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Bitsquad

Data Governance & Quality

Transform Data into Trust

Microsoft-powered governance solutions for secure, trusted enterprise data

Talk to Our Experts

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.

From Data Platform to Intelligence Platform

Traditional data platforms were built for storage and reporting. That model no longer fits how modern organizations operate. Reality That Enterprises Face Today:

Standardize data definitions

Standardize data definitions and policies

Monitor data quality

Monitor and improve data quality constantly

Manage access

Manage access, privacy, and compliance requirements

Enable trusted analytics

Enable trusted analytics across the organization

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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 Foundation

Data Governance & Quality Challenges

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

Uncontrolled self-service

Uncontrolled self-service analytics

Limited lineage

Limited lineage, traceability, and explainability

AI models

AI models trained on inconsistent or poor-quality data

Increasing risk

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

Microsoft Fabric is built to work across industries, from SMBs to enterprises. Some use cases for Fabric include:

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

Bitsquad helps organizations implement governance and quality that:

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Support self-service analytics

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Maintain data quality and consistency

03

Scale with enterprise data growth

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Align technical and business teams

Why Bitsquad

Microsoft Governance Platform Expertise

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

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

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

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

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

What is data governance and why is it important?

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Data governance is the practice of managing data availability, usability, integrity, and security. It establishes policies, standards, and responsibilities for data across the organization. Data governance is important because it ensures data is trustworthy, compliant with regulations, and accessible to those who need it while protecting sensitive information. Without governance, organizations face data silos, inconsistent reporting, compliance risks, and unreliable AI outcomes.

How do you start a data governance program?

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Starting a data governance program begins with assessing your current data maturity, identifying critical data domains, defining clear roles and responsibilities (data owners, stewards), establishing key policies and standards, selecting appropriate tools (like Microsoft Purview), implementing foundational governance for high-priority data, and then iteratively expanding scope based on business value.

Can you integrate data and governance platforms with existing systems?

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Yes, Microsoft Purview and Fabric governance capabilities integrate seamlessly with existing systems including on-premises databases, cloud data sources (AWS, Google Cloud), SaaS applications, ERP systems, and custom data platforms. This enables unified governance across your entire data estate without requiring data movement.

What are the key components of data governance?

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Key components include: data cataloging and metadata management, data lineage and traceability, data quality management, data classification and sensitivity labeling, access control and role-based security, policy management and enforcement, compliance and audit reporting, and data stewardship frameworks.

How does data governance improve data quality?

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Data governance improves data quality by establishing clear data standards, validation rules, and ownership. It enables proactive monitoring of data quality metrics, automated detection of anomalies, root cause analysis through lineage tracking, and remediation workflows. This results in more accurate, consistent, and reliable data for decision-making.

How does data governance support analytics and AI?

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Data governance ensures analytics and AI models operate on trusted, high-quality, well-documented data. It provides lineage from source to insight, ensures compliance with data privacy regulations, enables secure access to sensitive data, and establishes business glossary definitions. This leads to more accurate AI outcomes, reduced bias, audit-ready analytics, and faster time-to-trust for data-driven decisions.

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Whether you are a business aiming to embrace the next wave of digital transformation or a professional seeking a dynamic and inspiring workplace, Alletec is your partner in progress. At Alletec, a trusted Microsoft Dynamics 365 partner, technology meets empathy, and possibilities turn into reality. Together, let's create a future of success, innovation, and shared growth.

Let's make tomorrow extraordinary—together.

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