Mastering Data Archival Techniques: A Comprehensive Guide

In today’s data-driven business landscape, managing vast amounts of information efficiently is critical to maintaining optimal system performance, regulatory compliance, and cost-effectiveness. Data archival, the process of storing inactive data for long-term retention, is a fundamental practice for organizations, particularly those utilizing platforms like Salesforce. Understanding the nuances of data archival techniques is pivotal to ensuring seamless operations and future-proofing your organization’s data management strategy.

The Essence of Data Tiering & Tiering Pyramid

Data tiering is the practice of categorizing data based on its frequency of use and importance to the organization. This categorization allows for optimized storage and retrieval, enhancing system performance. The tiering pyramid is a conceptual framework that classifies data into different tiers:

Tier 1: Operational Data (Full Search & Reporting)

Tier 1 encompasses real-time operational data actively used for day-to-day business processes. This data must be readily accessible for immediate search, reporting, and decision-making. Salesforce’s platform is an ideal repository for this tier due to its quick access capabilities and seamless integration with operational processes.

Tier 2: Historical Data (Limited Search & Reporting)

As data ages, its frequency of access decreases. Tier 2 holds historical data that is still relevant but requires limited search and reporting functionalities. This data is essential for trend analysis and long-term business strategies. Leveraging Salesforce’s platform for this tier may be feasible, albeit with specific optimizations, to effectively manage the reduced search and reporting requirements.

Tier 3: Archived Data (External Platform)

Archived data, while no longer actively used, holds immense value for regulatory compliance, legal requirements, and potential future references. Tier 3 involves moving this data to an external platform, such as a data lake, allowing for cost-efficient storage and controlled API access for retrieval.

 

Exploring Archival Approaches

Effective data archival demands carefully considering the platform’s capabilities and the organization’s needs. Here are three key approaches to data archival within the Salesforce ecosystem:

Approach 1 – Archiving on Platform (Using Record Archiving Indicator)

Salesforce offers a built-in mechanism for archiving data using the Record Archiving Indicator. This approach involves flagging records as archived within standard or custom objects. While this keeps data within the Salesforce environment, it may impact performance due to increased data volume. Effective data partitioning and indexing are essential to ensure smooth operations.

Approach 2 – Archiving on Platform (Big Objects)

Salesforce’s Big Objects provide a specialized storage mechanism for large volumes of data with infrequent access requirements. This approach suits Tier 2 and Tier 3 data, allowing seamless integration with existing Salesforce processes while maintaining scalability and performance.

Approach 3 – Archiving off Salesforce Platform (Data Replication to a Data Lake)

For Tier 3 data, where long-term retention is essential, archiving of the Salesforce platform is a pragmatic choice. Replicating data to a data lake offers cost-effective storage and control over API access. This approach minimizes the impact on Salesforce performance and aligns with the concept of data tiering.

 

Crafting Your Data Archival Strategy

Devising an effective data archival strategy involves deeply understanding your organization’s needs, compliance requirements, and the platform’s technical capabilities. Here’s a roadmap to guide your strategy:

  1. Assessment: Analyze your data landscape to determine what data falls into each tier and its associated requirements.
  2. Platform Optimization: Optimize your Salesforce platform depending on the chosen archival approach. Implement data partitioning, indexing, and leverage platform features like Big Objects.
  3. Archival Policy: Define a clear archival policy that outlines when data transitions between tiers and when it’s eligible for archiving.
  4. Implementation: Based on your chosen approach, implement the necessary processes and tools for data archival, whether within the Salesforce platform or an external data lake.
  5. Testing and Monitoring: Rigorously test the archival processes and set up monitoring to ensure that data is being archived correctly and can be retrieved when needed.
  6. Documentation and Training: Document your archival strategy and provide training to relevant teams. This ensures consistency in data management practices across the organization.
  7. Continuous Refinement: Regularly revisit your data archival strategy to adapt to evolving business needs, compliance regulations, and technological advancements.

 

When to Archive Data Instead of Migrating

Choosing between archiving and migrating data is a crucial decision in data management. Here’s when archiving is the preferred option:

  1. Compliance and Legal Obligations: Archiving keeps data accessible for compliance and legal purposes without complex migrations.
  2. Historical Analysis: Data needed for historical analysis or reference is best archived to preserve insights and minimize disruption.
  3. Cost-Efficiency: Archiving is often more cost-effective than data migration, saving resources and technology investments.
  4. Minimizing Disruption: Archiving has minimal impact on daily operations compared to potentially disruptive migrations.
  5. Long-Term Retention: Archiving suits data retention over extended periods, as it’s designed for long-term storage.
  6. Data Tiering Alignment: Align archiving with data tiering to maintain efficient practices.
  7. Scalability: Archiving helps manage data growth gracefully, especially when dealing with large volumes.

 

Data archival is not just about storage; it’s a strategic practice that impacts your organization’s efficiency, compliance, and future readiness. Mastering the art of data tiering and choosing the right archival approach is your key to unlocking optimal performance and data governance. By implementing a well-thought-out data archival strategy, you position your organization as a thought leader in efficient data management and set the stage for continued success in the dynamic world of business technology.

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