Transforming Data Management in the Financial and Insurance Sector Through Enterprise MDM and Big Data Technologies
The client is a prominent Financial and Insurance company based in the USA, renowned for its diverse portfolio of services.
About the Client
The client is a prominent Financial and Insurance company based in the USA, renowned for its diverse portfolio of services. Faced with the challenge of efficiently managing data across various businesses, the client sought to build a robust Enterprise Data Management (EDM) platform that could serve as a central repository for data, supporting business analytics requirements while incorporating Master Data Management (MDM) capabilities.
Services
Artha Value Add
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Reduced Downtime
20% reduction in system downtime during data source modifications.
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Efficiency Improvement
30% improvement in data processing efficiency.
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Data Quality Enhancement
Achieved a 25% reduction in data errors and redundancies.
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Cost Savings
Realized a 15% cost reduction using scalable and cost-effective technologies.
Challenges
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Establishing Diverse EDM Platform: Addressing the need for an Enterprise Data Management (EDM) platform across diverse business lines. -
Constructing Robust MDM System: Building a Master Data Management (MDM) system to ensure comprehensive control over data quality and consistency.
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Integrating Big Data Technologies: Seamlessly incorporating Big Data technologies to enhance and streamline business operations.
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Ensuring Minimal System Disruption: Minimizing disruptions during the addition or removal of data sources for a smooth operational transition.
Results
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Cloud Solution Deployment: Successful deployment of the comprehensive solution on the cloud infrastructure.
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Synchronized Data Flow Integration: Integration of systems with synchronized data flow, facilitating collaboration between producers and members.
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Efficient Data Processing: Achievement of efficient and accurate data processing through the implementation of the latest and economical technologies.
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Data Subscription and Consumption: Enablement of data subscription to other departments and seamless consumption by operational data stores.
Solution
Introduction of Amazon Cloud and Talend
Leveraging Amazon cloud services and Talend Big Data platform to establish a solid foundation.
EDM Platform Design and Construction
Designing, constructing, and deploying an EDM platform with a plug-in architecture for flexible data source management.
Utilization of Big Data Pig Infrastructure
Employing Big Data Pig infrastructure for efficient transformation of data into a canonical format.
Application of Data Standardization Rules
Applying data standardization and transformation rules to ensure consistency in the canonical format.
Sophisticated Matching Algorithm
Implementing a complex matching algorithm to identify duplicates across all data sources.
Conflict Resolution Processes
Executing conflict resolution processes to identify data collisions and proactively generate notifications.
Survivorship Rules Implementation
Applying survivorship rules to extract attributes and create a unified master record from grouped data.
AWS Data Pipeline Orchestration
Utilizing AWS data pipeline for orchestrating the entire data processing workflow.
Utilization of Diverse Components
Incorporating various components such as AWS (EC2, S3, RDS, MySQL, EMR), Scoop, Pig, Data Pipeline, Talend MDM, and Talend Big Data components.
Introduction of Amazon Cloud and Talend
Leveraging Amazon cloud services and Talend Big Data platform to establish a solid foundation.
EDM Platform Design and Construction
Designing, constructing, and deploying an EDM platform with a plug-in architecture for flexible data source management.
Utilization of Big Data Pig Infrastructure
Employing Big Data Pig infrastructure for efficient transformation of data into a canonical format.
Application of Data Standardization Rules
Applying data standardization and transformation rules to ensure consistency in the canonical format.
Sophisticated Matching Algorithm
Implementing a complex matching algorithm to identify duplicates across all data sources.
Conflict Resolution Processes
Executing conflict resolution processes to identify data collisions and proactively generate notifications.
Survivorship Rules Implementation
Applying survivorship rules to extract attributes and create a unified master record from grouped data.
AWS Data Pipeline Orchestration
Utilizing AWS data pipeline for orchestrating the entire data processing workflow.
Utilization of Diverse Components
Incorporating various components such as AWS (EC2, S3, RDS, MySQL, EMR), Scoop, Pig, Data Pipeline, Talend MDM, and Talend Big Data components.
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