Strategy · Service 01

Data Strategy.

An actionable data and analytics strategy aligned to your commercial priorities — covering people, process and technology, with a costed, phased roadmap your board will back.

2 wks
Strategy Workshop sprint
12 mo
Typical roadmap horizon
100+
Organisations advised
Vendor-independent
Tooling guidance
Overview

Strategy first. Technology second.

The most common failure mode we fix: organisations that have bought technology before deciding what problem they're solving. A data strategy built around a vendor pitch is not a strategy — it's a procurement decision dressed up.

We start with your commercial objectives, map the data and capability gaps that stand between you and them, then design a target state and a delivery roadmap that is proportional to your size, your risk appetite, and your actual budget.

Where we help.

01

Current-state audit

Data assets, quality, lineage, tooling, team capability — an honest baseline.

02

Target operating model

How data will be owned, governed, and consumed across your organisation.

03

Technology roadmap

Platform, tooling and architecture choices — vendor-independent, costed, sequenced.

04

AI & analytics strategy

Use-case identification, prioritisation, and the data foundations each use case requires.

05

Governance design

Right-sized policies, data ownership, and accountability structures.

06

Business case

Value model linking data investments to measurable commercial outcomes.

How we work

Discover, design, plan.

1
Weeks 1–2

Discovery

Stakeholder interviews, data landscape review, commercial priority mapping.

2
Weeks 3–4

Current state

Capability assessment, gap analysis, risk and opportunity identification.

3
Weeks 5–6

Target state design

Operating model, architecture principles, tooling recommendations.

4
Week 7–8

Roadmap & business case

Prioritised 12-month plan with named owners, costs and success metrics.

Deliverables

  • Data strategy documentBoard-ready, 20–30 pages, with executive summary.
  • Current-state assessmentMaturity scoring, gap analysis, risk register.
  • Target architectureLogical data architecture and technology stack.
  • Delivery roadmapCosted, phased, with named owners and dependencies.
  • Business caseValue model, ROI estimates, investment profile.
  • Governance starter packData ownership RACI, policy templates, forum cadence.
Technology

Tools & frameworks we use.

Data Maturity Modelling
DAMA-DMBOK
Zachman Framework
TOGAF
Microsoft Fabric
Databricks
Snowflake
dbt
Power BI
Looker
In production

A real engagement.

Case study

Housing association — 12-month data strategy delivering measurable ROI.

Current-state audit and 12-month data strategy covering platform consolidation, governance and three priority AI use cases. Board approved £1.2m investment programme within six weeks of delivery.

Read full case study
£1.2m
Board-approved investment
6 wks
Board approval timeline
3
Priority AI use cases identified
8 wks
Strategy to roadmap
FAQ

Common questions.

How long does a data strategy take?+
Our standard engagement is 8 weeks from kickoff to final roadmap. We also offer a 2-week accelerated sprint using our Data Strategy Workshop product.
Do you recommend specific platforms?+
No. We are vendor-independent. We assess your situation and recommend the best fit — sometimes that's Microsoft Fabric, sometimes Snowflake, sometimes staying with what you have.
What if we already have a strategy?+
We can review and stress-test it, identify gaps, and update the roadmap rather than start from scratch. A strategy refresh typically takes 3–4 weeks.
How do you handle buy-in across departments?+
We run stakeholder workshops at the start and a readout session at the end. The roadmap document is designed to be presented at board and ExCo, not just handed to the data team.
Ready when you are

Put your data to work.

Book a free 30-minute consultation with a senior Databuzz consultant.