Why are data retention policies important?

Organizations need data retention policies to protect sensitive data, comply with regulatory requirements, and streamline data management. These rules minimize the risk of data breaches, reduce storage expenses, and promote responsible and effective data practices by establishing precise criteria for how long data should be kept and when it should be removed.

What Is a data retention period?

The data retention period is the set amount of time that an organization maintains certain kinds of data before deleting or archiving it. The data retention period may vary based on regulatory requirements and the organization's need to maintain data.

What are the risks of non-compliance with data retention regulations?

Non-compliance with data retention regulations can expose organizations to legal penalties, reputational damage, and loss of customer trust. In addition, noncompliance with prescribed retention periods may also lead to unauthorized access, data breaches, etc.

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Secure sensitive data everywhere from hybrid multicloud to SaaS

View

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Establish controls for safe adoption of AI technologies including GenAI

View

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Unblock the biggest impediments for Safe Adoption of AI Copilots like Microsoft 365 Copilot

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Data Access Intelligence & Governance
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View

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Discover shadow and cloud-native assets and accurately classify data

View

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View

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Analyze breach impact & automate notifications to affected individuals

View

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Understand data lineage and secure real-time streaming data

View
Build safe enterprise AI systems

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Implement rule-aware AI copilots across your organization’s data anywhere

View

Data Vectorization and Ingestion
Extract info from complex Unstructured Files, convert it into AI-ready formats, and sync to vector databases

View

Data Curation and Sanitization for AI
Transform raw, unstructured files into data ready for model training and tuning

View

Context-aware LLM Firewalls
Protect AI interactions with intelligent retrieval, response, and prompt firewalls

View

Unstructured Data Governance
Manage and govern unstructured data to enable its safe use with generative AI

View
Govern data for safe innovation

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Unstructured Data Governance
Manage unstructured data to enable safe use with generative AI

View

Data Access Governance
Monitor sensitive data access and prevent unauthorized use

View

AI Governance
Establish controls for safe adoption of AI technologies including GenAI

View

Data Catalog
Enable users to easily find, understand, trust and access the data they need

View

Data Lineage
Automatically track changes and transformations of data throughout its lifecycle

View

Data Quality
Conduct data quality checks and validation across various data types

View
Automate data privacy operations

Data Mapping Automation
Manage your entire data mapping lifecycle and automate RoPA reports

View

AI Governance
Comply with emerging AI regulations and ensure safe use of AI

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Data Subject Request Automation
Automate entire DSR lifecycle from consumer request intake to secure report delivery

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Automate your entire assessment lifecycle and demonstrate compliance

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Manage your first-party and third-party consent lifecycle from scanning to reporting

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Breach Management
Automate your incident management and optimize notifications to users & regulatory bodies

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Use automation to audit and improve compliance with global regulations and industry standards

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