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Part 1: Why Creating a Data Asset is Important

Before discussing the steps, it is important to understand the objective.

Creating a Data Asset helps the organization:

• Maintain a centralized data inventory
• Identify Personal Identifiable Information (PII)
• Assign ownership and accountability
• Define data retention periods
• Assess risk severity
• Map data to business processes
• Prepare for audits and regulatory reviews

Without structured data asset registration, organizations struggle with visibility, compliance gaps, and audit failures.

Part 2: Step-by-Step Process to Create a Data Asset

Step 1: Navigate to Data Catalog

• Open the Privacy or Governance module
• Go to the Data Catalog section
• Click on “Create” or “Add Data Asset”

The “Add Data Asset” form will open.

This form ensures structured and standardized data registration.

Step 2: Complete the Data Asset Form

Each field in the form has compliance and governance significance.

1. Source System

   This identifies where the data originates.

   Examples:

   • CRM system
   • HRMS
   • ERP
   • Visitor Management System
   • Internal governance platform

   Why it matters:

   • Enables system-level traceability
   • Helps in system audits
   • Supports breach impact analysis
   • Improves third-party risk assessment

   Knowing the source system is critical for data mapping and regulatory documentation.

2. Table Name

   This represents the database table where the data is stored.

   Examples:

   • accounts
   • admin_accounts
   • account_sessions
   • employee_records

   Why it matters:

   • Helps technical teams locate the data
   • Strengthens database-level governance
   • Supports IT and audit collaboration

   This improves precision in compliance documentation.

3. Column Name

   This identifies the specific data field within the table.

   Examples:

   • email
   • ip_address
   • phone_number
   • external_ref

   Why it matters:

   • Enables column-level governance
   • Reduces ambiguity
   • Improves security configuration
   • Supports forensic analysis

   Column-level registration ensures granular data control.

4. Data Type

   Defines the format of the data stored.

   Examples:

   • varchar
   • integer
   • text
   • date
   • boolean

   Why it matters:

   • Helps apply validation rules
   • Supports encryption strategy
   • Assists database integrity checks
   • Enables structured monitoring

   Understanding data type strengthens technical governance.

5. Manual PII Tag

   This allows classification of data as Personal Identifiable Information.

   Examples:

   • Email Address
   • Phone Number
   • Main IP
   • Government ID

   Why it matters:

   • Identifies regulatory exposure
   • Enables privacy risk assessment
   • Supports Data Protection Impact Assessments (DPIA)
   • Improves subject rights management

   Manual tagging ensures contextual accuracy beyond automated detection.

6. Business Process Mapping

   This connects the data asset to a business function.

   Examples:

   • Visitor Ticketing & Entry Management
   • Employee & Performer Management
   • Merchandise Sales & Order Fulfillment
   • Visitor Feedback & Analytics

   Why it matters:

   • Ensures lawful purpose limitation
   • Supports compliance audits
   • Enables process-level risk assessment
   • Prevents unnecessary data collection

   Data must always serve a defined business objective.

7. Owner

   Assign a responsible individual or role.

   Examples:

   • Compliance Manager
   • Head of Compliance
   • IT Manager
   • Data Protection Officer

   Why it matters:

   • Establishes accountability
   • Enables approval workflows
   • Ensures periodic review
   • Strengthens governance discipline

   Ownership eliminates ambiguity in responsibility.

8. Retention Schedule

   Defines how long the data will be stored.

   Examples:

   • Visitor Records – 24 Months
   • Employee Records – Contract Term + 5 Years
   • Transaction Records – 7 Years

   Why it matters:

   • Prevents over-retention
   • Reduces legal liability
   • Lowers storage cost
   • Improves compliance with data protection regulations

   Retention governance is a core requirement in privacy frameworks.

9. Risk Severity

   Indicates the impact level of the data asset.

   Levels:

   • Low
   • Medium
   • High

   Why it matters:

   • Determines control strength
   • Influences monitoring frequency
   • Prioritizes security investment
   • Supports risk reporting

   Risk-based classification strengthens enterprise risk management.

Step 3: Submit the Data Asset

After filling all required fields:

• Click Submit
• The system validates inputs
• The data asset is registered in the Data Catalog

Once submitted, the asset becomes visible in the centralized inventory.

Part 3: Viewing a Created Data Asset

After creation, clicking on the listed data asset opens a detailed view panel.

This detailed view provides a comprehensive governance summary.

Information Displayed in the Details Panel

Governance Value of This Workflow

Creating and reviewing data assets delivers structured benefits:

• Centralized data visibility
• Clear ownership model
• Automated and manual classification
• Risk-based monitoring
• Defined retention governance
• Regulatory audit readiness
• Improved breach impact analysis
• Enhanced accountability

It transforms scattered database fields into controlled and governed enterprise assets.

Integration with Privacy and Risk Management

Data asset registration directly supports:

• Enterprise Risk Management (ERM)
• Information Security Management
• ISO 27001 compliance
• Data Protection regulatory frameworks
• Internal audit processes
• Third-party risk assessments

A well-maintained Data Catalog becomes the backbone of compliance reporting and security oversight.

Conclusion

The process of creating a Data Asset and reviewing its detailed configuration is not merely administrative. It is a foundational governance activity that strengthens transparency, accountability, and regulatory compliance.

By systematically documenting source systems, database structures, PII classification, ownership, risk severity, business purpose, and retention schedules, organizations build a resilient and audit-ready data governance framework.

Structured data asset management ensures that information is not just stored, but responsibly governed, securely managed, and strategically controlled throughout its lifecycle.