AI Driven Intelligent Data Retention and Deletion Workflow Guide

Intelligent Data Retention and Deletion Workflow

1. Data Collection

1.1 Identify Data Sources

Utilize AI-driven tools to map out data sources within the telecommunications infrastructure, including customer interactions, billing systems, and network performance data.

1.2 Data Ingestion

Implement ETL (Extract, Transform, Load) processes using AI tools like Apache NiFi or Talend to automate data ingestion from identified sources.

2. Data Classification

2.1 Categorize Data Types

Employ machine learning algorithms to classify data into categories such as personal, sensitive, and operational data.

2.2 Risk Assessment

Utilize AI-based risk assessment tools like IBM Watson or Microsoft Azure’s AI capabilities to evaluate the sensitivity and compliance requirements of classified data.

3. Data Retention Policy Implementation

3.1 Define Retention Periods

Leverage AI analytics tools to analyze regulatory requirements and business needs to define appropriate data retention periods for each data category.

3.2 Automate Policy Enforcement

Use policy management tools such as OneTrust or TrustArc to automate the enforcement of data retention policies across the organization.

4. Data Monitoring

4.1 Continuous Monitoring

Implement AI-driven monitoring solutions like Splunk or Datadog to continuously track data usage and compliance with retention policies.

4.2 Anomaly Detection

Utilize AI algorithms to detect anomalies in data access patterns that may indicate unauthorized use or potential breaches.

5. Data Deletion Process

5.1 Trigger Deletion Protocols

Set up automated triggers using AI tools to initiate deletion protocols once data retention periods expire.

5.2 Secure Data Deletion

Employ secure deletion tools such as Blancco or SecureErase to ensure that data is irretrievably deleted in compliance with privacy regulations.

6. Documentation and Reporting

6.1 Maintain Audit Trails

Utilize AI-driven logging tools to maintain comprehensive audit trails of data retention and deletion activities.

6.2 Generate Compliance Reports

Automate the generation of compliance reports using business intelligence tools like Tableau or Power BI to ensure transparency and accountability.

7. Review and Optimization

7.1 Periodic Workflow Review

Conduct regular reviews of the workflow using AI analytics to identify areas for improvement and optimization.

7.2 Update Policies and Tools

Continuously update data retention and deletion policies based on evolving regulations and advancements in AI technologies.