The migration of legacy product data into new or existing PIMs
Data Migration can be a complex process. Start with Data has a proven method for product data migration with a blueprint approach to migrating legacy product data into new or existing PIMs.
What is data migration?
Data migration is the process of transferring data from one digital storage system to another, which involves defining the scope, profiling, selecting, preparing, extracting, transforming and loading data.
It is important to highlight the differences between data migration, data integration and data conversion. At the start of the data migration project, data may need to be modified or transformed, which is known as data conversion. The process of combining data from different sources into a single, unified view refers to data integration. As such, conversion and integration form only a sub-category of tasks within a data migration project.
What is a Data Migration Strategy?
Data migration strategy defines the approach for migrating the data managed in the existing solution to the new one. A data migration strategy prevents a substandard migration project from causing more problems than it solves (such as missing deadlines or going over budget).
The Data Migration Process
The broad industry consensus identifies three phases of activities in the data migration process, we extend that to a fourth phase, given the importance of getting the preparation and planning right before embarking on the activity itself. At the bottom of this page, you will find a breakdown of our stages.
2. Planning and Designing
In the initiation phase, we document the strategy, scope and governance of the data migration.
- Requirements – Current System inventory & Migration Scope
- Design – Analysis of Source & Target Data Model, Data Mapping & Data Templates, Planning for Execution Steps, Tool Selection
- Product data governance maturity assessment: benchmarking across access, ownership, quality
The build phase comprises the activities required to transfer the source data from existing systems to new systems
- Profiling, Validation & Cleansing – required to gather the knowledge of the data in question; source data must be audited to avoid problems at a later stage.
- Cleansing – All issues identified need to be resolved and must be included in the error report. All data quality deviations described in the report must be addressed by fixing the data in the source system or by the automated rules defined by the Data Owner. Depending on the scale and extent of the issues, this may require further tools and specialist resources.
- Data Extraction – Extract required data from source system.
- Data Transformation – This stage involves data loading, source data validation, data conversion and converted data validation
- Data Loading – to target model
- Verification – Data verification, sign off from business stakeholders
Activities required to close off the data migration projects – the final load and validation. The final iteration
- Data Archival
- Data Cleanup in the old system
Bear in mind how much budget you can allocate to the migration process. Using the services of a data migration consultancy is key, as strategy-planning with them sets you up for a successful and problem-free migration. Additionally, ensure you consult closely with those who rely on the data – the end users. Successful data migration will increase user adoption of the new PIM solution.
Best Practices for Data Migration
Data migration tools
As with any good product, you need a tool with features fit for purpose; flexibility, scalability, ease of use for non-experts (with minimal technical expertise) and intuition in its interface and suite of functionalities. There’s no one tool that fits all for migration projects. Depending on the client’s application landscape, IRM recommendations, source and target capabilities, data quality scope – the right choice should be made.
Start with Data’s partner in data tools is Conemis, a provider whose innovative approach, leveraging the latest developments in AI, has proved to be highly fit for purpose in the migration projects we have managed. To give you more context, let’s look at the types of attributes you should be looking for in a high-quality data migration tool
What to look for in the right tool
Straightforward Data Mapping tools like a code-free, drag-and-drop, graphics-oriented user interface.
Data Integration and Transformation Capabilities which can restructure data for targeted delivery.
Enhanced Connectivity enabling seamless connection with various source and destination structures.
Automated workflow orchestration and job scheduling to streamline data processing.
Data analysis, cleansing and deduplication capabilities to verify and improve data quality prior loading data to the target system.
Data enrichment to support additional, clean content for the initial data migration, for example address data enrichment, validation or enrichment of the company information with D&B.
Recommended tools based on the source or target systems to benefit from predefined workflows, connectors, mappings.
This is not to omit hosting, user limitations, range of functionalities, automated processes, scalability and customer support services.
Data migration challenges
A poorly executed data migration process leaves your organisation unresponsive to a rapidly evolving business ecosystem, with a fragmented and inconsistent set of tools.
Data Migration Consultancy
Start with Data has a proven method for product data migration with a blueprint approach to migrating legacy product data into new or existing PIMs.
Our proven method for product data migration
Our 4 Phase Data Migration Approach
Find out more
If you would like to find out more about how product data management, PIM and MDM can create value for your business, we’d love to hear from you – Ben Adams, CEO Start with Data