We assess enterprise data maturity; a data-quality framework with ownership and governance models turns data into a governed asset that feeds decision-making.
The critical topics this service addresses and the outcome we deliver in each.
We document the current state as an evidence record through a 5-level maturity assessment grounded in DAMA-DMBOK and DCAM frameworks.
We define quality indicators across accuracy, completeness, consistency, timeliness, validity and uniqueness with a measurement baseline and acceptance criteria.
Within the contracted scope we deliver a federated governance model, a RACI matrix and a data steward program.
Moving to a higher maturity level is validated through an owner-approved improvement program and review cadence.
How we phase the service across delivery, governance, and connected service pillars.
We first surface the visibility of corporate assets through data inventory and data flow mapping, then clarify the DMBOK-based maturity assessment during discovery.
We define quality rules compatible with Great Expectations and dbt tests in a tool-agnostic way, and tie metadata standards to an Atlas, Collibra and Purview compatible catalog.
We run change management through an ADKAR-based training and communication plan and sustain it with a quarterly governance committee.
Illustrative surfaces where this service is commonly activated.
We make conflicting cross-department reports traceable through quality rules and a single source of truth definition.
We prepare data inventory and classification to form a basis for KVKK compliance work, aligned with auditor and legal review.
We establish data ownership in small and mid-sized teams with a scale-appropriate, lightweight governance framework.
This service's depth on sector-specific technical and compliance topics.
We measure data quality across six dimensions, define thresholds and acceptance criteria for each, and track trends through a dashboard.
A central CDO office provides coordination while department-level data stewards run daily operations; responsibilities are clarified with RACI.
We prepare a maturity report and benchmark across 14 DCAM-based categories with concrete action items for each level.
Organizations accumulate data across siloed systems without a coherent framework to govern quality, ownership, or lifecycle — leading to inconsistent reporting, regulatory exposure, and missed insights. Our Data Strategy & Governance practice establishes enterprise-wide data policies, stewardship models, and maturity roadmaps that transform raw data assets into trusted, governed information. We align data governance with DAMA-DMBOK and GDPR/KVKK compliance requirements from day one.
Improve quality indicators through baselines, acceptance criteria, and reviewed evidence
Make risk, control, and compliance indicators visible through measured targets and evidence records
Improve quality indicators through baselines, acceptance criteria, and reviewed evidence
The engagement covers the full spectrum of enterprise data governance — from initial landscape discovery and stakeholder alignment to policy authoring, tooling implementation, and operating model handover. We embed data stewards within business units and establish a Data Governance Council to sustain the program beyond the initial delivery phase. Ongoing managed services options are available for continuous monitoring, quality scoring, and policy enforcement.
Improve quality indicators through baselines, acceptance criteria, and reviewed evidence
Enable cross-department data sharing with policy-enforced access controls reducing breach risk
Every Data Strategy & Governance engagement produces a structured set of artifacts designed to be actionable immediately and sustainable long-term. Deliverables follow a phased release schedule tied to project milestones, ensuring stakeholders receive value incrementally rather than in a single end-of-project dump. All documentation is authored in Microsoft 365 and version-controlled in the client's repository.
Turn the outcome into a measurable target with baseline, owner, and evidence review cadence
Shorten operational cycle time against agreed measurement targets and acceptance criteria
Hand over a fully operational catalog with trained stewards, requiring no vendor lock-in
Timeline is confirmed during discovery based on scope, integration complexity, current maturity, and acceptance criteria. The project plan is tied to approved scope and dependencies.
Yes. Our governance frameworks are cloud-agnostic by design and integrate natively with Microsoft Purview on Azure, AWS Glue Data Catalog, or Google Dataplex, depending on your existing infrastructure.
Absolutely. Our hybrid governance architecture uses connector-based metadata ingestion to catalog and govern data residing in on-premises SQL Server, SAP, and mainframe systems alongside cloud data platforms without requiring data movement.
The council typically includes a Chief Data Officer (or delegate), domain data owners from each business unit, IT data architects, and a compliance liaison. We facilitate the first 6 quarterly council sessions and provide meeting templates, escalation procedures, and charter documentation.
Yes. Our policy library includes pre-built templates for BFSI (BRSA/Basel IV), healthcare (HIPAA/HL7), and retail/e-commerce verticals. Each template is tailored during workshops to reflect your regulatory jurisdiction, risk appetite, and organizational culture.
We establish a governance health scorecard at project kickoff with agreed KPIs such as data quality index, stewardship coverage ratio, policy compliance rate, and catalog adoption percentage. Baseline measurements are captured in week 2 and progress is tracked against targets at each milestone gate.
This short form routes your request to the right support team. We clarify context first, then define the safe sharing method.
Privacy-aware first contact; safe sharing flow when needed; no sales pressure.
