Skip to main content
Home » Salesforce Data Migration Services Blueprint for Success » Mastering Salesforce Data Migration in 2024: Tips and Tools for a Successful Launch

Mastering Salesforce Data Migration in 2024: Tips and Tools for a Successful Launch

Salesforce Data Migration is a process for migrating data from an existing application or database into A successful data migration into requires a well designed plan. Data Tools Pro has prepared a detailed plan to plot you on the right course.

Table of Contents

Additional Reading

Avoid common migration pitfalls.


In this article, we will highlight the core recommendations for a successful data migration. From inventorying your data to testing your data movement process, these steps will ensure a smooth and successful transition to Salesforce.

Our Migration Blueprint Approach

The over-arching themes and recommendations of this migration guide are intended to be technology agnostic.

We have continuously refined our Data Migration Blueprint which combines process and off the shelf technology tools. Though out this article we highlight those tool. We are constantly evolving, learning, and updating this guide. If you have a better solution or experience to lend, we want to hear about it!

Feel free to contact us to share your experiences and challenges.

Salesforce Data Migration Infographic

Infographic: 10 Point Data Migration Countdown

0. Where to Start?

The first challenge out of the gates that most organizations grapple with is where to start? Salesforce admins, data teams, and business owners are typically brought together to balance 3 important questions:

  1. What data do we need from our existing application for continuity to manage the process?
  2. How do we ensure data from our existing application is available for continuity of information and historical context?
  3. What data requirements exist in the destination Salesforce instance to successfully insert records and move forward?

To achieve a successful data migration, every organization will have varying levels of expertise on hand to address these questions. Because Salesforce is the path forward, typically resources are on hand with in-depth knowledge how the system and process works. We recommend starting with your Salesforce instance and working backwards to your source application. We make that recommendation assuming you are starting the data data migration project at a later point of your initiative and your Salesforce data model is not going to change dramatically.

Notion Migration Checklist

View Checklist on Notion

Salesforce data migration checklist

Roles and Responsibilities

Data migration projects succeed because of the people, expertise, and dedication to success. Sometimes data migration projects require a large cross-functional team. For some organizations it can be accomplish with a 2 person team. We recommend clearly acknowledging who is responsible for the following key areas:

  1. Source system data steward: Someone who understands the data structure and meaning of the data from the source system
  2. Salesforce data steward: Someone who understands the data structure and meaning of data for the destination system. In a perfect world someone understands both ends to help with the mapping.
  3. Business Process Owner: Someone to sign off on mapping of inputs from old system to new Salesforce instance. This is important when making decisions where some data could be discarded or hardcoded where there is not a perfect match.
  4. Data Validation Business Leader: Typically the data team and analysts may not have context and deep understanding to the meaning of data. This is why we recommend identifying metrics where the old application and new Salesforce instance serve as system of record. For example, when we migrate a CRM, I have marketing and sales leaders identify the metrics they track and clarify Salesforce or a data warehouse as the source of truth. These are important points to validate or highlight as functional or impaired aspects of data migration.
  5. Project owner / manager: This person will track and report back progress and raise potential issues blocking requests that could hold up progress?
  6. Data Quality Analyst: This person(s) will analyze and validate the data to ensure there is universal understanding, meet with stakeholders to explain mismatches exist in the data, data quality and completeness issues.
  7. Data Migration Engineer(s): This role is broken into multiple parts.
    • Harmonization and movement of data into Salesforce
    • Transformation and preperation of data from old system to fit new Salesforce instance.
    • Managing and executing the final migration execution plan.

Break Up your Migration into Small Components

The secret to simplifying your data migration project is breaking your end to end process into smaller components. That is why we break our data migrations into a series of checklists, plans, have invested in building specialized tools like Data Tools Pro App.

1. Map and Inventory your Data

Inventory your Destination Salesforce Objects

Build a list of Salesforce objects that you are migrating data into to successfully run your process. For each object, you should flag mandatory fields that your Salesforce admins and business stakeholders need to run and manage the process. When it comes to managing the business, this would be inclusive of tracking and reporting. In a prefect world you have a data dictionary, but that is not always the case so data migration is the opportunity to build this important data asset.

Acquire and Stage your Source Data

Acquiring and staging your source data is one of the first steps in your data migration journey. This process involves gathering all of your data from your current system and preparing it for migration. Your source system could be Salesforce, another CRM, and even a custom built application. Additionally, Salesforce in 2023 has many first party and 3rd party industry modules. Hopefully there is a data dictionary, but at minimum you will need expertise on hand to serve as data steward.

With an understanding of the Salesforce object, at this stage you are shifting your focus to the existing app where you are identifying not only data that needs to be migrated to satisfy your new Salesforce, but potentially historical context. Once you have a complete list of the fields and have started to review what needs to be migrated it’s time to acquire data from your source system.

Acquire and Stage your Source Data

Sensitive PII

As part of the inventory process it is important to highlight sensitive PII in the source system and Salesforce to ensure you are handling this data according to your data governance policy. Classifying this data during data migration is a fairly standard process, and one reason why we typically stage data in a secured system where masking policies can be applied.

Metrics / KPIs

Another import part of the inventory process is insight into what metrics and KPIs are measured and reported from the existing system and how they may have been translated in the new system. Understanding areas where Salesforce will become the system of record and for some organizations the source of truth is very important. Business stakeholders will measure the success of your migration based on key metrics matching rather than record counts. While it may add effort and scope to your migration project, validating key reports between the existing system and Salesforce is a great way to build confidence.

Export Salesforce Documents

Don’t leave your documents behind. If you are migrating between Salesforce instances you may need to extract and migrate documents. The process requires careful planning and specialized tools.

Related Article: Migrate Salesforce Documents and Attachments

Extracting your Data

There are several methods for acquiring your source data, including manual data export, data extraction tools, and APIs. The method you choose will depend on the size of your data. The complexity of your current system, and your overall migration strategy also influences technology choices.

There are hundreds to tools for moving data between systems. Many provide similar functions but could vary in cost as most focus on production data pipelines and ETL. Data migrations are unique because in most cases a data migration is a one time event and in many cases data teams are already backlogged with work to take on a data migration.

Our Data Acquisition Approach

As part of our own Migration Blueprint, we use Azure Data Factory to move data to stage and then to complete the migration into Salesforce. However, for your specific migration process and technology investments you may choose similar alternative tools. We are always testing new providers and partners and will continue to share our experiences.

In our Migration Blueprint, Data factory facilitates movement of data from your source to data staging. The staging of data is a temporary place to house it so it can be prepared for insertion into your instance. We have built standardized templates where data is secured, masked and managed while it is in transit and being staged.

Azure Data Factory Staging for acquiring data
Extract and stage source data

In this data extraction video demo, we extract data from Zoho, import into Zoho and utilize DataTools Pro to set the objects that we are mapping into.

Snowflake data platform for Salesforce Data Migration

Snowflake Data Platform for Secured Staging

As core component in our Migration Blueprint, we selected Snowflake as the preferred data platform to handle staging and transformation. Snowflake can be setup as a service in your AWS, Azure, or Google infrastructure or managed by our team in our Azure hosted Snowflake tenant. Snowflake provides all of the data processing power for small and large scale migrations, while ensuring all of the data remains secured and encrypted at rest. Snowflake Security Compliance.

Mapping Data Relationships to Salesforce

Defining the data relationships and mapping your source data to Salesforce is an important part of a successful migration. This process involves identifying where each piece of data will reside in your instance. The relationships between objects is also very important to understand entity relationships.

To help ensure a successful mapping process, it’s important to follow these best practices:

Collaborate with your business and data teams

Your data and business teams have the expertise to understand the relationships and meaning behind your data. Involving your business subject experts during the mapping process will help reduce re-work in later stages.

Use visual ERDs and dictionaries:

ERDs (Entity Relationship Diagrams) and dictionaries help to define the relationships between your data objects. These visual aids make it easier for both technical and non-technical stakeholders to understand the data relationships and structure.

Salesforce data migration mapping

In this data mapping video demo, we use DataTools Pro to manage field and picklist mapping.

Map Salesforce Fields with Migration Dictionary

With our fee Data Tools app you can specify what fields you will map, and define the source fields, logic and notes. Additional features allow you to export the data or generate database tables.

Create a Project Migration Scorecard to Stay Organized

With our free Data Tools scorecard you can select the salesforce objects for management through the entire data migration process. The result is a scorecard that you can track object by object and drill into field level detail and export the current status to Excel, PDF or copy/paste into an email.

2. Validate and Analyze your Data

Before migrating your data to Salesforce, it’s important to validate that you have complete and correct data. Depending on the complexity of your source system, your data could require lots of data transformations. By validating and transforming your data before migration, you can ensure your data is in a useable format. During this stage, you’ll perform heavy lifting for data transformations, such as joining data, removing duplicates, and surfacing data quality issues from your old system.

Data Quality

During this validation step, you will locate data quality issues in the source system. By clearly communicating and planning data quality issues, you improve your chances for success. Attempting to solve data quality issues during data migration can be a slippery slope . In some cases if the data is poor enough quality your data migration initiative could increase in scope 30-50%. We recommend that data quality issues should be handled only as needed to successfully import data into Salesforce.

Data Validation Checklist

– Key Business Reports from Source System

– All fields that contribute to KPIs and Metrics

– User / Record Ownership

– Fields with Sensitive Personal Information

– Sensitive PII or privileged data that should be masked

In this final stage of data validation and transformation, it’s crucial to involve your business stakeholders and define clear criteria for sign-off.

Working with your business team, you should establish clear validation and sign-off. Your acceptance criteria should align expectations how data captured, mapped, and transformed before you migrate to Salesforce. These criteria include:

  • Reviewing data quality and accuracy
  • Verifying data relationships and mapping
  • Confirming all critical data is accounted for within Salesforce

By having clear validation and sign-off criteria in place, you can have confidence in your data and know that it will support your business needs and drive business value. This will help ensure the success of your migration and lay a solid foundation for your instance.

Data Analysis and Validation with Datameer

Through the creation of our Migration Blueprint we adopted Datameer on top of Snowflake allowing for low / no code data validation, analysis and preparation. One of the key features is an ability to profile, analyze and prepare data in once place. Having a visual tool also allows for inline documentation and collaboration with technology and business stakeholders.

3. Data Preparation for Salesforce

To migrate data into Salesforce you will prepare each field to be compatible with your salesforce instance. Each Salesforce object will need data labeled and formatted properly. There are a number of important considerations when preparing data for importing into including but not limited to:

Column Names

Column names in your source data should match the field names in Salesforce. If your column names contain characters not allowed as Salesforce field names, they will need to be modified. It’s important to establish a naming convention to ensure consistency across your organization.

Lookup relationships to other objects

Lookup relationships allow you to connect one object to another in Salesforce. When importing data into Salesforce, make sure the relationships between objects are properly established. For example, if you have a custom object called “Orders” that should be related to the “Accounts” object, you will need to make sure that the relationships are defined before importing the data into Salesforce.

Null values

Salesforce requires certain fields to have a value. If there is no value available, you should assign a default value to avoid data errors. This is crucial to maintain data integrity and ensure the smooth functioning of Salesforce.

Date / Time UTC Format

Date and time fields in Salesforce must be in Universal Time Coordinated (UTC) format. You should ensure source data is formatted accordingly before attempting to import into Salesforce. If your source data is in a different time zone, you may need to adjust the dates and times to UTC format.

Character limits

Before migrating data to Salesforce, it’s important to check the character limits of each field in the target Salesforce instance. This helps to avoid data truncation and loss of information. The character limits vary depending on the field type and it’s essential to make sure your data fits within these limits.

Data types

Salesforce has specific data types for each field should be mapped in the correct format:

  • Number
  • Date/time,
  • Picklist,
  • Text.

Picklist Mapping

Picklists are a type of field in Salesforce that allow you to select a value from a predefined list. When you import data into Salesforce, you need to make sure that the values in your source data match the values in the Salesforce picklists. If your source data contains values that do not match the Salesforce picklists, you will need to either modify the source data or update the picklists in Salesforce to accommodate the new values.

Numeric values

To ensure accurate reporting and data analysis, numeric values must be in the correct format for Salesforce. For instance, currency fields should have the currency symbol and decimal places in the right format. It’s important to validate this beforehand to prevent data inaccuracies.

Data Encoding:

Data encoding is a process of converting data into a specific format that can be understood by different systems. During the migration process, you should encoded in UTF-8 to avoid data loss or corruption.

4. Migrate Into Salesforce

Once you have prepared data, there are various ways to load it into Salesforce. One popular option is Data Loader, a tool that allows you to insert, update, and delete records in Salesforce using a CSV file. Other traditional Extract, Transform, Load (ETL) tools are available as well as cloud data pipeline services. Implementing the right tools and services for your available skills, allows you to automate the process, saving time and effort, and ensuring data accuracy and consistency.

Azure data factory Salesforce data migration harmization and movement

Harmonized Salesforce Data Loading with Azure Data Factory

Azure Data Factory is a great solution for migrating data into Salesforce because it offers a cloud-based platform for ETL (Extract, Transform, Load) operations.

It enables you to move data from various sources into Salesforce in a scalable, secure, and managed environment. Azure Data Factory provides a number of benefits such as data orchestration, automated data movement, and real-time data integration, making it ideal for large-scale data migrations. Overall, Azure Data Factory makes it easy to migrate data into Salesforce, providing a cost-effective, scalable, and efficient solution for your data migration needs.

5. Refine and Document

Refining and documenting your data migration process from beginning an important step to ensure the success of your migration and to confirm to stakeholders that you were successful. This reduces your risk for error when it comes time to let users loose in your production where they will start modifying and adding new data.

In most if not all cases there could be post migration cleanup work, so having yourself organized will ensure you can rapidly respond to any issues or edge cases that were missed along the way.

Additionally, re-testing your migration many times before the production cutover will give you confidence that your data is accurate and properly formatted.


Data migration is a critical process for organizations looking to switch to Salesforce and requires a high degree of care no matter the size and scale. A successful migration requires careful planning, preparation, and execution. By following the steps outlined in this article, you can increases your chances with success and ensure smooth transfer of your data into Salesforce, while avoiding common mistakes and data quality issues.

If you are interested in embarking on your data migration using the Migration Blueprint recommended tools and want additional assistance you can start with our free Salesforce Migration Assessment.