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Data Strategy and Governance

Treat data as a managed asset, with owners, standards and measurable quality.

A data strategy says which data matters, who owns it, how good it must be and how it will be used. Governance makes that real in daily operations without turning into bureaucracy.

We align with DAMA-DMBOK and, for Saudi entities, the NDMO data management and personal data protection standards, and size the programme to what your organisation can run.

What is included

Service offerings

02.1

Data strategy

Link data priorities to business strategy and AI ambitions.

  • Data vision and principles
  • Priority domains and use cases
  • Roadmap and investment case

02.2

Governance operating model

Domains, owners, stewards and a council with clear decision rights.

  • Operating model
  • RACI and decision rights
  • Policies and standards

02.3

Maturity and compliance assessment

Baseline against DAMA-DMBOK, NDMO or sector requirements.

  • Maturity scores by area
  • Gap analysis
  • Prioritised remediation plan

02.4

Master and reference data

One trusted version of customers, products, suppliers and codes.

  • MDM strategy
  • Data models and matching rules
  • Stewardship processes

02.5

Data quality management

Rules, monitoring and issue resolution for critical data.

  • Critical data elements
  • Quality rules and scorecards
  • Issue workflow

02.6

Privacy and classification

Classify data and meet PDPL and sector obligations by design.

  • Classification scheme
  • Privacy controls
  • Records of processing

When to call us

Signs you need this

  • Regulators or auditors ask for evidence you cannot easily produce.
  • Different reports show different numbers for the same thing.
  • AI or analytics projects stall on data quality.
  • An NDMO or PDPL deadline is approaching.

Approach

How we work

  1. 01Assess

    Baseline maturity and identify the critical data elements.

  2. 02Design

    Operating model, policies and standards scaled to your organisation.

  3. 03Embed

    Implement controls in platforms and stewardship in daily work.

  4. 04Measure

    Track quality, coverage and compliance like any operational metric.

Standards and frameworks

Aligned with recognised practice

  • DAMA-DMBOK (2nd edition, revised 2024)
  • NDMO Data Management and Personal Data Protection Standards (KSA)
  • Saudi Personal Data Protection Law (PDPL)
  • UAE Personal Data Protection Law (Federal Decree-Law 45/2021)
  • ISO 8000 (data quality)

Solutions

Where this service is applied

Data foundations

Data Quality and Governance Systems

Governance that runs in the systems, not in the slide deck.

View solution Data foundations

Modern Data Platforms

One governed platform for analytics and AI, designed for your scale and your region.

View solution Decision intelligence

Decision Intelligence Platforms

Connect the data, the analysis and the action behind your most important decisions.

View solution

Technology

Platforms we work with

Vendor-neutral: examples of platforms commonly used in this service. Names identify technologies only and do not imply a partnership.

  • Microsoft Purview
  • Collibra
  • Alation
  • Informatica
  • Atlan
  • Ataccama
  • OneTrust
  • BigID
See the full technology ecosystem →

Insights

Further reading

Trusted Data for Enterprise AI

Enterprise AI rarely fails at the model. It fails on data nobody certified for the job. The fix is not a clean-everything program but trusted data, earned one use case at a time.

Read →

Governance Without Bureaucracy

Governance that lives in committees grows with the number of meetings. Governance that lives in pipelines grows with the data. Most programs fail because they chose the first and expected the results of the second.

Read →

Implementing NDMO With DAMA-DMBOK

The NDMO standards tell you what must be true. DAMA-DMBOK tells you how to make it true. Entities that confuse the two end up with 191 documents and very little managed data.

Read →

Master and Reference Data

A single version of the truth is not found by software. It is decided, attribute by attribute, by people with authority to decide. MDM technology only executes those decisions, and fails when nobody has made them.

Read →

Talk to us about Data Strategy and Governance

Engage this service on its own or as part of a solution. We will agree scope, outcomes and the right team with you.

Start a conversation

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