Migrate Data to your Salesforce Org like a Pro

Migrate Data to your Salesforce Org like a Pro

data migration

Post 1: Plan for Success

Written by Charu Goyal, Tomasz Czekaj and Daniel Cwikowski from EPAM PolSource

Charu GoyalCharu Goyal
Director, Technical Architect
Tomasz CzekajTomasz Czekaj
Data Migration Specialist
Daniel CwikowskiDaniel Cwikowski
Senior Database Developer

March 12, 2021 | 15 min read

Migrating data into your Salesforce instance is a crucial step in retiring legacy systems, merging legacy Salesforce orgs or systems coming from acquisitions. Unlike system integration, you have only one chance to migrate data and retire your legacy system. So, it’s important to do it right, the first time around.

If not handled properly, data migration can generate sub-optimal results with far-reaching consequences – 

  • Financial implications – Delays in migration mean using the legacy systems longer than planned causing added licensing, maintenance cost. So adhering to the planned timeline is important to stay on budget.
  • Low ROI – Not having accurate or any data available in target Salesforce org causing low usability, adoption rate and hence Return on Investment (ROI).

Also, the complexity may increase significantly when you are dealing with large volumes of data spread across disparate systems, business processes, tables and poor data quality.

We recently helped an enterprise customer migrate millions of records from 4 different legacy systems with 99% accuracy and minimal downtime in their Salesforce environment. The customer, however, had 2 failed attempts doing the same with 2 other SI’s. 

migrate data

So what did Polsource do differently? We helped the customer plan and execute better!

Turns out, comprehensive planning is just as important as flawless execution, especially when it comes to data migration. 

At Polsource, Comprehensive Planning is at the core of every Data Migration.

In the 20+ org merges we performed last year, we placed comprehensive planning at par with flawless execution to achieve near-perfect customer satisfaction scores in all our engagements.

And this blog post aims at educating you on just that – how to plan your Data Migration Project for success?

This blog post is the first of a multi-part series aimed at highlighting data migration strategies, best practices to be followed at various stages and some key gotchas. 

So let’s start with the critical steps that you should include in your data migration journey:

Define your goals, succinctly  

Identify and document the scope, source and target systems, guiding principles, success metrics, rough timeline, roadmap, archival strategy, security & compliance related requirements and risks of the data migration project. Build a data migration team and engage with an experienced SI to help you achieve your data migration goals smoothly.

Take time to understand your data

Data can be nuanced. Data can be highly segmented. Data can be of poor quality. 

So analyze your data for these segmentations, nuances, quality issues and how this would impact your migration logic. For example, duplicates in Accounts and Contacts is a common data quality issue which should ideally be handled before data migration. Partner with your data stewards to navigate through these data intricacies using BI tools. Data Stewards are your go-to data experts who understand, govern and manage your data using sophisticated tools.

Plan for Success 

Rushing through the planning process can easily jeopardize your migration during the execution phase by presenting unforeseen impediments. So carefully and comprehensively plan your data migration project. Organize detailed planning sessions with your data migration team to plan for the following:

1) Finalize Requirements – Document requirements in the form of user stories such that the target persona, desired function and ultimate value to be achieved are captured and shared with all the parties involved. Each data migration user story should cover:

      • Source and Target systems 
      • Source and Target object mapping
      • Criteria for data capture
      • Field mappings and transformations
      • Logic to handle required Salesforce fields, validation rules and required lookup filters
      • Dependencies
      • Ownership

Create a detailed plan that documents the involved tasks, order of execution, target date and time of execution, owners, dependencies, testing handoffs and progress tracking, prior to the final execution.

2) Environment Strategy – Establish the environment in which you will execute the various phases of data migration. If you have large volumes of data to migrate, then a Full Copy sandbox would be the ideal place to execute the first round of migration. Make sure that any new fields to hold the migrated data are created and set up with the right access before the execution phase. Complex transformations and migration logics should be tried and tested in a lower sandbox environment like developer sandbox on small samples of data.

3) Govern automations to be run on migrated data – Engage with your IT team to understand if any automations (like process builders, triggers, workflow rules) would be fired in your target Salesforce org when data is loaded. Having these automations run as the data is loading can trigger email notifications, lengthy data processing jobs, external integrations and can potentially slow down the data load process. 

If your data volumes are large, these automations can also severely impact system performance. To avoid this, consider building exception rules in your metadata to prevent their execution for migrated data. This can be done by using a consistent flag on your migrated data and checking for this flag before letting the metadata execute. Any important data processing should be done as part of the transformation process.

govern automation

4) Choice of Tools – Select the right tool to build the migration scripts that would entail the object and field mapping, transformation, source and target environments. Although Data Loader is capable of handling huge volumes of data, the use of tools like Informatica or Talend can help you automate the data migration in a reliable, repeatable manner. Tools like Salesforce Inspector and Workbench can help you run queries on migrated data for in-depth validation.

5) Testing Strategy – Partner with your data stewards to create a test plan for the data being migrated. Ensure that data volumes, relationships, ownership, visibility, transformations and corner cases are tested on all data with the help of SOQL queries or reports. Consider a Data UAT so that various system users can interact with the migrated data at a more granular level to identify potential issues.

6) Mock Cutover Planning – For complex data migration projects, a mock cutover migration is essential to being successful. Complex projects entail multiple source systems, data with tight dependencies, complex migration logic and/or strict migration schedule with large data volumes. A mock cutover helps your team members rehearse the cutover activities against the timeline with the dependencies and error handling factored in. This ensures that your data migration team works like a well oiled machine during the production go-live.

7) Cutover Planning – Factor in your quarter-end and other crucial business activities together with the estimated timeframe for execution, testing, UAT to create a go-live plan. Socialize this plan with various stakeholders to get their buy-in. Loop-in the various IT teams and stakeholders to understand if the source systems can be frozen prior to go-live such that no delta migrations are needed for truing up the data. Discuss the maintenance window during which the go-live activities would be executed and its potential impact on day-to-day operations.

8) Rollback Strategy – Develop a rollback strategy in case the migrated data does not meet the minimum threshold as defined in your success metrics. Usually, for data migration projects, rollback simply means mass deleting all or some of the migrated data. Bear in mind that while newly inserted data can be easy to delete, rolling back data updates made on existing records would mean referencing the backup data in the target Salesforce system. Hence, it is very important to backup both your source and target data before data migration begins in production. More to follow on archival strategy in a subsequent blog post.

Execute flawlessly

Comprehensive planning with impeccable execution can help you hit a home run. Execution involves migrating data per the timeline into various environments and testing it. Rinse and repeat if errors are found. Experienced data architects and developers should be able to avoid issues related to migrating non-latin script characters, Created Date and Last Modified Date fields, attachments, Chatter feeds, et cetera. For go-live, prepare to decommission your source systems and send out the required communications to your end users about the data that is now available. Time to pop that champagne! 🥂

Let Polsource help you with your Data Migration woes

At PolSource, we don’t just bring technology – we bring ideas, solutions, and support. You get the benefits of global coverage with the agility of a boutique consultancy. The best of both worlds. As one of the fastest growing Salesforce Platinum Partners, we provide you with the innovation, flexibility, speed and accuracy you need to transform your business with Salesforce – all while reducing your company’s risk and cost.

We can provide the thought leadership needed to navigate through discovery, planning, execution and change management – plus we have extensive experience in leading large data migration efforts from systems like Zendesk, Freshdesk, ServiceNow, Salesforce, Zoho. Our trusted advisors can help guide your migration efforts while keeping the approach in line with Salesforce best practices and industry expertise built over the years.

Want to know the best solution to migrate data in your org? Contact us!