1. Duplicate data
Duplicate entries are one of the most frequent issues arising during Salesforce Data Migrations. These discrepancies can cause inefficiencies, inaccurate reporting, and a frustrating user experience.
To tackle this, an in-depth audit of your dataset is often required to identify duplication patterns. In recent migrations, we have used custom SQL scripts, which eliminate duplicate entries, ensuring clean and accurate data is migrated into Salesforce.
A key factor is understanding the root causes and identifying why the duplicates existed in the first place which allows processes to be implemented to prevent duplication from occurring post-migration, ensuring long-term data integrity.
2. Data mapping
In Salesforce migrations, a common issue is improper data mapping, which will lead to missing or incomplete information. Poorly mapped data can severely impact functionality of the platform, delaying user adoption and system efficiency.
One of the first jobs to be completed is to ensure all data is correctly mapped to the relevant Salesforce fields by extracting your data into a structured SQL database. This method allows for precise mapping and configuration to align your data with
Salesforce requirements.
Once the data has been mapped, it’s advisable to conduct a detailed line-by-line analysis of the data mapping to detect any gaps and misalignments. This proactive approach will allow you to discover any issues with your data set before it has the chance to impact your Salesforce data or performance, allowing you a seamless transition to the new system.
3. Inconsistent data formats and structures
Legacy systems will often store data in formats or structures which are not compatible with Salesforce. This can create obstacles during the migration and lead to issues with data accuracy and compatibility.
You should ensure that you have standardized your data formats and structures, and retrospectively format your legacy data to align with Salesforce’s requirements. It is important that manual validation is used to verify the accuracy of the data. In some cases where data formats are exceptionally complex, customized validation workflows and transformation processes may be required. This would allow the most intricate datasets to be smoothly migrated into Salesforce without sacrificing data quality
or functionality.
4. Complex data models
Salesforce implementations frequently involve data models with complex relationships, including objects tied together through lookups and junction objects. Migrating these intricate models can be challenging without disrupting the data’s integrity.
The first step would be to detail the relationships you currently have in place through mapping, by understanding the complexity of their relationships. The necessary steps can then be taken to maintain the integrity of these connections during the
migration process.
In more advanced scenarios, you may need to simplify complex data models, removing any unnecessary object dependencies or convoluted relationships. This will improve your system performance whilst also ensuring data integrity, which will reduce your future maintenance needs and enhance scalability.
5. Automated data validation
One of the most time-consuming aspects of a Salesforce migration is validating that the data migrated aligns with the agreed-upon migration rules. This manual validation process can stretch over months, delaying the go-live date and increasing project costs.
However, automated data validation can significantly streamline this process by automatically comparing the migrated data against predefined rules and criteria.
