Data Cleansing & Normalization



What we follow

We have a highly skilled project team who process data cleansing in well-organized workflow systems. Along with the automated processes, manual data entry effort is done. Our experts rewrite the product data wherever required to increase the data efficiency.

The Data Cleansing & Normalization process includes

  • Data Analysis – Identify critical product data for cleansing. Analyze the product data for missing information, duplication and gap analysis.

  • Data De-duplication – Set validation rules to find the duplicates. Automated workflow systems use those validation rules to remove the duplicates.

  • Standardize Data – To maintain data consistency, specified rules and parameters are set for the various components in a product data like the SKU number, price, Meta tags, product URLs etc.

  • Normalize Data – Redundant data is removed and checked for inconsistencies.

  • Quality Check – Check product data again for quality and repeat the process till will we arrive at 100% quality.


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