What is a Data Migration?

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A Data Migration is the process of transferring data between computer storage systems or file formats. They greatly range in scale and can often be significant projects including numerous preparation and reconciliation activities. For this reason, a Data Migration Platform is often used to automate a lot of the repetitive tasks. Examples of a Data Migration project include:

  • Switching Customer Relationship Management (CRM) systems.
  • The merging or acquisition between two companies leading to a need for one database.
  • If the decision is made to outsource a certain area of the business that requires data.

What do you need to consider during a Data Migration project?

A Data Migration can often be a large task with plenty of potential risks and is therefore not something to be done without extensive planning beforehand. 7 things you should consider before starting any Data Migration project are:

  1. Pre-Migration Planning – Assess the required timescales, resources, plans, targets for the project ahead.
  2. Project Initiation – Creating a stakeholder communication plan, preparing for later stages of the project, resolving any risks highlighted in the Pre-Migration Planning.
  3. Landscape Analysis – Creating a Data Dictionary, impact report and project estimates.
  4. Solution Design – Agreeing on service level agreements, identifying all software and hardware specs and requirements.
  5. Build & Test – Testing the migration away from the live environment, deciding fall back policies and creating a gap analysis.
  6. Execute & Validate – Keeping a log of SLA progress and independently validating the data migration.
  7. Decommission & Monitor – Validating the system retirement and handing over ownership of the environment.

Explore our Data Migration Project Checklist to read the full detail of each stage of the Data Migration.

What are the drivers of a successful Data Migration?

Data Migration Pro Research Study

Explore our Data Migration research that looks at the factors that determine data migration success or failure and how to tackle them.