Data vision & business alignment
Which business goals require which data? We translate your strategy into concrete data ambitions.
Service · Strategy
Your business model changes faster than your data landscape can follow. A data strategy closes that gap: it connects your business goals to the data, people and technology you need to stay agile. Concrete, prioritised, actionable.
A data strategy is the bridge between your business strategy and your data landscape. It is the overarching layer that gives direction to governance, master data management, architecture and integration, so they no longer run as separate projects but as one coherent whole. cimt structures that strategy per DAMA DMBoK: every ambition maps to a recognisable knowledge area, and the coherence between the parts is assured.
Why now
Business models, and whole industries, are changing at a higher pace than before. More and more new revenue models rely directly on data. Organisations that want to respond need a data landscape that moves with them rather than holding them back. A data strategy makes that agility concrete: it determines which data, which architecture and which decision-making you need to react quickly, and in what order you build it.
The building blocks
Not a weighty report that disappears in a drawer, but a workable whole of direction, priorities and execution.
Which business goals require which data? We translate your strategy into concrete data ambitions.
Where should your data landscape go? A target picture that grows with new business models.
Policy, ownership and data quality as the basis under every data-driven step.
A phased plan that delivers value each quarter, not only after years.
The roles, teams and decision-making that keep the strategy alive.
Measurable indicators, so you steer on results instead of gut feeling.
From strategy to execution
A strategy only delivers value once it is executed. cimt provides both: the direction and the hands to build it. From your data strategy, we take on the underlying disciplines.
Policy, ownership and compliance as the foundation.
One reliable source for your core data.
The technical target picture for your data landscape.
Connecting sources into usable, reliable data flows.
From data to decisions that move the business forward.
A data landscape that is ready for AI applications.
Start with direction
In a short session we bring your business goals and your current data landscape together, and sketch where a data strategy delivers the most.
Frequently asked
A data strategy sets the direction: which business goals require which data, and how you shape your data landscape around them. Data management is carrying out all activities around data: storage, integration, quality, analysis. Data governance is, within that, the policy and processes that determine how data is managed. In short: the strategy picks the destination, governance guards the rules, management does the work.
A first workable data strategy (vision, target architecture and a prioritised roadmap) typically takes 4–8 weeks. After that it is a living document that moves with your business goals. cimt works incrementally: you start with the highest priorities and build out from there.
No. A good data strategy is precisely a phased plan. We start where the business benefits most and expand at the pace your organisation can handle. Big-bang transformations are risky and rarely necessary.
We structure the strategy per DAMA DMBoK, the international framework for data management. That way every ambition maps to a recognisable knowledge area (governance, quality, architecture, master data, and more) and the coherence between the parts is assured.