Implement a data classification policy

Implementing a data classification policy is crucial for understanding the criticality of your data and optimizing storage utilization. It enables organizations to allocate resources effectively and choose energy-efficient storage options, aligning data management with sustainability goals.

Best Practices

Implement a Comprehensive Data Classification Policy

• Identify and categorize all data types based on their criticality to business operations. This helps in understanding which data is essential and which can be archived or deleted.
• Define clear classification tiers (e.g., high, medium, low) and assign energy-efficient storage solutions based on these categories to optimize costs and energy usage.
• Establish a regular review process to ensure data is always classified correctly and adjust storage allocations as business needs change, helping to avoid unnecessary resource consumption.
• Integrate automation tools that can automatically classify data as it is created or modified. This reduces manual overhead and ensures consistent application of the policy.
• Train employees on the importance of data classification and its impact on sustainability. Awareness can lead to better habits in data handling and storage.
• Leverage cloud-native services that allow you to reinforce data policies, such as automated lifecycle management features to transition data to appropriate storage tiers or delete data over time.

Questions to ask your team

• Have you implemented a formal data classification policy?
• How often is the data classification policy reviewed and updated?
• Do you regularly assess the criticality of data to business outcomes?
• Are there clear guidelines on which storage tiers are used for each classification?
• How is the data classification communicated to your teams?
• What processes are in place for lifecycle management of data as its classification changes?
• How do you ensure compliance with your data management and classification policies?

Who should be doing this?

Data Governance Officer

• Establish and oversee the data classification policy.
• Ensure compliance with data management standards related to sustainability.
• Collaborate with stakeholders to define criticality levels for data.

Data Architect

• Design data storage solutions that align with the classification policy.
• Identify appropriate energy-efficient storage tiers based on data criticality.
• Assess and recommend technologies to optimize data storage costs and efficiency.

Data Analyst

• Analyze data usage patterns to identify opportunities for data lifecycle management.
• Provide insights on data value to inform classification and storage strategies.
• Monitor and report on efficiency gains from implemented storage policies.

IT Operations Manager

• Implement storage solutions based on data classification.
• Manage the lifecycle of data, transitioning to more efficient storage as needed.
• Ensure proper data deletion practices are followed for outdated data.

Compliance Officer

• Ensure that data management practices comply with regulatory requirements.
• Monitor the implementation of the data classification policy for adherence.
• Conduct audits to evaluate the effectiveness of sustainability initiatives.

What evidence shows this is happening in your organization?

• Data Classification Policy Template: A standardized template defining how data should be classified, detailing the categories and policies for each classification level.
• Data Classification Training Guide: A guide that provides best practices, methodologies, and instructions for employees on correctly classifying and handling organizational data.
• Data Classification Adoption Strategy: A strategic plan for rolling out data classification across the organization, identifying timelines, resources, and success metrics.
• Data Classification Matrix: A structured matrix mapping classification levels to appropriate storage tiers, access control requirements, and retention schedules.

Cloud Services

AWS

• Amazon S3: S3 offers different storage classes for different access patterns and lifecycle management policies to move data to lower-cost, energy-efficient storage options.
• Amazon Data Lifecycle Manager: Automates the creation, retention, and deletion of EBS snapshots, allowing you to manage data lifecycle and reduce unnecessary storage costs.
• AWS Storage Gateway: Integrates on-premises environments with cloud storage, providing flexibility in data classification and management.

Azure

• Azure Blob Storage: Offers tiered storage options to efficiently manage data, including hot, cool, and archive tiers based on data usage needs.
• Azure Archive Storage: A cost-effective storage solution for data that is rarely accessed, supporting better management of data lifecycle.
• Azure Data Lake Storage: Provides scalable, cost-effective storage for big data analytics with capabilities for lifecycle management to optimize storage costs.

Google Cloud Platform

• Google Cloud Storage: Offers multiple storage classes to help you store, manage, and automatically transition data between classes based on defined access patterns.
• Google Cloud Data Lifecycle Management: Enables you to manage your storage classes and automatically delete outdated data as per your defined policies.
• BigQuery: Facilitates the analysis of data stored in Cloud Storage, helping you classify and understand your data’s value to drive efficient storage management.