Data migration often involves long-term, costly and high-risk projects. Most of all it commonly requires a lot of complex customer-specific scripts. As a result, project teams frequently take only the extraction, data manipulation (transformation) and loading into consideration. Improving and cleansing data is often neglected or not taken seriously enough, leading to non-standardised data and preventing similar records from being merged.
Any migration process starts with knowledge-based interpretation. High precision matching and intelligent enrichment will cleanse and improve the data. Subsequently the data are merged based on specific business rules. Human Inference DataHub is an out-of-the-box solution, that combines these steps, to deliver quality data to the target system(s).