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
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                          Data Quality

                          Data Standardization, Cleansing, De-dupe and golden record creation wired to an interactive dashboard with configurable data quality metrics
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                          Data Validation

                          Global address validation & correction using postal directories and 3rd party APIs. Contact/lead email and phone number verification
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                          Data Enrichment

                          Customer/contact enrichment through 3rd party partnerships. Product/material enrichment through web scraping, image processing, unstructured data analysis
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                          Hierarchy Management

                          Customer/vendor hierarchy validation, creation and management through 3rd party partnerships. ML algorithms for product/material hierarchy assignment at scale (including GPC/GS1 migration)
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                          Feedback Loop

                          Active Learning based feedback module allows business users to pass feedback and augment the algorithm’s results if required
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                          Data Governance

                          Ensure on-going data is kept clean by managing Stewardship, policies etc. Individual modules for metadata management, data quality dashboards/metrics and more
                          IMPLEMENTATION
                          Sancus 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
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