A strong Salesforce CI/CD pipeline has the potential to boost data quality with every release when paired with a comprehensive strategy.
Why It Matters: Poor data quality leads to costly errors, unreliable metrics, and a degradation of data security measures. This can result in costly outages and time-consuming mistakes.
- Poor data quality can lead to a reduction of efficiency in DevOps processes.
- Unreliable metrics impair your ability to make confident, data-driven business decisions.
Here are 7 ways Salesforce CI/CD supports strong data quality:
1. Automated Testing
Ample testing is a critical aspect of verifying proper coding structures and integration of changes prior to production. Failing to do so means you are simply trusting everything is done perfectly—and that’s rare.
Salesforce CI/CD tools facilitate automated testing to enable regular checks on data quality including validation rules, data integrity, and the overall functionality of the update.
This is a nonnegotiable part of a complete CI/CD strategy. Manual testing is possible, but it’s slow and error prone. Automating this process quickens the testing phase and ensures total coverage.
2. Version Control
Multi-developer teams often run into problems if the proper guardrails aren’t in place. Code overwrites and updates that don’t work together can cause a deployment to fail. Keeping track of these changes for easy revisions and testing clears up this confusion.
Integrating version control into your CI/CD strategy allows teams to maintain different versions of configurations, workflows, and data models.
Data quality is supported by easy rollbacks to previous states when any issues with the code are found.
3. Code Reviews
The code that makes up your applications or updates has a direct impact on the quality of data the product processes. Faulty applications will produce poor data. Bad code can create misfires that damage data and lead to inaccurate reporting.
An optimized Salesforce CI/CD pipeline will utilize an automated code review tool to ensure all changes adhere to best practices, minimizing the risk of introducing data quality issues.
Code reviews are a critical part of a contemporary CI/CD approach. If you can’t trust your code is 100% accurate, then you can’t trust the application it creates.
4. Incremental Updates
Releasing a new, complete application is a great feeling for a company. However, these major releases should not be the sole focus of a Salesforce DevOps pipeline. Bug fixes, patches, and updates are all essential for maintaining a functioning, secure platform.
CI/CD allows for small, incremental updates to Salesforce configurations and data models, reducing the chances of large-scale data issues.
Smaller releases can address issues in real time and provide a stronger barrier around data. Protection requires flexibility, and this is a great way to accomplish that.
5. Simplified Standardization
Proper handling of system data is more reliable when you can be sure your team members are all approaching this important consideration the same way. Standardizing processes is crucial to implementing repeatable systems with positive results.
CI/CD promotes the standardization of data handling processes, ensuring consistency and reducing the possibility of human errors that might affect data quality.
Human error is a major threat to data quality. Automating various aspects of the DevOps pipeline helps ensure your applications are stable, but you need to take precautions to ensure your team is treating data with the care it deserves.
6. Documentation
A paper trail is necessary for finding and rectifying data quality issues. Repeated mistakes will produce predictably negative results, so it’s important to fix the broken systems that produce poor products.
CI/CD encourages collaboration among teams and the documentation of changes made to Salesforce configurations, helping with tracing and rectifying data quality issues efficiently.
This also helps organizations in regulated industries keep track of compliance considerations for easy access in the event of an audit.
7. Continuous Monitoring
You can’t fix a problem if you don’t know it exists. Unrecognized problems are incredibly detrimental to data quality as they can cause unseen errors over an extended period of time. Utilizing the proper tooling to find these errors allows your team to fix them before they degrade your data.
Setting up monitoring and alerting mechanisms within CI/CD pipelines helps with identifying data quality issues in real-time, enabling prompt actions for resolution.
Salesforc CI/CD tools introduce multiple layers of protection against errors and mistakes that impact the quality of your data. Successfully implementing these tools with proper training gives you the best chance at achieving consistently high-quality data.
Next Step…
Data quality is an ongoing consideration. Every DevOps release is an opportunity to support a stronger, more secure Salesforce environment.
Check out our blog, 7 Tips for Increasing Quality in Every Salesforce Release Cycle, to learn more about maintaining high levels of quality with every release.