Best Practices for Preparing for an Efficient Data Migration

Jan 26
17:39

2021

Cloudywave

Cloudywave

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Effective migration has always been troubling and challenging work for any Salesforce professional. However, if you have a good understanding of what data migration is along with some of the variables that everyone is supposed to hold in mind for Data Migration Strategies, the process becomes very straightforward...

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Effective migration has always been troubling and challenging work for any Salesforce professional. However,Best Practices for Preparing for an Efficient Data Migration Articles if you have a good understanding of what data migration is along with some of the variables that everyone is supposed to hold in mind for Data Migration Strategies, the process becomes very straightforward.

 

Identify the required fields:

 

The first step is to list the fields involved in the migration process:
  • Required fields
  • Optional fields
  • System Generated fields
Then identify any additional fields that might be required, like:
  • Legacy IDs
  • Business rules
Determine the order of migration

In Salesforce, relationships that exist between objects and dependencies dictate the order of migration. For example, all accounts have owners, and opportunities are associated with an account. In this case, the order would be to

  • Load users

  • Load accounts

  • Load opportunities

Relationships are expressed through related lists and lookups in a Salesforce application while IDs(foreign key) create relationships in a database.

Data Migration Workbook

Create and follow a data migration workbook throughout the scope of migration. This is a consolidated workbook that holds the data mapping for each object involved in the process. A single template with multiple tabs (one each for each mapping object) including a DM checklist and storage requirements. The workbook can be personalized based on your own business requirements.

Pre-data migration considerations:
  • Create and set up a user with a system administrator profile for data migration.
  • Complete system configuration.
  • Set up roles/profiles.
  • Be sure to store all possible legacy IDs for a record in Salesforce. (This can help with troubleshooting later on.)
  • Confirm that record types and picklist values are defined.
  • Set up every single product/currency combination in the pricebooks if it will be used in Salesforce. (This will need to be loaded into the standard pricebook first.)
  • Proper mapping needs to be defined.
Data load considerations:
  • Clean and optimize your data before loading. It’s always good practice to standardize, clean, de-dupe and validate source data prior to migration.
  • Use Bulk API for better throughput, especially when working with large data volumes to increase load speed.
  • Disable and defer what you can. When you know your data is clean, you can safely disable the processes that you would normally have in place to protect against data entry errors in batch loads, or made by users during daily operations. All of these operations can add substantial time to inserts — complex triggers in particular. These are the first things you should investigate when you debug a slow load.
  • While loading large data volumes, the calculations can take a considerable amount of time. We can probably increase load performance by deferring the sharing calculations until after the load is complete.
Some additional rules for migration:
  • Clearly define the scope of the project.
  • The process builder must be aware of source format and target (Salesforce) required data format.
  • Your migration process must have the ability to identify failed and successful records. The common approach is to have an extra column in a source table that stores the target table’s unique ID. That way, if there are fewer failure records after the first iteration, you can re-execute the process, which will only pick failed records that are not yet migrated.
  • Actively refine the scope of the project through targeted profiling and auditing.
  • Minimize the amount of data to be migrated.
  • Profile and audit all source data in the scope before writing mapping specifications.
  • Define a realistic project budget and timeline based on knowledge of data issues.
  • Aim to volume-test all data in the scope as early as possible at the unit level.

These best practices can help you prepare for and execute a successful large-volume Salesforce data migration.

 

Things To Consider Before You Move Data with Salesforce Migration:
  • 1-User mapping is important before you start. You should clearly understand how the user IDs of the existing system match those of the new system. It is critical to make sure that the record ownership is set up correctly in the new system.

  • 2-Revisit the organization-wide defaults and existing profiles. These are foundations of security and safe Salesforce migration.

  • 3-Make sure that you have a couple of licenses available for the old instance for a few months after the cut over date. If after migration you face any issues, you can go to the old instance and investigate the issues.

  • 4-Keep watch on the space you are consuming. When you move additional data to a system it is important to consider space. Ask your Salesforce representative to buy extra space in the new system.

  • 5-It is important to consider the order of insertion when you insert records in a new system. For example, you insert accounts first and then all the contacts so that the relationships between these two objects are set properly.

  • 6-It is very important to plan out the Salesforce migration first so that the users are well informed about the cut-off date and possible issues which may occur. It is a good idea to have pilot users test the migration for some period of time.

  • 7-Before you roll out the instance to others, be prepared to perform testing as a developer and perform sanity testing directly with Salesforce.

  • Salesforce data migration is an important task required for providing effective data solutions to an organization. It must be performed carefully without affecting the quality of data in the system.