
Both options are open to you. We can hand the plan to your teams to run, or carry it into delivery through our data assurance services, from validation through to continuous QA in your pipelines.
Also in Data Confidence: Data Warehouse & BI Testing · Data Migration Testing · Data Quality & Validation · Data Pipelines & Continuous QA
Get a strategy your leadership will fund
Share your context and constraints, and you will receive a clear, evidence-driven proposal for Data Advisory & Strategy, with no obligation.