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  • FEATURES
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    Data Cleansing

    Data standardisation & AI/ML led data cleansing
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    Data
    Enrichment

    Enrichment from unstructured data sources, proprietary and 3rd party sources
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    Hierarchy
    Management

    Automated hierarchy mapping & ML based master data categorization at scale
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    Data
    Quality

    ML based automated anomaly detection for hierarchies, categorical and numeric data types
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    Data
    Oversight

    ML based ongoing data management to ensure continuous data quality management
    IMPLEMENTATION
    AI Data Cleanser has been implemented for various master data types enabling transformation across the business value chain
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    Customer MDM with Cognitive RPA

    Enabling a unified and cleansed customer master across the enterprise by integrating multiple CRM systems
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    Product Hierarchy Management at Scale

    Enabling development of product master data by standardizing taxonomy and cleansing data from different suppliers/retailers
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    Contact MDM with External Data

    Enabling better marketing effectiveness through cleansing and 3rd party data enrichment of contact data systems
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    Product Attribute Enrichment with Computer Vision

    ML tools & algorithms to extract attributes from images of multiple formats and enrich existing product attribute master data
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    Vendor Data Quality Management

    Enabling unification of vendor database through cleansing, hierarchy & data quality management
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    Material Master Data Management

    Enabling unification of material level master data through cleansing, hierarchy & data quality management
    DEMO VIDEO

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