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DAMA Maturity Scan

DAMA Maturity Scan

How mature is your data management?

Rate your organisation across the eleven DAMA knowledge areas and receive a detailed report with your score per area and the three areas where targeted improvements add the most value.

Do you have 3 minutes or 6? In the longer version you also share your main challenges, so a follow-up conversation is more focused.

Rate your organisation honestly: there are no right or wrong answers.

Data Governance

How mature is your organisation's Data Governance?

How mature is your organisation's Data Governance? No formal governance structure exists; data is managed ad hoc. Some governance roles exist but are informal or inconsistently applied. Governance roles and policies are partially documented but adoption is inconsistent across teams. Governance framework is defined and documented with assigned data owners/stewards. Governance framework is actively monitored with data stewardship programs and performance metrics tracked regularly. Governance is embedded organization-wide with active steering committees and KPIs.

Data Quality

How mature is your organisation's Data Quality management?

How mature is your organisation's Data Quality management? No formal data quality processes; errors are fixed reactively. Some data quality checks exist but are manual, inconsistent, or siloed by team. Data quality rules are defined, measured, and tracked with scorecards or KPIs. Data quality is proactively managed, automated, and continuously improved organization-wide.

Data Architecture

How mature is your organisation's Data Architecture management?

How mature is your organisation's Data Architecture management? No enterprise data architecture exists; systems are built ad hoc. Some architectural standards exist but are not consistently applied or documented. Enterprise data architecture is defined with data models, standards, and integration guidelines. Data architecture is actively governed, reviewed, and aligned with business strategy enterprise-wide.

Metadata Management

How mature is your organisation's Metadata Management?

How mature is your organisation's Metadata Management? No metadata management exists; data definitions are undocumented or siloed. Some business terms are documented but no central catalog or lineage tracking exists. A business glossary and data catalog exist and are actively maintained. Metadata is fully governed with automated lineage, impact analysis, and trusted data catalog.

Data Security & Privacy

How mature is your organisation's Data Security & Privacy management?

How mature is your organisation's Data Security & Privacy management? No data security policies exist; access controls are ad hoc and undocumented. Basic security measures exist but lack consistency; no formal data classification. Data classification and access controls are formally defined and regularly reviewed. Data privacy and security is embedded in all processes with automated monitoring and GDPR compliance.

Reference & Master Data

How mature is your organisation's Reference & Master Data Management?

How mature is your organisation's Reference & Master Data Management? No master data management; duplicate and conflicting records across systems. Some master data is identified but no formal MDM program or golden records exist. MDM program is in place with defined golden records and reference data management. Master data is fully governed, synchronized across all systems, with automated matching and reconciliation.

Data Warehousing & BI

How mature is your organisation's Data Warehousing & Business Intelligence?

How mature is your organisation's Data Warehousing & Business Intelligence? No centralized reporting; each team builds their own reports manually. Some BI tools are used but data is siloed; no enterprise data warehouse. A centralized data warehouse exists with standardized reports and dashboards. BI is fully integrated, self-service enabled, with real-time analytics and governed data products.

Data Integration & Interoperability

How mature is your organisation's Data Integration & Interoperability?

How mature is your organisation's Data Integration & Interoperability? No integration strategy; data is copied manually between systems. Some ETL processes exist but are fragile, undocumented, or one-off solutions. Integration architecture is defined with reusable APIs and managed data pipelines. Data integration is fully automated and event-driven across all systems enterprise-wide.

Data Modeling & Design

How mature is your organisation's Data Modeling & Design?

How mature is your organisation's Data Modeling & Design? No data models exist; database design is undocumented and inconsistent. Some data models exist but are not standardized or maintained across teams. Enterprise data models are defined, version-controlled, and reviewed for quality. Data modeling is integrated into SDLC with auto-generated, governed, and ontology-aligned models.

Document & Content Management

How mature is your organisation's Document & Content Management?

How mature is your organisation's Document & Content Management? No document management; files are scattered across drives and email with no version control. Basic document storage exists but lacks taxonomy, retention policies, or governance. Document management system exists with defined taxonomy, retention policies, and access controls. Content is fully managed with automated classification, records management, and compliance controls.

Data Storage & Operations

How mature is your organisation's Data Storage & Operations?

How mature is your organisation's Data Storage & Operations? No formal database management; data is stored ad hoc with no lifecycle policies. Databases exist but lack performance tuning, backup policies, or documented procedures. Some database standards and backup procedures exist but are inconsistently applied across systems. Database operations are formally managed with defined SLAs, monitoring, and data lifecycle policies. Database operations are monitored with performance metrics, capacity planning, and proactive issue resolution in place. Data storage is optimized, automated, and self-healing with cloud-native capabilities and zero data loss.

Which DAMA knowledge areas are the highest priority for improvement in your organisation?

Select all that apply. We combine this with your scores to determine your three focus areas.

Which DAMA knowledge areas are the highest priority for improvement in your organisation? Data Governance Data Quality Data Architecture Metadata Management Data Security & Privacy Reference & Master Data Data Warehousing & BI Data Integration & Interoperability Data Modeling & Design Document & Content Management Data Storage & Operations

Both questions are optional.

What are the primary business challenges your organisation faces today that are driven by data issues? (e.g. reporting delays, poor data quality, compliance risk, lack of data trust)

What tools or platforms does your organisation currently use to support data management?

Where should we send your report?

You will receive the full report by email. We use your details only for this and, if you wish, to get in touch.

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Your full report is on its way to the email address you provided. Below is a short preview.

Your overall maturity

-

Level: -

Ad hoc

Developing

Defined

Managed

Optimised

Where you sit on the DAMA maturity ladder, from ad hoc to optimised.

The full report contains your score per knowledge area and the three areas where targeted improvements add the most value.

Data Management & Governance consultancy in the Netherlands. DAMA DMBoK framework. Qlik, Snowflake and erwin by Quest partner.

Approach

Our approach (DAMA)
What is the DAMA wheel?
DAMA maturity assessment
DAMA DMBoK explained

Solutions

AI & Data Readiness
Data Governance
Data Integration
Data Migration
Master Data Management
Data Architecture

Technology

Qlik
Snowflake
erwin by Quest

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