The CMARIX team provides enterprise data governance consulting services to Chief Data Officers, risk officers, and data platform stewards who need more than a governance policy document. Our services include the implementation of frameworks, tools, and processes that ensure the quality of data, control access to data, provide lineage from source to use, and keep you compliant, making all your decisions and AI models based on trustworthy data.
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CMARIX offers data governance services encompassing strategic planning, data quality management, master data management, cataloging, data security, operating model design, platform implementation, AI governance, and adoption. Each project is uniquely designed in accordance with your level of governance maturity, your regulatory requirements, and the consumers of your data.
A governance program built on where your organization actually is today.
Our process involves analyzing your current data governance maturity on five different fronts: data quality, data lineage, access controls, data cataloging, and data privacy. After this, we create a target-state data governance framework by selecting the appropriate toolset and operational approach based on your organization's size and regulations, while delivering a roadmap and milestones for successful implementation. Governance is an integral part of the strategic process, and that is why we align it with our data strategy consulting services.
Approach: DAMA-DMBOK Assessment | Maturity Scorecard | Framework Design | Roadmap | Tool
Data your analysts and models can depend on, enforced at the platform level.
We assess your data assets for completeness, accuracy, consistency, timeliness, and uniqueness; then put automated quality policies, anomaly detection, and freshness validation based on SLAs into place, which execute as part of every pipeline run. Quality problems become apparent before the data gets to the dashboard or model – not after a stakeholder complains about the discrepancy. Learn more about data engineering services here.
Approach: Great Expectations | Soda | dbt Tests | Monte Carlo | Anomalo | OpenMetadata | Grafana Alerting
A searchable, trusted catalog that makes governance visible to every data consumer.
We help you build and populate enterprise data catalogs that include technical metadata, glossary terms, owners, lineage, tags, and quality scores for each of your data assets. A well-kept data catalog helps analysts get insights faster, enforces policies at scale, and provides the lineage evidence needed for audits.
Approach: Collibra | Alation | Atlan | Microsoft Purview | DataHub | Apache Atlas | OpenMetadata | dbt Docs
One authoritative version of your most critical data entities.
We offer MDM solutions that create a unified view of customers, products, suppliers, employees, and accounts, avoiding the inaccuracies that lead to revenue leakage, regulatory risks, and flawed analyses. All MDM deployments include stewardship processes, match-merge rule development, golden record testing, and reconciliation back to the source systems. Governance is applied throughout all data sources, and our data integration services consolidate them through a single rule set.
Approach: Informatica MDM | Reltio | Stibo STEP | Semarchy | Boomi | MuleSoft | dbt | Custom Python
Access controls, privacy enforcement, and audit evidence built into the data platform.
Column-level security, row-level filtering, dynamic data masking, PII identification, data retention, and deletion are implemented to meet GDPR, HIPAA, CCPA, and financial services regulation requirements. All security policies operate at the platform level, not the application level, and so apply irrespective of access. Governing data and governing models should go together; this is part of our machine learning operations (MLOps) consultation services.
Approach: Microsoft Purview | Collibra DQ | AWS Macie | HashiCorp Vault | OPA | dbt Masking | Databricks Unity Catalog
The organizational structure that makes governance sustainable without us.
We design the data council structure, stewardship role definitions, domain ownership assignments, escalation paths, and decision rights that govern how your organization manages data across business units and systems. A governance operating model without the right organizational structure fails when the initial project team moves on. We build the model for long-term sustainability.
Approach: Data Council Design | Stewardship Role Framework | RACI Matrix | Decision Rights | Adoption Plan
Govern the data that trains your models as rigorously as the models themselves.
For AI and ML use cases, governance mechanisms specific to them are put in place: Training Data Set Versioning, Bias & Fairness Auditing, Feature Lineage Tracking, Model Cards, and Data Quality Gate, where model training cannot proceed if the input data does not meet certain quality criteria. It is as reliable as the data that was used for its training.
Approach: DVC | MLflow | OpenLineage | Great Expectations | Evidently AI | Collibra AI Governance | Arize AI
Governance that your data consumers understand and your data producers follow.
We design and deliver data literacy programs, stewardship training, governance tool onboarding, and business glossary workshops that build the organizational understanding needed for a governance program to generate lasting value. Policies and tools that nobody uses are not governance; they are documentation.
Approach: Training Curriculum Design | Stewardship Workshops | Business Glossary Facilitation | Adoption Metrics | Change Management
CMARIX aligns every data governance consulting engagement to established industry frameworks rather than proprietary methodologies, so your program can be maintained, audited, and extended by any qualified practitioner after the engagement closes.
The universally accepted body of knowledge for data management. CMARIX bases its governance programs on the 11 DMBOK knowledge areas in respect of data quality, data lineage, data security, data architecture, and data stewardship.
Data Capability Assessment Model is adopted by financial institutions to design their data governance framework with respect to regulatory requirements. CMARIX adopts the approach of DCAM framework in cases of BCBS 239, Basel IV, and their equivalents.
In cases where the areas of data governance and cybersecurity risk management overlap for organizations, CMARIX integrates data access and classification frameworks to NIST SP 800-53 and FAIR quantitative risk principles.
A structured, milestone-gated process that moves from maturity assessment to an operational governance program, with working deliverables at every stage and no big-bang policy launches that never get adopted.
Our analysis of your current governance maturity level is done by evaluating aspects such as data quality, lineage, access, cataloging, privacy, and stewardship, scoring them against industry benchmarks, and pinpointing the areas where there is high risk from both a regulatory and an operational perspective.
Timeline: Week 1-2
Deliverables: Maturity scorecard · Data asset inventory · Stakeholder map · Regulatory obligation register · Gap analysis
We develop the target-state governance structure based on DAMA-DMBOK and your regulatory requirements, select the catalog, quality, lineage, and MDM tools compatible with your technology environment, and develop a phased implementation roadmap with accountability measures.
Timeline: Week 2-4
Deliverables: Governance framework blueprint · Operating model design · Tool selection matrix · TCO model · Roadmap
Governance controls are implemented for one of the critical data domains, usually customer, product, or finance data, to prove value, test the operational model, and uncover any resistance issues. The pilot provides an operationalized reference model that your team can replicate in other domains.
Timeline: Week 4-10
Deliverables: Pilot domain catalog · Quality rules · Lineage documentation · Access controls · Stewardship workflows
These governance tools will be applied to your data platform via catalog population, configuration of quality monitors, creation of the lineage graph, access control, and the creation of golden records for master data. Policies are put in place at the platform layer level, rather than simply documented.
Timeline: Week 8-16
Deliverables: Catalog population · Quality test suite · Lineage graph · Access control configuration · MDM golden records
Data council has been created, governance accountability has been established on a per-domain basis, and escalation and problem-solving workflows have been developed. Data literacy and data stewardship education/training programs have been developed. Governance technologies without an operating model end up being shelfware.
Timeline: Week 12-18
Deliverables: Data council charter · Stewardship role assignments · Escalation workflows · Training delivery · Adoption baseline
Trends in governance and data quality implementation are measured each month. Governance involves covering new data areas according to a predetermined schedule, and policies and controls are adjusted based on changes in regulations. Governance is a process that never stops, and this is how we practice it.
Timeline: Ongoing
Deliverables: Monthly governance health reports · Quality trend reports · Domain expansion plan · Regulatory update reviews
CMARIX selects governance tooling based on your existing data platform, catalog maturity, regulatory requirements, and the organization's capacity to adopt and maintain the tooling after implementation.
CMARIX is a reputable data governance firm for regulated and data-intensive sectors, providing governance programs that meet the specific data management needs of each industry's regulatory framework.
Healthcare organizations manage sensitive patient information across EHRs, imaging platforms, claims systems, laboratories, and clinical applications. CMARIX builds data governance frameworks covering PHI classification, role-based access controls, audit logging, data retention, consent management, and data quality. Governance policies are applied across distributed healthcare environments to maintain secure and accountable data usage. These frameworks establish clear ownership, improve data discoverability, support regulatory requirements, and create trusted foundations for clinical analytics, AI, and healthcare applications.
Dive Into More
CMARIX delivers strategy-to-implementation governance expertise backed by deep data platform and governance tooling experience. Through operating model design, stewardship enablement, and ongoing governance and adoption support, organizations build governance programs that remain effective, scalable, and embedded across business and technical teams.
Governance Programs Implemented
In-House Data & Platform Engineers
Client Retention Rate
Regulated Industries Served
CMARIX structures data governance consulting services engagements to match your governance maturity and organizational readiness, from a targeted assessment to a fully operational enterprise governance program.
A structured maturity assessment across data quality, lineage, cataloging, access control, and stewardship. Deliverables include a scored gap analysis, regulatory obligation mapping, tool recommendations, and a phased implementation roadmap.
What you get:
A dedicated team of data governance consultants, catalog engineers, data quality specialists, and MDM architects designs, builds, and activates your governance program across priority data domains with full operating model setup.
What you get:
CMARIX operates as an extension of your data governance function: catalog maintenance, stewardship support, quality monitoring, regulatory update reviews, domain expansion, and monthly governance health reporting.
What you get:
A governance assessment and roadmap engagement runs USD 10,000 to USD 20,000 over 3 to 4 weeks. A full governance program implementation runs USD 50,000 to USD 150,000 over 3 to 6 months, depending on the number of data domains, catalog tooling selected, and operating model complexity. Ongoing governance operations retainers run USD 6,000 to USD 18,000 per month.
A pilot domain implementation delivering a working catalog, quality framework, and stewardship model for one data domain typically takes 8 to 12 weeks. A full enterprise governance program covering multiple domains, MDM, and a complete operating model takes 3 to 6 months. CMARIX uses a pilot-first approach so your organization can see working governance before committing to a full-scale rollout.
Data management is the broad set of practices that covers how an organization collects, stores, processes, and uses data. Data governance is the organizational authority and control layer within data management: the policies, roles, processes, and tools that ensure data is handled consistently and accountably. CMARIX builds governance programs that work alongside your existing data management infrastructure, not as a replacement for it.
A data catalog refers to a searchable list of your organization's data assets, augmented with contextual information such as ownership details, glossary descriptions, lineage, quality metrics, and access controls. This tool makes governance transparent for all data consumers, empowers your stewards to enforce policies at scale, and provides auditors with lineage information. CMARIX deploys data catalogs using Collibra, Alation, Atlan, and Microsoft Purview.
Master data management (MDM) establishes a single, authoritative record for your most critical shared data entities: customers, products, suppliers, employees, and accounts. It is a core component of data governance because inconsistent master data is the root cause of many data quality, regulatory, and analytical problems. CMARIX implements MDM as part of governance programs on Informatica, Reltio, Stibo, and Semarchy platforms.
The following governance policies come into effect through AI models: training data lineage, audits for bias and fairness, feature quality, and model card documentation. CMARIX offers AI data governance structures that use the same quality, lineage, and access policies that any important data element in the enterprise uses for ML training data.
CMARIX matches up governance programs with the DAMA-DMBOK and DCAM frameworks, choosing the pertinent knowledge areas and capability dimensions based on your maturity and regulatory environment. CMARIX practitioners hold the CDMP and DCAM certifications. We don’t force an approach that can no longer be supported after the engagement period.
Governance initiatives usually fail due to a lack of connections between policy and platform controls, lack of accountability within stewardship roles, and non-adoption of tooling. At CMARIX, we ensure that each governance policy has a platform control, an operating model with ownership and escalation processes, pilot implementation of domains prior to scale-up, and data literacy training for the stewards and consumers who will use the governance initiative on a day-to-day basis.
Your unique concepts will be crafted into a remarkable end result by our team.
