Data migration services

Empaxis investment firm clients

Unlock seamless data migration for your investment firm

Moving data from one platform to another is no simple task. Data migration is a painstaking process, and if you do it wrong, your firm will be severely impacted.

And the reality is most firms are not experts in migrating data, so the chance of risk is very high. Your data is too valuable to risk leaving migration up to your team and hope they figure it out.

Empaxis India office - investment operations outsourcing

Empaxis makes migration easy

We believe that data is the lifeblood of your investment firm, and the best solution is to partner with a team of experienced data migration experts who have the technology and processes in place to ensure a successful outcome.

Here at Empaxis, we’ve successfully completed hundreds of data migration projects for investment firms, hedge funds, family offices, banks, and institutions worldwide, ensuring a smooth transition without disrupting their operations.

Our approach

Our data migration process is designed to minimize downtime and ensure that your data remains secure throughout the transition. We work closely with your team to develop a customized migration plan that fits your specific needs and timelines.

Step 1: Gather requirements
  • Meet with your team.
  • See all systems currently work on, the platform(s) you want to migrate to, the data integrations needed, and the data views you want.
Step 2: Create a plan
  • Formulate a data migration strategy.
  • Determine workflows.
  • Establish KPIs.
  • Set up regular check-ins and progress reports.
Step 3: Assess the data
  • Analyze the source data to assess its quality, structure, and complexity.
  • Identify any data dependencies or relationships.
  • Determine data ownership and access requirements.
Step 4: Map the data
  • Create a data mapping document that specifies how data from the source will be mapped to the destination format.
  • Define data transformation rules to ensure compatibility between source and target systems.
  • Address issues like data cleansing and de-duplication if necessary.
Step 5: Test
  • Develop a testing plan to include unit testing, integration testing, and user acceptance testing.
  • Test the migration process with a subset of data to identify and resolve issues.
  • Validate the accuracy and completeness of the migrated data.
Step 6: Extract data
  • Extract data from the source system(s) using the defined mapping and transformation rules.
  • Ensure data integrity during extraction by using checksums or hashin
Step 7: Load data
  • Load the extracted data into the target system(s) while adhering to the predefined mapping and transformation rules.
  • Monitor the process for errors or inconsistencies.
Step 8: Validate and verify
  • Validate the data in the target system(s) against the original source data to ensure accuracy.
  • Verify that data relationships and dependencies are maintained.
Step 9: Test and validation
  • Perform extensive testing on the target system(s) to confirm that the data is functioning as expected.
  • Conduct user acceptance testing to involve end-users and validate that the data serves their needs.
Step 10: Deploy
  • Plan the migration cutover carefully to minimize downtime and disruptions.
  • Execute the migration during a scheduled maintenance window.
  • Monitor the migration process in real-time and be prepared to address any issues that arise.
Step 11: Post-migration validation
  • After the migration is complete, conduct post-migration validation to ensure all data is successfully transferred and that the new system is operational.
  • Address any outstanding issues or discrepancies.
Step 12: Prepare documentation and knowledge transfer
  • Document the entire migration process, including data mapping, transformation rules, and any issues encountered.
  • Provide training and knowledge transfer to relevant personnel for ongoing data management.
Step 13: Perform monitoring and maintenance
  • Continuously monitor the target system(s) to ensure data quality and performance.
  • Establish data governance practices to maintain data integrity over time.
Step 14: Maintain regular communication
  • Keep stakeholders informed throughout the migration process, providing regular updates on progress and any unexpected challenges.
Step 15: Feedback and improvement
  • Gather feedback from users and the project team to identify areas for improvement in future data migrations

Let’s have a conversation

Want to learn more? Curious to find a better way to handle your procedures and cut your costs? Whether you’re ready to get started or simply exploring options, let’s chat. There’s no charge to you.

Meet with Empaxis

Get the latest in financial technology support, AI and digital transformation and investment operations outsourcing

Our monthly newsletter features helpful resources, articles, and best practices to implement within technology providers and investment firms