Data Migration Framework

Poorly planned or executed data transfer is a major pitfall of many IT projects. Yet it can be done quickly, without loss, and at a third less cost.

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Adastra Data Migration Framework

Adastra Data Migration Framework projects are a proven set of methodologies, processes and technological solutions that ensure efficient and reliable transformation, data transfer which ensure the complete verification of its accuracy and goals.

This process involves the following five steps:

1. Analysis of the data structures

The fundamental starting point for any successful migration is a detailed analysis of the source structures in source and target systems to understand and identify differences between these structures and their interaction mapping.

2. Analysis of the data lifecycle

Data in the source and target systems may differ not only in structure, but also in how to work with the data, their life cycle and related processes. Therefore, it is essential to do two-way mapping of the condition of the data and to ensure the consistency and the quality of the new data.

There may be times during a migration when a new data system declines as it does not meet defined business rules.

3. Removal of poor quality data

The goal of data migration is not to clean data as effectively as possible, but to transfer the data, including errors, as faithfully as possible. As the data needs to comply with the requirements of the new system, it must be determined which data is to be used for proper systems operations.

These controls must be automated and guaranteed in migration tools. Data cleaning is done either automatically as part of the migration tool, or, errors can be identified, categorized, and chosen for manual cleaning. What must be prevented is the situation when new data cannot be loaded because of errors.

4. Migration Process

The migration tool determines how strictly the migration is run, how often tests will be repeated and how the whole process is conducted and fine-tuned.

Individual runs record all errors that arise and the weaknesses in internal control reports in addition to identifying data that must adapt to business rules or which do not meet the quality requirements. This rigorous process ensures all problems are identified and resolved.

5. Testing and reconciliation of data

An essential component of Adastra Data Migration Framework is a detailed reconciliation check of the data accuracy where the compliance of data between input and output, and the migration between phases, is checked.

The tool enables the reconciliation of data by defining the complex rules involved in the input systems where data usually have a different structure than in the target system. Comparing and checking the data at this point is far from an easy task.

Case studies

Equa Bank clients were fully migrated to Raiffeisenbank in 12 hours

When Equa Bank was being mergedintoRaiffeisenbank in November 2022, we handled the migration of Equa Bank’s client data into Raiffeisenbank’s CRM system. We also ensured the client master data was propagated to the bank’s core systems.

hours instead of 3 weeks – shorter live migration thanks to 10 months of testing and agile development

700,000

subjects to migrate

450,000

people - each with 200 attributes, added to Raiffeisenbank’s client base after the acquisition of Equa Bank

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An increase in impressions among the target group: a 10x bigger target group

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