Enterprise Data Management & security Services

Data governance & protection

Understand, classify and safeguard your data to ensure responsible access, reduce risk and enable secure use of your information by both people & AI.

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Understand, Protect & Manage Your Data

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Understand Your Data

Gain visibility into your data landscape by locating, identifying, classifying, and organizing information so you know what data you have and how it’s being used. 

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Protect your data

Safeguard sensitive and business-critical information through robust security measures, ensuring responsible access and reducing risk for both people and AI. 

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Manage Data Lifecycle

Keep the data you need, remove the data you should. Retain only what’s necessary for business or compliance reasons and securely dispose of unnecessary or outdated data to minimize risk and optimize operations. 

Common Data Governance Challenges We Solve

Gain Visibility into Your Data

Lack of visibility into all organizational data leads to unknown risks and missed opportunities.

Reduce Risk of Data Exfiltration

Increased risk of data breaches or unauthorized access due to inconsistent protection and classification.

Meet Data Compliance Requirements

Challenges meeting compliance requirements and retention policies leads to the risk of regulatory penalties or data sprawl.

Reduce Storage Costs & Data Exposure

Inefficient data lifecycle management, resulting in unnecessary storage costs and exposure from retaining outdated or irrelevant data.

Ready to Secure Your Data for People and AI?

Data Governance & Protection Consulting Services

Data Catalog & Discovery
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Gain visibility into what data you have, where it lives, and how it’s used.

Data Classification & Endorsements
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Classify and label data so the right people—and AI—use it responsibly.

Document-Based Data Protection
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Protect unstructured files wherever they live and travel.

Structured Data Protection
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Secure sensitive data inside databases and applications.

Data Lifecycle Management
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Keep what you need, remove what you don’t.

AI Data Security
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Enable AI without putting your data at risk.

Insider Risk Management

Protect your organization from intended or unintended risks caused by your employees actions.

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Data Catalog & Discovery

Gain visibility into what data you have, where it lives, and how it’s used.

Schedule Icon

Data Classification & Endorsements

Classify and label data so the right people—and AI—use it responsibly.

Plan Icon

Document-Based Data Protection

Protect unstructured files wherever they live and travel.

hand holding a gear with workflow signifying support and management

Structured Data Protection

Secure sensitive data inside databases and applications.

Two hands shaking with a gear above them

Data Lifecycle Management

Keep what you need, remove what you don’t.

Report Icon

AI Data Security

Enable AI without putting your data at risk.

Insider Risk Management

Protect your organization from intended or unintended risks caused by your employees actions.

DATA GOVERNANCE & PROTECTION FREQUENTLY ASKED QUESTIONS

What is data governance and why is it important for enterprises?

Data governance is the practice of understanding, managing, and protecting data so it can be used responsibly and securely. For enterprises, strong data governance reduces risk, supports compliance, improves data quality, and enables trusted use of data for analytics and AI initiatives.

How does data governance reduce security and compliance risk?

Effective data governance reduces risk by identifying where sensitive data lives, classifying it correctly, and enforcing consistent protection and retention policies. This helps prevent data exfiltration, unauthorized access, and compliance violations while improving audit readiness and visibility across the data estate.

How does data governance support AI and Copilot adoption?

AI and copilots rely on access to large volumes of data, which increases the risk of oversharing or misuse. Data governance ensures only appropriate, well‑classified data is available to AI tools, enabling responsible AI adoption while protecting sensitive and regulated information.

What is the difference between data protection and data governance?

Data protection focuses on securing data through controls like encryption, access policies, and data loss prevention. Data governance is broader—it includes protection, but also covers discovery, classification, lifecycle management, compliance, and decision‑making around how data is used by people and AI.

How do organizations gain visibility into their data?

Organizations gain visibility by implementing data discovery, cataloging, and classification across structured and unstructured data sources. A governed data catalog helps teams understand what data exists, where it’s stored, who can access it, and how it’s being used.

How does data lifecycle management reduce cost and risk?

Data lifecycle management ensures data is retained only as long as necessary for business or regulatory purposes and securely deleted when it’s no longer needed. This reduces storage costs, limits exposure from outdated data, and helps organizations meet retention and compliance requirements.

What platforms and tools support data governance and protection?

Modern data governance is commonly enabled through Microsoft platforms such as Purview, Microsoft 365, Azure, and Fabric. These tools support data cataloging, classification, protection, compliance, and AI data security across cloud, on‑prem, and SaaS environments.

When should an organization invest in data governance?

Organizations should invest in data governance when facing compliance challenges, security incidents, AI adoption initiatives, or rapid data growth. It’s especially critical before deploying AI, copilots, or advanced analytics to ensure data is trusted, protected, and used responsibly.

Case Studies

01
Building a User ID Agent to Modernize Client Services
02
Data Platform Assessment Creates a Clear Path to Modernization
03
Turning Sales Order Backlog into Actionable Business Insight
04
Preserving Critical Engineering Knowledge with an AI Assistant
05
Creating a Trusted Sales Data Foundation with Microsoft Fabric
06
Building AI Into the Flow of Service Operations
01

Building a User ID Agent to Modernize Client Services

How a Global Data and Analytics Organization Used AI to Automate User Access Management and Create a Foundation for Service Operations Transformation

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02

Data Platform Assessment Creates a Clear Path to Modernization

How a Manufacturing Organization Used a Focused Assessment to Identify Reporting Risks, Select a Future-State Architecture, and Define Its Next Investment

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03

Turning Sales Order Backlog into Actionable Business Insight

How a Global Manufacturer Is Using Microsoft Fabric and Power BI to Improve Shipment Readiness, Backlog Visibility, and Business Decision-Making

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04

Preserving Critical Engineering Knowledge with an AI Assistant

How a Specialized Manufacturer Is Turning Institutional Expertise into a Governed, Searchable Engineering Resource

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05

Creating a Trusted Sales Data Foundation with Microsoft Fabric

How a Manufacturing Organization Is Replacing Duplicated Reporting Logic with a Governed, Scalable Analytics Platform

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06

Building AI Into the Flow of Service Operations

How a Global Data and Analytics Organization Used Microsoft AI to Modernize IT Service Management

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Blog

Data, KQL, Log Analytics, Microsoft, Microsoft Sentinel, Transform

Transforming Log Analytics: How We Saved a Company Over $100,000

Joseph Dutton