cimt

Our approach

The DAMA DMBoK framework as foundation under your data

At cimt we use DAMA DMBoK as the internationally recognised framework for all our data management work. No ad-hoc projects — a structured, proven methodology that scales with your organisation, from assessment through ongoing operations.

The DAMA DMBoK (Data Management Body of Knowledge) is the internationally recognised standard for data management, published by the DAMA International association. It describes 11 knowledge areas — from Data Governance and Data Quality to Data Architecture and Metadata Management — and provides a structured way to measure, improve and sustain data management maturity within an organisation. cimt uses DAMA DMBoK as the foundation under every engagement: it makes our approach repeatable, measurable, and compliant with EU AI Act, GDPR and Data Act.

Why a framework

Data management is not a technical problem

It is an organisational problem. Without structure, initiatives stall in ad-hoc fixes that don't scale. DAMA DMBoK provides direction where otherwise there is none.

Repeatability

A proven methodology that works regardless of your organisation's size. No bespoke approach that disappears with the project.

Maturity assessment

Objectively determine where you stand and where the biggest opportunities lie — based on facts, not assumptions.

Roadmap planning

Set priorities based on business impact, not on technology hype.

Compliance base

A solid foundation for EU AI Act, GDPR, Data Act and other regulations.

The 11 knowledge areas

DAMA DMBoK in cimt service delivery

Each knowledge area maps to concrete cimt services, supported by technology from our partners Qlik, Snowflake and erwin by Quest.

DAMA knowledge area cimt service More
Data Governance Data Governance & Data Quality View
Data Quality Data Governance & Data Quality View
Data Integration & Interoperability Data Integration & Streaming View
Reference & Master Data Master Data Management View
Data Architecture Data Architecture & Lakehouse View
Data Modelling & Design erwin Data Modeler View
Data Warehousing & BI Analytics & Insights View
Metadata Management erwin Data Intelligence View
Data Storage & Operations Managed Services View
Data Security Data Governance & Compliance View
Document & Content Management Data Integration & Streaming View

From framework to practice

Four steps, one goal

A framework only matters when it leads to action. That's why we translate the DAMA knowledge areas into a concrete plan for your organisation.

  1. 01

    Assessment

    What we do: Maturity assessment based on the DAMA DMBoK framework

    Outcome: Objective view of your current data maturity

  2. 02

    Roadmap

    What we do: Prioritise based on business goals and quick wins

    Outcome: A concrete action plan with measurable milestones

  3. 03

    Implementation

    What we do: Phased delivery with Qlik, Snowflake and erwin

    Outcome: Working solutions that deliver value directly

  4. 04

    Embed

    What we do: Governance structure, knowledge transfer and managed services

    Outcome: Durable data management that keeps working

See where you stand

Book a maturity assessment

In a no-obligation conversation we map where the biggest opportunities lie — and which steps deliver impact fastest.

Frequently asked

DAMA DMBoK in practice

Do we need DAMA DMBoK if we already have a data team?

A data team benefits more from a shared framework than without one. DAMA DMBoK provides the common language and methodology your own team can use to work structurally, even after external parties leave. It is not extra burden — it makes existing work repeatable and transferable.

How long does a DAMA maturity assessment take?

An assessment typically runs 2 to 4 weeks, depending on organisation size and scope. We evaluate the current state per DAMA knowledge area via interviews, document review and data sampling, and deliver a ranked roadmap with quick wins and long-term priorities.

Does DAMA DMBoK work for smaller organisations?

Yes — especially then. The methodology is scalable: at SME organisations we focus on a handful of knowledge areas with direct business impact (often Data Governance, Data Quality and Data Integration), while at larger organisations we scope all 11 areas. The framework is the same — the application depth scales with you.

How does DAMA DMBoK relate to ITIL, COBIT or TOGAF?

DAMA DMBoK is specific to data management; ITIL covers service management, COBIT IT governance and TOGAF enterprise architecture. They do not exclude each other — DAMA DMBoK fills in the "data layer" under a broader governance model. We align our approach with the frameworks you already use.

What is the difference between DAMA DMBoK v1 and v2 — and which does cimt use?

DMBoK v2 (2017) is the current standard and has been extended with topics like Big Data, Data Science and Data Storage & Operations. cimt works with v2 and tracks the modernisation toward DMBoK v3 — which will explicitly cover AI governance and cloud-native architecture.