Veracell developed a solution to address challenges with duplicate product entries within a Electro Center's product catalog. Multiple product codes, often created for specific customers, referred to the same underlying item, impacting data quality and requiring significant manual effort for harmonization.
A Python algorithm using fuzzy matching and clustering identifies duplicate product entries.
A simple UI enables easy analysis execution and access to processing logs.
The solution significantly reduces manual effort and supports reliable data cleansing and migration.
A reusable Python-based algorithm was developed using cross-column data aggregation, fuzzy string matching and hierarchical clustering to identify both potential and confirmed duplicates. A simple user interface was also developed to allow easy execution of the analysis and viewing of processing logs.
This solution provides Electro Center with a more efficient workflow for product data management. The tool systematically identifies and groups duplicate products, saves significant time previously spent on manual searching, and provides a reliable foundation for data cleansing and migration.
These glimpses are just the tip of the iceberg. Together, let's turn your "what-ifs" into "how-tos," shaping a future we dare to dream.
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