Automated Schema Matching and Data Projection to Enhance Master Data Management Data Quality
Keywords:
Automated Data Mapping, Schema Matching, Data Quality, Machine LearningAbstract
Especially in master data management (MDM), the quality of data is very crucial for preserving the correctness, consistency & the dependability of the information of an organization. The main challenges of companies have is combining data from many sources—each with a different structure & the format—which causes discrepancies & difficulties creating a coherent data view. Novel solutions that help to align the consistency of data structures across many systems include automated data mapping and schema matching. By automating the detection of linkages between data fields using smart algorithms and machine learning models, these techniques significantly lower human effort and errors usually related with the process. Furthermore, automatic data mapping and schema matching assure consistent data structure across systems, thereby improving data quality and therefore operational efficiency and better decision-making. These techniques also help to eliminate duplicates and discrepancies in data, therefore enabling the preservation of a single, consistent source of truth for vital organizational information.
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