Salesforce Testing

What is Salesforce Testing?

Salesforce testing is the process of ensuring the data quality, functionality, and performance of a Salesforce implementation or Salesforce migration. It majorly involves application testing, and data testing to meet business requirements.

Types of Salesforce Testing

1. Application Testing
   1. Functional Testing: Verifying that the system performs as expected based on specified requirements.
   2. Performance Testing: Evaluating the system’s response time and scalability under different load conditions.
   3. Security Testing: Identifying vulnerabilities and protecting sensitive data.
2. Data Testing: Validating data integrity, accuracy, and consistency during migration and updates.

As discussed above, while Salesforce testing encompasses various areas, this article will specifically focus on Salesforce data testing. Let’s delve deeper into this below.

Salesforce Data Testing

Here are some key challenges with salesforce data testing:

• – Application testing tools like Selenium and JMeter excel at application testing, they aren’t well-suited for testing data centric systems like Salesforce.
• – The data testing problem is further compounded by challenges that Salesforce does not allow direct access to the database, requiring SOQL (Salesforce Object Query Language) for data manipulation.

A Salesforce instance can have millions of customers records, necessitating thorough testing and certification. Proper data testing ensures business continuity, regulatory compliance, and a seamless customer experience during the transition.

Salesforce Migration Process

A successful project encompasses not only sunsetting and migrating the Salesforce instance, but also archiving legacy data and retesting impacted downstream systems.

Migrating data from one Salesforce instance to another often involves more than a simple transfer. Here, we’ll explore the key aspects involved in a comprehensive Salesforce migration strategy:

1. Sunsetting and Data Migration: This initial phase involves decommissioning the existing legacy Salesforce instance and seamlessly transferring its data to the new target instance.
2. Legacy Data Archiving: To ensure historical data remains accessible, it’s crucial to archive the legacy Salesforce data. This typically involves transferring the data to a secure archive, such as a dedicated SQL Server database.
3. Data Reconciliation Testing – On-Premises Data Lake: Following migration, data consistency needs to be verified. Data reconciliation testing compares the newly migrated data in the new Salesforce instance to its corresponding data stored in the on-premises data lake.
4. Data Reconciliation Testing – Cloud Data Lake: Modern data storage often involves cloud-based data lakes. Here, reconciliation testing ensures the accuracy of migrated data from the new Salesforce instance to the Snowflake cloud data lake.

Salesforce Data Reconciliation Testing with iceDQ:

A critical aspect of any Salesforce migration is ensuring the accuracy and consistency of the migrated data across various target environments. This typically involves data reconciliation testing, which compares the migrated data to its source in the original Salesforce instance, as well as any additional data destinations.

iceDQ enables automated data reconciliation testing across different salesforce instances, on-prem databases, data lakes and cloud databases as follows:

A1 Salesforce vs. Salesforce reconciliation.
B1 Salesforce vs. SQL Server database reconciliation.
C1 Salesforce vs. Data Lake (Hive) reconciliation.
D1 Data Lake (Hive) recon vs Snowflake reconciliation.

iceDQ’s Native Salesforce Support & Data Reconciliation

In this section, we’ll explore screenshots of iceDQ’s native support for Salesforce and reconciliation rules configuration.

Above interface shows iceDQ’s native Salesforce support (Figure 3) with familiar workbench interface (A) and iceDQ’s support for SOQL (B) queries simplifies data reconciliation for any salesforce testing project.

Legacy vs. New Salesforce Reconciliation

Using iceDQ you can create data reconciliation tests between Legacy and New Salesforce data (Fig 4). In the above figure you can see that, CONTACT_TABLES were compared (A & B) using “modid” as the join key. “A-B” & “B-A” result type checks in C ensures both the tables match post-migration.

Reasons to adopt iceDQ

1. Cross-Platform Reconciliation: iceDQ can do data reconciliation testing across multiple platforms. Cross-platform support for data reconciliation across systems, files and databases.
   1. Legacy Salesforce Instance vs. New Salesforce Instance
   2. Legacy Salesforce Instance vs. Database
   3. New Salesforce Instance vs. Data Lake
2. Full Data Volume Testing: iceDQ enables full volume testing for millions of records ensuring accuracy of each customer record.
3. Proof of Testing & Regulatory Compliance: iceDQ not only automates the snowflake data testing but also enable creation documentation
4. Native Salesforce (SOQL): It supports writing of SOQL just like any other DB.
5. Automation: Generate audit trails for regulatory compliance and automate testing with low-code/no-code options.

“The ease of integrating iceDQ with Salesforce was a major advantage. It allowed our team to independently perform comprehensive testing without relying on developer resources. This accelerated our testing process and ensured timely project completion.”
– Director Data Quality

Expected Achievements and Gains with iceDQ:

iceDQ, an automated data testing platform, simplifies the process with its native Salesforce connectivity (including SOQL support) and robust reconciliation capabilities. It allows you to compare data across diverse environments like Salesforce, SQL Server, Data Lake, and Snowflake, ensuring consistency throughout the migration. iceDQ automates complex data checks, enabling efficient testing at scale and guaranteeing data accuracy during migration.