Durga Analytics Enterprise Offering
Enterprise Data Governance — End-to-End Governance for Modern Enterprises
A complete, end-to-end data governance program design and implementation service. We help you define policies, operating model, data catalog, data quality, security, privacy and stewardship, and turn governance from a PowerPoint topic into a working capability embedded in day-to-day decisions.
Enterprise Data Governance Snapshot
- • End-to-end data governance framework tailored to your business and regulatory context
- • Practical operating model: roles, RACI, forums, processes and KPIs
- • Technology-agnostic blueprint covering catalog, lineage, DQ, MDM and security tooling
- • Implementation roadmap and quick wins aligned to your data platform and analytics strategy
Why Enterprise Data Governance, End-to-End?
Most organizations realize that data is a strategic asset, but governance remains fragmented: overlapping committees, multiple glossaries, Excel-based data dictionaries and unclear ownership. Our Enterprise Data Governance offering creates a unified, outcome-focused capability that supports compliance, analytics, AI and day-to-day operations.
From Slides to System
Move beyond high-level frameworks. We translate principles into concrete processes, roles, workflows, tools and KPIs that teams actually use.
Business-First, Not Tool-First
Start with business outcomes: trusted MIS, regulatory reporting, AI readiness, reduced rework. Then align policies, data models and tools to those outcomes.
Designed to Scale
A modular governance blueprint you can extend from one domain and region to enterprise-wide, across cloud, on-prem and hybrid environments.
Core Governance Pillars
We structure Enterprise Data Governance around six interlocking pillars — covering strategy, people, process, technology, and controls — so the program is complete yet practical.
Pillar 1 — Strategy, Principles & Operating Model
- Data vision & governance principles aligned to business and digital strategy
- Defined scope and priorities: domains, regions, regulations and critical data elements
- Governance structure: steering committee, data council, domain councils
- Operating model with clear RACI across business, IT, risk, compliance and data teams
Pillar 2 — Data Ownership, Stewardship & Culture
- Data owner and data steward role definitions, KPIs and incentives
- Domain-based ownership mapped to products, customers, locations, etc.
- Stewardship processes for definition changes, data issue management and approvals
- Awareness and training programs to build a “data as product” mindset
Pillar 3 — Data Catalog, Metadata & Lineage
- Business glossary: common definitions for KPIs, entities, and critical attributes
- Technical metadata and lineage from source systems to reports and models
- Tool selection / optimization (Collibra, Alation, Purview, Informatica, open source, etc.)
- Processes for onboarding new datasets and maintaining metadata quality
Pillar 4 — Data Quality, Controls & Issue Management
- Enterprise DQ framework: dimensions, rules, thresholds and scoring
- Implementation of DQ checks at ingestion, transformation and consumption layers
- Data quality dashboards and scorecards by domain and system
- Issue logging, triage, remediation workflows and root cause analysis
Pillar 5 — Privacy, Security & Compliance
- Data classification scheme and handling guidelines for sensitive data
- Access control patterns, RBAC, masking, tokenization and encryption approaches
- Alignment with regulatory obligations (e.g., GDPR-style privacy, sector regulations)
- Controls for AI and advanced analytics use of governed data
Pillar 6 — Master Data, Reference Data & Lifecycle
- Conceptual and logical models for key master and reference data domains
- Golden record strategy (central MDM, domain MDM, registry/hub patterns)
- Data lifecycle management: creation, change, archival and deletion
- Integration with data platforms, warehouses, lakes and downstream systems
Typical Governance Outcomes
- Single, trusted definition of key KPIs across finance, risk, sales and operations
- Reduced reconciliation effort between reports and systems
- Improved confidence in regulatory and board reporting
- Faster onboarding of new products, channels and data sources
- Clear ownership for data issues and quality improvement
- Higher success rate for analytics and AI initiatives
- Audit-ready documentation for controls and data flows
- Better risk management around privacy and data access
- Foundation for data mesh / data product strategies
Delivery Approach — From Assessment to Embedded Governance
Our Enterprise Data Governance program is delivered in structured phases, each with tangible outputs and stakeholder alignment. We work closely with business, technology, risk and compliance teams.
Phase 1 — Assessment & Blueprint
Current-state assessment of governance, tools, data quality and pain points. We define target-state governance model, principles, and high-level architecture; identify quick wins; and agree on a prioritized roadmap by domain.
Phase 2 — Design & Foundation Build
Design detailed processes, roles, forums and metrics. Configure or enhance catalog, lineage and data quality tooling. Stand up governance for initial domains (e.g., customer, product, finance) including definitions, rules and ownership.
Phase 3 — Rollout, Adoption & Continuous Improvement
Scale governance to additional domains and regions. Embed governance checkpoints into change management and SDLC. Establish regular councils, scorecards and continuous improvement backlog.
What You Get — Tangible Governance Artifacts
Our end-to-end program leaves you with a fully documented and operational data governance capability, not just recommendations.
- Data governance charter, principles and target operating model
- Role descriptions, RACI matrices and governance forum terms of reference
- Business glossary and critical data element inventory for initial domains
- Data quality framework, rules catalog and dashboards for selected domains
- Classifications, policies and control patterns for privacy and security
- Processes and SOPs for stewardship, issue management, change control and approvals
- Tooling blueprint (catalog, lineage, DQ, MDM) and configuration guidelines
- Implementation roadmap for the next 12–24 months, aligned with your data platform strategy
Engagement Models & Indicative Pricing
We tailor the engagement to your size, regulatory context and current maturity. Below are typical models.
Focused Domain Governance
Ideal for organizations starting governance in a single critical area (e.g., Customer, Finance, Risk). Focus on blueprint, governance for 1–2 domains, and quick wins.
- 6–10 week program
- 1–2 domains in scope
- Lightweight tool configuration
Enterprise Governance Foundation
For organizations ready to establish a central governance capability and roll out across multiple domains and functions.
- 12–24 week program
- 3–6 domains in scope
- Operating model + tooling blueprint
- Data quality and catalog rollout for priority domains
Managed Governance & Stewardship
Ongoing support from Durga Analytics as your governance partner — co-running councils, managing tools, tracking DQ and stewarding adoption.
- Co-managed or fully managed governance operations
- Tool admin, metrics, training and change management
- Quarterly maturity and roadmap reviews
Durga Analytics Data Governance Team
Governance, Risk & Data Leaders
Consultants with deep experience across banking, financial services, energy, retail and digital-native enterprises — blending data strategy, architecture, risk, compliance and engineering.
Technology & Platform Experience
- Enterprise data platforms (Databricks, Snowflake, BigQuery, Azure/AWS/GCP data stacks)
- Data governance tools (Collibra, Alation, Informatica, Azure Purview and others)
- MDM, DQ and lineage solutions integrated with BI and AI platforms
- Practical patterns for data mesh, data products and AI governance
Request an Enterprise Data Governance Consultation
Share a brief overview of your current data landscape, key systems, regulatory context and top data pain points. We’ll respond with a tailored assessment proposal and a draft roadmap for an end-to-end governance program.