DSC

Data Governance Consulting

DSC helps companies bring order to their data define data owners and stewards, implement quality rules, catalog key datasets, and ensure compliance, so that teams can trust the numbers in reports and dashboards. Our data governance consulting builds a practical data governance framework around data stewardship, data quality management, data cataloging, and data lineage not a policy document that sits on a shelf.

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Data Governance Challenges We Help Solve

Many organizations struggle with the same governance gaps, even after investing in tools and dashboards. Below are the challenges we most often help clients resolve.

  • There is no clear owner or steward for specific datasets.
  • Different departments calculate the same metrics differently.
  • Systems contain duplicate and conflicting records.
  • The team does not know what data even exists and where it is stored.
  • Reports and dashboards are not trusted due to data quality issues.
  • There are compliance risks (GDPR, CCPA, PIPEDA) due to a lack of access control.
  • Governance is perceived as a purely IT initiative without business involvement and therefore does not take hold.

 

What Our Data Governance Services Include

DSC helps organizations put structure in place for their data so it’s trusted, secure, and easy to manage across teams. Below are the core areas we cover.

Data Governance Framework Design

We help you build a governance operating model that assigns ownership and defines how decisions get made.

  • Defining roles: data owners, stewards, and a governance board
  • Developing data policies and standards
  • Establishing a decision-making and escalation model
  • Alignment with business goals, not just IT

Data Quality Management

We help you control the accuracy and consistency of your data so teams can rely on it.

  • Setting data quality and validation rules
  • Detecting duplicates and gaps
  • Monitoring quality within pipelines
  • Reporting on data quality levels for business teams

Data Cataloging & Lineage

We implement a data catalog and track lineage, so your team always knows where data comes from.

  • Cataloging key datasets
  • Documenting metadata and business definitions
  • Tracking lineage where data comes from and how it’s transformed
  • Selecting and implementing tools (Collibra, Atlan, Microsoft Purview, Alation)

Compliance & Access Control

We help reduce regulatory risk by putting the right controls around sensitive data.

  • Classifying data by sensitivity level
  • Setting data retention and deletion policies
  • Implementing role-based access control
  • Ensuring compliance with GDPR, CCPA, PIPEDA, and industry requirements

Data Governance as the Foundation for BI & AI

Data governance isn’t just a compliance checkbox; it’s the groundwork that makes dashboards, reporting, and AI/ML initiatives dependable. When ownership, definitions, and quality standards are clear, everything built on top of the data holds up.

  • Without high-quality, consistent data, dashboards show conflicting numbers
  • ML models trained on “dirty” data produce unreliable predictions
  • Clear data ownership speeds up the rollout of new reports and products
  • Governance reduces risk ahead of audits and regulatory reviews

What You Get From DSC Data Governance Services

  • Trusted, Consistent Data Unified metric definitions across all teams and systems.
  • Clear Ownership & Accountability It’s clear who is responsible for the quality of specific data.
  • Reduced Compliance Risk Fewer surprises during audits and regulatory reviews.
  • Faster, Safer Data Access Teams get the data they need faster, without unnecessary risk.
  • Higher Adoption of BI & AI Trust in data increases the use of dashboards and models.

Our Data Governance Process

A clear, structured approach that gives clients confidence this isn’t a scattered set of tasks, but a defined path from assessment to adoption.

  1. Governance Maturity Assessment: assessment of the current state: data owners, quality, tools, and risks.
  2. Framework & Policy Design: developing the governance operating model, roles, and policies.
  3. Stewardship Model & Roles: defining owners and stewards for key data domains.
  4. Tooling & Cataloging Implementation: implementing the data catalog, quality rules, and lineage.
  5. Rollout, Training & Change Management: training teams and gradually rolling out governance processes.

Data Governance Tools We Work With

The platforms and tools DSC uses to bring governance, quality, and cataloging to life across your data ecosystem.

  • Cataloging & metadata: Collibra, Atlan, Microsoft Purview, Alation.
  • Data quality: dbt tests, Great Expectations, Monte Carlo.
  • Data platforms: Snowflake, Databricks, BigQuery integrated with Data Architecture and Data Engineering.

Related Data Governance Case Studies

Related Services

Data governance works best alongside the rest of the data stack. Here are related services from DSC.

Frequently Asked Questions

What is data governance, and how does it differ from data management?

Data governance sets the policies, ownership, and standards that determine how data should be handled, while data management is the day-to-day execution of those standards. Governance defines the rules; management carries them out.

What is included in your data governance consulting services?

Our services cover data ownership frameworks, access controls, data cataloging, quality standards, and compliance alignment tailored to your existing systems and team structure.

Why is data governance essential for small and medium-sized businesses?

Without governance, growing businesses accumulate inconsistent metrics, unclear ownership, and compliance risk. A right-sized governance program keeps data trustworthy as the company scales.

What are the roles of data stewards and data owners?

Data owners are accountable for a dataset’s accuracy and appropriate use, while data stewards manage its day-to-day quality, documentation, and access on the owner’s behalf.

How do you implement a data catalog?

We inventory your data sources, define consistent metadata and business definitions, and roll out a catalog tool that makes data easy to find, understand, and trust.

Do we need a dedicated data governance tool to get started?

No. Many organizations start with clear policies, defined ownership, and lightweight documentation before investing in a dedicated platform.

How does data governance impact dashboard accuracy and data quality?

When metrics are defined once and governed consistently, dashboards pull from the same trusted source, eliminating conflicting numbers and rebuilding confidence in reporting.

Do you provide assistance with GDPR, CCPA, or PIPEDA compliance?

Yes. We help design governance frameworks that support compliance with GDPR, CCPA, PIPEDA, and other applicable regulations.

What is the typical timeline for implementing a data governance program?

Timelines vary by scope and data complexity, but most initial programs take a few months to establish, with maturity building over time.

How do you measure and monitor data quality?

We define quality metrics such as accuracy, completeness, and consistency, then set up monitoring so issues are caught and resolved before they reach reporting.

Can data governance be implemented incrementally rather than company-wide?

Yes. We typically recommend starting with a high-priority domain or dataset to prove value, then expanding governance across the organization.

How is data governance maintained after the initial implementation?

Governance is sustained through ongoing stewardship, periodic reviews, and clear accountability not a one-time project that’s shelved after launch.

Ready to Build a Trusted Data Foundation?

If your team lacks trust in the numbers in reports, has no clear data owner, or faces growing compliance risks, DSC will help build a practical governance program that actually takes hold within the company. Let’s start with an assessment of your current governance maturity.

Get a Governance Maturity Assessment