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BPL Database

Database Systems, Management, Libraries and more.

How to Create Governance Policies for Data Handling: Best Practices

Jacob Davis, April 17, 2025April 8, 2025

Did you know that 92% of businesses now prioritize structured data frameworks? Without clear guidelines, companies risk compliance gaps and costly data breaches—averaging $4.35 million per incident.

A well-designed policy ensures consistent information management while reducing risks. Tools like Atlan’s Policy Center help teams implement compliance 63% faster, and brands like Tide have slashed GDPR response times from weeks to hours.

This guide breaks down a 12-step process to align regulatory needs with real-world execution. By the end, you’ll know how to protect assets and streamline operations.

Table of Contents

Toggle
  • What Are Data Governance Policies (And Why You Need Them)
    • Defining data governance policies in plain terms
    • The business impact of strong data governance
  • 6 Types of Governance Policies for Data Handling
    • Data Quality Policies: Ensuring Accuracy and Reliability
    • Security Policies: Protecting Your Assets
    • Privacy Policies: Compliance with Regulations
    • Lifecycle Policies: Managing Data from Creation to Deletion
    • Ethics Policies: Aligning Data Use with Company Values
    • Definition Policies: Creating a Common Language
  • Who Should Be Involved in Creating Your Policies
    • Key Stakeholders Across Your Organization
    • Building Cross-Functional Collaboration
  • How to Assess Your Current Data Practices
    • Conducting a Data Inventory Audit
    • Identifying Gaps and Risks
  • Defining Clear Objectives for Your Data Governance
    • Connect Rules to Real Business Outcomes
    • Measure Success with SMART Metrics
  • Drafting Your Data Governance Policy Document
    • Essential Sections Every Policy Needs
    • Writing Tips for Clarity and Adoption
  • Implementing Technology to Support Your Policies
    • Tools for Automated Enforcement
    • Choosing the Right Platform
  • Rolling Out Policies Across Your Organization
    • Change Management That Works
    • Training Teams Without Overwhelm
  • Monitoring and Maintaining Your Governance Framework
    • Setting Up Regular Policy Reviews
    • Key Performance Indicators to Track
  • Real-World Examples of Effective Data Governance
    • Healthcare Sector: Saving Lives and Sensitive Data
    • Higher Education: Blueprints for Campus-Wide Success
  • Taking Your Data Governance to the Next Level
  • FAQ
    • What exactly are data governance policies?
    • Why should my company invest in these policies?
    • What’s the difference between security and privacy policies?
    • How often should we update our governance framework?
    • Who needs to be involved in creating these rules?
    • Can small businesses benefit from formal governance?
    • What tools help enforce governance policies?
    • How do we get employees to follow new data procedures?

What Are Data Governance Policies (And Why You Need Them)

Imagine your company’s information as a busy highway—without traffic rules, chaos ensues. A data governance policy acts like those rules, ensuring everyone uses and protects details correctly.

Defining data governance policies in plain terms

Think of it as a playbook. It combines three things:

  • People guidelines: Who can access what
  • Process maps: Steps to handle information safely
  • Tech requirements: Tools to enforce the rules

The business impact of strong data governance

Companies with clear rules see 22% higher profits (Forrester). Why? Fewer errors, faster decisions. A healthcare group cut patient leaks by 81% after updating their framework.

Policy BenefitImpact
Better complianceAvoids 78% of GDPR fines
Stronger securityReduces breach costs by 40%
Clearer processesSaves 15+ hours weekly

Without these guardrails, you risk fines, leaks, and wasted time. The fix? Start building your playbook today.

6 Types of Governance Policies for Data Handling

Six core strategies form the backbone of a resilient system. Each tackles a unique challenge—from accuracy to ethical use. Here’s how they work together.

Data Quality Policies: Ensuring Accuracy and Reliability

Mistakes cost time and trust. Set standards like Atlan’s 97.3% accuracy threshold with automated checks. Example rules:

  • Validate entries in real time (e.g., email formats).
  • Flag outliers for review before use.

Security Policies: Protecting Your Assets

Breaches hurt reputations and budgets. Layer defenses like:

  • Role-based access (only what’s needed).
  • Encryption matching PCI DSS standards.

Privacy Policies: Compliance with Regulations

Avoid fines by automating GDPR or HIPAA workflows. Track consent and anonymize details where required.

Lifecycle Policies: Managing Data from Creation to Deletion

Not all info stays useful forever. Auto-archive old records (e.g., purge customer details after 7 inactive years).

Ethics Policies: Aligning Data Use with Company Values

Monitor AI bias in hiring tools. Audit algorithms quarterly to ensure fairness.

Definition Policies: Creating a Common Language

End confusion with a shared glossary. UNLV’s 200-term template ensures teams mean the same thing by “customer” or “revenue.”

Policy TypeKey Benefit
QualityReduces errors by 62%
SecurityCuts breach costs by 40%
PrivacyAvoids 78% of fines

Mix these rules to build a framework that’s both flexible and foolproof.

Who Should Be Involved in Creating Your Policies

Who you include in the process determines your success. The right mix of expertise ensures rules are practical, compliant, and adopted company-wide.

A team of diverse professionals collaborating on data governance policies in a bright, modern office. In the foreground, three individuals - a data analyst, a compliance officer, and a business stakeholder - are gathered around a glass-topped conference table, engaged in a focused discussion. Soft, indirect lighting from overhead fixtures creates a warm, collegial atmosphere. In the middle ground, a wall-mounted monitor displays a data flow diagram, highlighting the complexities of data handling processes. The background features floor-to-ceiling windows, offering a scenic view of a bustling city skyline, symbolizing the far-reaching impact of their work. The team's body language conveys a sense of teamwork, with hands gesturing and eyes locked in thoughtful exchange.

Key Stakeholders Across Your Organization

Define roles responsibilities early. Essential players include:

  • Chief Data Officer: Aligns strategy with business goals.
  • Legal Counsel: Maps rules to GDPR or HIPAA.
  • IT Security Lead: Implements tech safeguards.

Data stewards bridge gaps between departments. They ensure accuracy and resolve conflicts.

Building Cross-Functional Collaboration

Weekly syncs between marketing and IT cut errors by 34%. Aliaxis formed a 14-member council, slashing conflicts by 67%.

Tools like Atlan’s workflow templates reduce meeting hours by 41%. Assign accountability using a RACI matrix:

RoleResponsibility
Data OwnersApprove final drafts
ComplianceAudit for legal risks
ITEnforce tech controls

Strong teams thrive on collaboration. Start small, scale fast, and measure progress.

How to Assess Your Current Data Practices

You can’t fix what you don’t measure—start with an honest audit. Mapping your setup reveals weak spots you never noticed. Here’s how to pinpoint gaps before they become disasters.

Conducting a Data Inventory Audit

Catalog all assets, even hidden ones like shadow IT. BigID’s tools scanned 2.3M items in 11 minutes—automation saves weeks of manual work.

  • List 23 critical points (storage locations, user access logs).
  • Evaluate quality: Is info outdated or duplicated?
  • Analyze flows: Who touches what, and how often?

Identifying Gaps and Risks

Compare your processes to ISO 8000-61 standards. Heat maps highlight high-risk zones needing urgent fixes.

Use a 1–5 scale to score:

  • Likelihood of breaches (e.g., unencrypted files = 5).
  • Impact if leaked (customer details vs. internal memos).

Classification labels (public/internal/confidential) streamline protection. Update quarterly as threats evolve.

Defining Clear Objectives for Your Data Governance

Clear goals turn vague ideas into actionable results—start with the right objectives. Without them, even the best rules lack direction.

Connect Rules to Real Business Outcomes

Link your framework to tangible wins. A retail chain boosted inventory turnover by 18% after tying quality checks to supply chain speed.

Examples of aligned goals:

  • Cut storage costs by 20% with lifecycle automation.
  • Reduce breach response time to under 2 hours.

Measure Success with SMART Metrics

Track progress using 8 key metrics:

  1. Policy adoption rates (aim for 90%+).
  2. Incident resolution speed (e.g., under 4 hours).
  3. Cost per gigabyte of stored details.

Atlan’s dashboards show real-time compliance scores, helping teams stay audit-ready. Set targets like “100% ISO 27001 certification readiness” to keep efforts focused.

Strong business results start with sharper goals. Define yours today.

Drafting Your Data Governance Policy Document

Clear writing saves teams 100+ hours annually—craft policies that stick. A document that’s confusing or incomplete won’t protect your business. Follow this blueprint to build one that works.

A crisp, professionally-bound document laid on a clean, well-lit desk. The pages are organized in a clear, structured layout, with section headings and bullet points. The cover page displays the title "Data Governance Policy" in a bold, modern font. Soft, directional lighting casts subtle shadows, emphasizing the document's tangibility. The background is a neutral, uncluttered space, allowing the policy document to be the central focus. The overall mood is one of authority, clarity, and attention to detail - reflecting the importance of a well-crafted data governance policy.

Essential Sections Every Policy Needs

Eugenia Moore’s 7-part template cuts drafting time by 40%. Include these:

  • Purpose: Why the rules exist (e.g., “Ensure GDPR compliance”).
  • Applicability: Who must follow them (teams, vendors).
  • Definitions: Clarify terms like “sensitive data.”

Atlan’s AI auto-generates these sections, reducing writing time by 58%.

Writing Tips for Clarity and Adoption

Replace “utilize” with “use” to hit an 80+ Flesch-Kincaid score. More hacks:

  • Version control: Track changes like code (Git-style logs).
  • 4-stage reviews: Legal → IT → Leadership → Final sign-off.
  • Active voice: “Teams must encrypt files” vs. “Files should be encrypted.”
SectionExampleTool
Purpose“Reduce breach risks”Atlan AI
Procedures“Quarterly audits”Checklist
Standards“ISO 27001 aligned”Compliance Hub

Avoid jargon. Test readability with Hemingway Editor. Update every 6 months—or after major regulatory shifts.

Implementing Technology to Support Your Policies

Tech is your secret weapon for turning rules into results—here’s how to pick the right tools. Manual processes slow you down, but automation handles the grunt work while reducing errors.

Tools for Automated Enforcement

Atlan’s policy-as-code feature cuts compliance time by 89%. Key features to look for:

  • Real-time alerts: Flag violations before they escalate.
  • Role-based access: Limit visibility to approved teams.
  • Auto-classification: Tag sensitive details like credit card numbers.

Choosing the Right Platform

Compare top 5 tools using this 14-point checklist:

PlatformBest ForROI Example
AtlanGDPR automationFintech saved $280K/year
BigIDShadow IT discoveryScanned 2.3M items in 11 mins
CollibraEnterprise scalingCut audit prep by 70%

Prioritize integrations. A healthcare client slashed manual work by 60% after linking their CRM to Atlan’s framework. Test demos with your team—usability beats flashy features.

Rolling Out Policies Across Your Organization

Launching new rules company-wide? A smooth rollout makes all the difference. Tide’s GDPR implementation saw 92% adoption in 3 weeks by focusing on two things: clear training and phased changes.

Change Management That Works

Break the rollout into 30-60-90 day phases:

  • First 30 days: Pilot with one department (e.g., HR).
  • Next 30: Expand to customer-facing teams.
  • Final 30: Company-wide launch with cheat sheets.

Assign “data champions” in each group. Reward early adopters—UNSW saw engagement jump 41% with small bonuses.

Training Teams Without Overwhelm

Ditch boring manuals. Sprinto’s control monitoring shows 3x better retention with:

  • 5-minute microlearning videos.
  • Chatbots answering policy questions instantly.
  • Quiz banks with pass/fail thresholds.

Track progress with dashboards. Aim for 90% certification rates like UNSW’s case study. Regular refreshers keep processes sharp.

Strong collaboration turns resistance into results. Start small, celebrate wins, and scale fast.

Monitoring and Maintaining Your Governance Framework

Your work doesn’t end after launching rules—continuous improvement keeps them effective. A strong framework thrives on regular checkups and real-time adjustments. Here’s how to stay ahead of risks and keep your system agile.

Setting Up Regular Policy Reviews

Don’t wait for audits to expose gaps. Schedule quarterly reviews using this 18-point checklist:

  • Auto-audit tools: Run compliance scans every 72 hours (e.g., Atlan’s dashboards).
  • Stakeholder feedback: Survey teams on pain points.
  • Regulation updates: Align with GDPR/HIPAA changes.

Sprinto’s real-time alerts reduce risk by flagging outdated rules before they cause issues.

Key Performance Indicators to Track

Measure progress with 5 critical metrics:

  1. Adoption rates: Are 90%+ teams following protocols?
  2. Incident response: Hit SLAs (e.g., critical fixes in ≤2 hours).
  3. Storage costs: Track savings from lifecycle automation.

Customizable dashboards for leadership show compliance scores at a glance. Integrate the PDCA cycle (Plan-Do-Check-Act) to refine processes quarterly.

Proactive monitoring turns policies into living systems. Start small, scale smart, and never stop optimizing.

Real-World Examples of Effective Data Governance

Want to see how top teams nail compliance? These case studies break it down. From healthcare to higher ed, real organizations prove smart frameworks drive results.

Healthcare Sector: Saving Lives and Sensitive Data

A Midwest hospital system slashed PHI breaches by 73% in 6 months. Their secret? Three practices:

  • Automated access logs flagged unusual activity instantly.
  • Quarterly staff training reduced human errors by 41%.
  • Encryption met database compliance standards, cutting breach costs.

Higher Education: Blueprints for Campus-Wide Success

UNSW Sydney’s 41-page handbook became a global template. Key features:

  • Clear standards for research data (e.g., anonymization protocols).
  • Student-friendly consent forms boosted opt-in rates by 29%.
  • Modular design lets departments adapt without chaos.

Bonus wins: A bank used AI monitoring to prevent $4.2M in fraud. A retailer unified customer profiles, lifting CLV by 29%. Proof? Smart rules deliver real ROI.

Taking Your Data Governance to the Next Level

Ready to future-proof your strategy? The landscape keeps evolving—stay ahead with these innovations. AI and blockchain are reshaping how teams manage information securely.

Explore emerging tech like immutable logs for audit trails. Set guardrails for AI tools (ChatGPT, etc.) to prevent misuse. Upskill your team with CDMP certifications—it boosts credibility and results.

Run annual maturity assessments. Track progress against industry benchmarks. Small tweaks keep your framework sharp as regulations change.

Start today—book a demo with Atlan or BigID. See how automation cuts compliance headaches by 80%+. The future belongs to those who adapt now.

FAQ

What exactly are data governance policies?

These are structured rules that define how your organization collects, stores, processes, and shares information. They help maintain accuracy, security, and compliance while aligning with business goals.

Why should my company invest in these policies?

Without clear guidelines, you risk security breaches, compliance fines, and poor decision-making due to unreliable information. Strong policies protect assets, build trust, and improve efficiency.

What’s the difference between security and privacy policies?

Security focuses on protecting systems from breaches, while privacy ensures personal information is handled according to laws like GDPR or CCPA. Both are critical but serve different purposes.

How often should we update our governance framework?

Review policies at least annually or when major changes occur—like new regulations, tech upgrades, or business expansions. Regular audits keep your approach effective.

Who needs to be involved in creating these rules?

A> Key players include IT teams, legal experts, department heads, and leadership. Collaboration ensures policies work for everyone while meeting compliance standards.

Can small businesses benefit from formal governance?

Absolutely! Even basic guidelines for data quality, access control, and retention help small teams avoid risks and build professional credibility.

What tools help enforce governance policies?

Platforms like Collibra, Informatica, or Microsoft Purview automate monitoring, access controls, and compliance tracking—saving time while reducing human error.

How do we get employees to follow new data procedures?

Combine training with clear documentation. Show how policies make their jobs easier while protecting the company. Regular reminders and leadership support drive adoption.
Database Management Data GovernanceData Handling Best PracticesData Security Policies

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