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