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              Data Governance & Quality

              Transform Data into Trust

              Microsoft-powered governance solutions for secure, trusted enterprise data

              Why Data Governance & Quality Matter

              Data governance and quality make enterprise data traceable and safe to use. Without them, data pipelines break trust, compliance becomes reactive, and AI systems scale inconsistency instead of insight.

              Alletec helps you:

              Standardize data definitions and policies
              Monitor and improve data quality constantly
              Manage access, privacy, and compliance requirements
              Enable trusted analytics across the organization
              Data Governance & Quality
              One Foundation Testimonial Background
              One Foundation Logo White
              “The Microsoft Fabric Data Platform has transformed our reporting and analytics. We no longer face ERP refresh limitations and now have real-time insights across systems. This foundation positions us to leverage AI and advanced analytics for future community impact.”
              Kerry Bird, One FoundationRead Full Case Study

              Data Governance & Quality Challenges

              Modern organizations struggle to scale analytics and AI without data governance and quality.

              Uncontrolled self-service analytics
              AI models trained on inconsistent or poor-quality data
              Limited lineage, traceability, and explainability
              Increasing risk as data usage expands

              Our Data Governance & Quality Services

              Enterprise Data Governance Frameworks

              Design and implementation of pragmatic governance frameworks that define data ownership and controls across the data estate.

              Microsoft Purview
              Microsoft Fabric governance capabilities
              Microsoft Entra ID (role-based access)
              Business Impact

              Clear accountability for enterprise data

              Reduced ambiguity and data misuse

              Scalable governance aligned to growth

              Data Cataloging, Lineage & Discovery

              Centralized data cataloging that allows users to understand and trust data. It provides full lineage from source systems to reports and AI models.

              Microsoft Purview Data Catalog
              Fabric metadata integration
              Business Impact

              Faster data discovery

              Improved trust in reports and dashboards

              Transparency across data pipelines and transformations

              Data Quality Management

              Implementation of data quality checks, validation rules, and monitoring. It helps ensure data meets business and regulatory standards.

              Fabric data pipelines
              Quality rules and validation logic
              Monitoring and alerting tools
              Business Impact

              Reduced reporting errors

              Improved decision accuracy

              Fewer manual reconciliations

              Security, Privacy & Access Control

              Protection of sensitive and regulated data through classification, access controls, and policy enforcement. It is done across analytics and AI.

              Microsoft Purview Information Protection
              Sensitivity labels
              Role-based access controls
              Business Impact

              Reduced data leakage risk

              Compliance with regulatory requirements

              Secure data sharing across teams

              Governance for Analytics & AI

              Governance models that ensure analytics, AI, and GenAI solutions operate on trusted and compliant data.

              Purview lineage and audit trails
              Fabric + AI platform integration
              Business Impact

              Trusted AI outcomes

              Reduced AI risk and bias

              Audit-ready analytics and AI systems

              Industries We Support

              Financial Services

                Data governance solutions enable regulatory compliance and audit readiness for financial institutions. They provide clear lineage for financial and risk reporting. They also ensure secure access to sensitive customer and financial data allowing teams to meet regulatory requirements while making decisions.

              Manufacturing & Supply Chain

                These teams rely on operational and sensor data to run plants efficiently. Governance ensures that the team gets trusted operational and sensor data, consistent production and quality metrics across systems, and controlled data sharing across plants. This creates reliable visibility without sacrificing control as operations scale.

              Retail & Distribution

                Retail organizations need to manage data across regions and customer touchpoints. Data governance and quality ensure accurate pricing and customer data, support the secure use of customer information. It also enforces governance across channels and regions. This enables coordinated decision-making while protecting customer trust.

              Professional Services

                Professional services firms depend on timely insights into performance. With Data governance tools organizations get reliable project and financial data, establish clear ownership of client and operational datasets, and enable controlled analytics access. This ensures trusted reporting while safeguarding sensitive client information.

              Governance Without Friction

              Alletec helps organizations implement governance and quality that:

              Support self-service analytics
              Maintain data quality and consistency
              Scale with enterprise data growth
              Align technical and business teams

              Why Alletec

              Microsoft Governance Platform Expertise

              • Microsoft Solutions Partner for Data & AI with a strong focus on governance and quality
              • Deep expertise implementing governance using Microsoft Purview and Microsoft Fabric
              • Fabric-first governance model aligned to Microsoft’s unified data platform
              • Hands-on experience designing lineage, metadata, classification, and access controls at enterprise scale

              Enterprise Data Governance Experience

              • Strong background governing data originating from ERP and core business systems
              • Deep understanding of financial, manufacturing, and operational data domains
              • Experience governing complex, legacy, and on-premises data sources
              • Proven track record governing data across Dynamics 365 and industry-specific systems

              Governance Designed for Production Use

              • Focus on governance that works in day-to-day operations, not just policy documents
              • Quality, access control, and lineage designed to hold up under real usage
              • Automation-driven approach to monitoring, enforcement, and accountability
              • Not just framework design. We help organizations depend on their governed data

              Integrated Governance Across the Data Lifecycle

              • Governance embedded across ingestion, analytics, and AI usage
              • Alignment between governance, analytics, and AI teams
              • Native integration with Power BI, Azure AI/ML, and business applications

              Our Data Governance Implementation Approach

              Phase 1

              Assessment & Strategy

              (2-4 weeks)

              • Current state assessment of your data landscape
              • Data quality analysis and pain point identification
              • Governance maturity assessment
              • Roadmap and prioritization based on business value
              Phase 2

              Quick Wins & Foundation

              (4-8 weeks)

              • Microsoft Purview deployment and initial data discovery
              • Critical data quality issues remediation
              • Basic governance framework and roles definition
              • Initial business glossary creation
              Phase 3

              Scale & Mature

              (8-16 weeks)

              • Comprehensive data catalog with lineage
              • Automated data quality monitoring
              • Security and compliance controls implementation
              • Master Data Management for key domains
              • Training and change management
              Phase 4

              Optimize & Sustain

              (Ongoing)

              • Continuous improvement and optimization
              • Governance metrics tracking and reporting
              • Expansion to additional data domains
              • Managed services and ongoing support

              Ready to Build Trust in Your Data?

              If inconsistent data, compliance concerns, or lack of visibility are limiting your analytics and AI initiatives, Alletec can help.

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              Contact Us

              Got questions about Data Governance & Quality ? Check out our FAQs for best answers

              Data governance is the set of processes and controls that ensure data is accurate and used responsibly across the organization. For enterprises, data governance is critical because data is shared across teams, systems, and use cases.

              Starting a data governance program begins with strategy, not tools.

              A practical approach includes:

              • Defining a clear data governance strategy aligned to business priorities
              • Establishing ownership using a defined data governance operating model
              • Identifying critical data domains and key data elements
              • Defining policies, standards, and data governance principles
              • Selecting enabling data governance tools to operationalize controls

              Many organizations use a data governance maturity model to assess where they are today and define realistic next steps for implementing data governance over time.

              Yes. Modern governance approaches are designed to integrate with existing enterprise systems rather than replace them.

              A modern data governance platform integrates with:

              • ERP and business applications
              • Data warehouses and lakehouses
              • Analytics and BI tools
              • Cloud and on-premises data sources

              This enables data management and data governance to operate together, ensuring governance policies travel with the data across systems without disrupting existing workflows.

              A comprehensive data governance model typically includes:

              • Governance structure – Roles such as data owners, stewards, and custodians
              • Policies and standards – Definitions, classification, and usage rules
              • Data governance processes – Issue management, change control, and escalation
              • Technology enablement – Catalogs, lineage, classification, and access controls
              • Measurement and oversight – KPIs aligned to a governance maturity model

              Together, these components form a scalable data governance architecture that supports both operational and analytical use cases.

              Data governance directly improves data quality by making ownership and accountability explicit.

              Through defined data governance processes, organizations:

              • Standardize definitions and business rules
              • Enforce validation and quality checks
              • Track lineage to identify root causes of data issues
              • Align data quality and data governance initiatives under a single operating model

              As a result, data governance and quality improve together—reducing rework, reconciliation effort, and loss of trust in reports.

              Analytics and AI depend on data that is reliable, secure, and well understood.

              Strong enterprise data governance ensures:

              • Governed access to trusted datasets for analytics teams
              • Clear lineage and definitions for consistent reporting
              • Secure handling of sensitive data through data governance and privacy controls
              • Compliance-ready datasets for regulated use cases

              By embedding governance into the platform, organizations enable analytics and AI to scale without duplicating data or creating unmanaged risk. This is why data governance best practices are foundational to successful AI adoption.

              Alletec blends deep Microsoft solutions expertise with industry knowledge and 25+ years of experience to catalyse digital transformation and amplify business outcomes for enterprises.

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