Use policies to manage the lifecycle of your datasets

Effective data management is crucial for sustainability goals. By implementing lifecycle management policies, organizations can automate data deletion and reduce unnecessary storage use, minimizing their environmental footprint.

Best Practices

Implement Automated Data Lifecycle Policies

• Define data lifecycle policies that specify when data should be moved to less expensive storage or deleted based on access patterns and business needs. This reduces the amount of provisioned storage, thereby minimizing environmental impact.
• Use cloud-native tools such as Amazon S3 Lifecycle Policies to automatically transition data to lower-cost storage classes or delete it after a specified period. This way, you enforce policies without manual intervention, ensuring compliance and efficiency.
• Regularly audit and review these policies to adapt to any changes in data usage or business requirements. This ensures relevance and helps in maintaining optimized storage costs.
• Educate your team on the importance of data lifecycle management for sustainability goals, fostering a culture that values responsible data handling.

Questions to ask your team

• Do you have policies in place to automatically delete unused or obsolete data?
• How frequently do you review and update your data management policies?
• Are your data categorization and lifecycle policies aligned with your sustainability goals?
• What mechanisms do you have to monitor data usage and identify datasets that can be archived or deleted?
• How are you ensuring that your data lifecycle policies are being enforced across all teams and departments?

Who should be doing this?

Data Steward

• Define and implement data lifecycle management policies.
• Ensure compliance with data management policies across all datasets.
• Monitor and assess data usage patterns to identify opportunities for optimization.
• Coordinate with teams to establish criteria for data retention and deletion.
• Facilitate training for staff on lifecycle management practices.

Cloud Architect

• Design and implement architecture that supports automated data lifecycle management.
• Select appropriate storage technologies based on data value and usage patterns.
• Implement configurations that enable efficient data storage and retrieval.
• Collaborate with the Data Steward to ensure alignment on data strategy.

Compliance Officer

• Review and audit data management practices to ensure compliance with regulations.
• Ensure that data deletion processes are documented and followed.
• Assess risks associated with data retention and implement mitigation strategies.
• Collaborate with Data Stewards to align compliance efforts with lifecycle policies.

Business Analyst

• Analyze business data usage and identify value drivers.
• Provide insights into how data management policies align with business goals.
• Assist in defining the criteria for data classification and lifecycle stages.
• Work with stakeholders to prioritize data sets based on business value.

What evidence shows this is happening in your organization?

• Data Lifecycle Management Policy: A formal policy outlining how data is classified, stored, transitioned to lower-cost storage over time, and eventually deleted once it reaches end-of-life.
• Retention Policy Checklist: A step-by-step checklist to verify that dataset retention and deletion timelines comply with regulatory and organizational requirements.
• Storage Tiering Plan: A detailed approach to utilize various storage classes, ensuring data is automatically moved to more cost-effective storage tiers based on usage patterns.
• Automated Deletion Runbook: An operational guide for configuring and monitoring automated data deletion tasks, including scripts, triggers, and alerting methods.
• Lifecycle Management Dashboard: A visual dashboard displaying metrics such as storage usage trends, policy compliance, and upcoming data deletion schedules.

Cloud Services

AWS

• Amazon S3: Amazon S3 provides lifecycle management features that allow you to automatically transition data to less expensive storage classes or delete it when no longer needed, thus optimizing storage costs and supporting sustainability efforts.
• AWS Data Lifecycle Manager: This service automates the creation, retention, and deletion of EBS snapshots, helping to ensure that only necessary data is retained and thus reducing storage usage.
• AWS Glue: AWS Glue can help you classify and organize data for analysis, allowing you to understand data usage patterns and inform policies for archiving or deleting unused datasets.

Azure

• Azure Blob Storage: Azure Blob Storage supports lifecycle management policies that allow users to automatically move blobs to cooler storage tiers or delete them after a certain period, reducing storage costs and environmental impact.
• Azure Data Factory: Azure Data Factory can orchestrate data movement and transformation workflows, which allows you to analyze data usage, making informed decisions about data lifecycle management.

Google Cloud Platform

• Google Cloud Storage: Google Cloud Storage offers Object Lifecycle Management, enabling automatic transition of objects to cheaper storage classes or deletion as per defined lifecycle policies.
• Google BigQuery: BigQuery allows for data analysis and can help identify underutilized datasets, supporting effective data lifecycle management and retention policies.