Optimize Data with Archive

Learning Objectives

After completing this unit, you’ll be able to:

• Explain how data is stored and archived in Archive.
  
• Compare archiving policies with purging policies.
  
• Explain retention periods.
  
• Assess key considerations before configuring Archive.
  
• Describe how Storage Analyzer can help you evaluate your archiving strategy and policies.
  

Archive Salesforce Data

The interaction between Archive and Salesforce data is seamless and automated. When you set up Archive, you define specific criteria for which records should be archived, such as records that haven't been modified for a certain period or records that meet specific business rules. Once these criteria are defined, Archive automatically identifies and moves the eligible records from your Salesforce instance to its own secure archive. This process ensures that your Salesforce environment remains optimized for current operations while maintaining a comprehensive historical record.

Additionally, Archive provides tools for easy retrieval and reporting of archived data. Users can search and access archived records as needed, which ensures that historical data remains accessible for compliance audits, reporting, and other business needs. The integration with Salesforce keeps the archived data consistent and up-to date, maintaining the integrity of your data management processes. Overall, Archive enhances your data management capabilities by providing a reliable and efficient solution for archiving and retrieving Salesforce data.

Storage, Backups, and Archived Data: Know the Difference

Salesforce admins manage millions of records across various clouds. Understanding the distinction between storage, backup, and archiving is essential for effective data management.

Salesforce storage refers to the space used for storing data associated with Salesforce objects (such as accounts, contacts, opportunities, and cases), plus files and file attachments. You pay Salesforce for the storage space that you use. Exceeding your storage limits increases your storage cost.

Backups create complete copies of your entire Salesforce org, including data, metadata, schema, and file attachments to enable quick restoration after accidental loss of data or corruption. For example, you might use Salesforce Backup and Recover to automatically create complete, secure copies of Salesforce data and metadata on a scheduled basis, and to restore selected records and files back into the org as part of your data recovery strategy.

Archive moves historical, rarely used data from production ‌into low-cost storage for long-term retention. For example, your historical data might include the following kinds of data.

• Old customer accounts that haven’t been active for several years.
  
• Expired contracts that have fulfilled their terms but must be retained for legal or compliance reasons.
  
• Employee records for people who no longer work at your company.
  
• Closed support cases that offer account context.
  
• Sales opportunities that might still provide valuable historical pricing or competitive information.
  

Use Archive to store this inactive data to reduce storage costs and improve Salesforce performance and efficiency.

The key difference between backups and archiving lies in their purposes: Archiving serves as an organizational strategy for long-term data retention and storage optimization, while backups function as your insurance policy for disaster recovery. It’s important to remember, however, that archiving doesn’t replace backup or vice versa—these strategies compliment each other in your data management toolkit.

Assess Key Considerations

Before implementing your archiving strategy, it’s critical to start by asking some essential questions. First, which roles within your company can set up archiving policies? For example, will system administrators define your policies? Who are the stakeholders that can contribute information and guidance about inactive data? Who can identify large-volume objects contributing to storage limits? These stakeholders are critical to helping you create an effective archiving strategy.

Of course, some of the most important considerations are to identify which data is consuming excessive storage and slowing down system performance, and to determine which records should be archived based on business needs and compliance requirements.

Furthermore, understand your company’s data retention policy and the criteria you’ll use to identify inactive data. These policies and criteria should align with regulatory requirements, such as Europe’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), the Health Insurance Portability and Accountability Act (HIPAA), and industry specific regulations. These regulations can require extended data retention and include requirements for immediate data removal. Keeping track of these global and diverse requirements can be complex–an automated solution can help your organization stay compliant.

Also, be sure to determine the appropriate archiving frequency for your organization, whether it’s daily, monthly, quarterly, or semi-annually. Furthermore, determine the day and time at which your archive policies will run. For example, do you want to run your policies during off hours so that your policy jobs don’t compete for system resources or degrade the performance of your production org? Create and manage archiving policies that automatically archive objects based on your defined data retention policy. Also, ensure that the right people are notified and responsible for executing queries to delete or move data. Be sure that your archiving policies maintain parent-child relationships so that related objects and attachments are preserved if the information needs to be accessed later.

Finally, consider who needs to see and access your archived records. Among this group, who will have permissions to unarchive records? For example, system admins might apply the principle of least privilege, where users are granted the minimum access permissions necessary to perform their job, and nothing more. This principle ensures that personal data is accessed only by authorized personnel with legitimate business reasons. It also reduces the risk of unauthorized access or data breaches. Incorporating this principle into your data strategy can help you comply with regulatory requirements for appropriate safeguards, demonstrate data protection by design, maintain defensible audit trails of data access, and reduce overall risk when managing historical data.

You can track the effectiveness of your archiving solution by monitoring and reporting on activities, data usage, and archived storage. You’ll learn more about roles and permissions later.

Archiving Policies and Purge Polices: Which to Choose?

As you begin to plan and implement your archiving strategy, consider two key policy types that determine how long your archived records remain stored: archiving policies and purge policies.

Archiving policies are based on retention periods, which are like expiration dates for your archived records. They’re typically based on legal requirements or organizational needs. After a retention period expires, the system automatically removes the data from your archive. Implementing archiving policies with defined retention periods is an effective way to automatically manage archived data lifespans.

Use purge policies when you require more control beyond standard retention periods. With purge policies, you create the criteria that determine when to selectively remove archived data. These criteria override the dates established by your retention settings. In other words, retention is a time-based deletion mechanism built into your archiving policy, whereas purging provides you with the flexibility to adapt to changing business needs or compliance requirements. For example, you might require a purging policy to ensure that you can appropriately respond to data deletion requests (such as the Right to be Forgotten request) in a timely manner. Purged data can't be retrieved, so think carefully about who'll have purge policy permissions in your org!

So should you use archiving policies or purge policies? Consider using both to maintain complete control over your archived data throughout its entire lifecycle.

Production to Archive: The Data Journey

The movement of records from your active Salesforce environment to your archive follows a structured process designed to maintain data integrity while optimizing your production org performance. The transition begins with carefully defined archiving policies and concludes with accessible historical data stored outside your production org.

Before any data moves, you create archiving policies that define exactly which records should be archived based on specific criteria. These policies can include conditions like record age (for example, cases closed for more than 2 years), status fields (for example, opportunities marked as Closed or Lost), or custom criteria specific to your business. Your archiving policies are the blueprint for how data moves into Archive and when.

Matt, the sys admin at Cumulus Cloud, works with his stakeholders to determine their archive policy. They need a policy that archives all closed cases that are older than 3 years and all opportunities marked as 'Closed Lost' after 18 months. Additionally, he configures some custom criteria to archive any records that haven’t been accessed or modified in the past 12 months.

After your policies are defined and activated, the Archive system runs selection queries against your Salesforce org to identify records that meet your defined criteria. The system identifies primary records, related records, and attachments–and identifies when this data should move together to maintain data relationships.

You determine when and how frequently to run your archiving jobs. Many companies run these jobs during off-peak hours to minimize impact on the production org. To increase performance, Archive runs multiple archiving jobs in parallel and can archive tens of millions of records a day.

Archive automatically archives master-detail child records with the parent. You can also define your policy configuration to automatically archive lookup child records with the parent, as well. When setting up your policy, it’s important to understand Archive data hierarchy. This includes how master-detail relationships and lookup relationships are handled, and whether you need a single policy or multiple policies to retain data relationships and to preserve the context and value of your historical data.

Even though your archived data is moved out of your production org, your users can still access that information. Use Archive Widgets for Lightning to display archived data as related lists in Salesforce. This ensures that your users can still access and view the data in the familiar Salesforce interface. Archive Widgets give you control over who can view archived data and who can unarchive that data.

Evaluate Archive Strategies and Policies with Storage Analyzer

After you set up your policies and begin archiving data, analyze your archive strategy to see what data is being stored, how frequently that data is accessed, and whether your retention policies correctly comply with data privacy regulations.

Matt, the sys admin for Cumulus Cloud Corporation, has similar questions. Archiving data improved system performance, but he still needs to address the rising costs of data and file storage, and he’s uncertain about which Salesforce objects and related files are consuming the most storage.

Then he discovers the Archive Storage Analyzer, a dashboard in Archive that provides a comprehensive analysis of data and file storage in the production org. Storage Analyzer is a visual tool that provides an overview of the top objects consuming storage and Cumulus Cloud’s usage history.

Now, Matt can incorporate the Storage Analyzer into his regular workflow. He can run regular audits to identify patterns and optimization opportunities, generate reports about the company’s data management practices to demonstrate compliance with privacy regulations, and use the analysis to help forecast future storage requirements.