DATA QUALITY IMPROVED BY 65% THROUGH AUTOMATION OF DATA INGESTING AND PROCESSING

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CLIENT

An American insurance provider was looking to enable identification of new products based on data insights. The client was facing below mentioned challenges -

Low trust in available data
Siloed data spread across the business landscape, making consolidation difficult
No 360-degree view of key data types
Difficulties in identifying and remediating data issues due to large volumes
Lack of common data co-relationship across the enterprise
Delayed business decision-making due to various data-related problems

SOLUTION

Through Mphasis’ NEXT digital transformation, we helped the client in -

Building a cognitive data hub to ingest data from multiple internal and external sources using Mphasis' Cognitive Data Framework
Automating data processes across the data hub by leveraging automated pipeline
Enabling automated AI-based data quality management
Improving trust in data through AI-based data cataloging, data lineage and metadata management
Enabling high speed analytics to ingest and generate valuable insights

BENEFITS

65% improved data quality through automated data ingesting and processing

20% increased operational efficiencies through reduction of manual efforts and use of AI-enabled data quality and data lineage management

15% improved reporting accuracy and faster insights through AI-based data analytics.

4.5% increased sales revenue resulting from identification of product offerings for upsell/cross-sell opportunities

Enhanced user experience