Modernizing the Data Warehouse ecosystem - SAS Migration to Azure
CASESTUDY
AI, ML, Virtual Assistants and Automation Deliver Operational Excellence and 99% SLA much to the customer’s delight
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CLOUD
Co-Engineering World’s First Human Data Sciences Clouds with AMAZE for Data & AI
Our Customer
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AT A GLANCE
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A leading life and non-life insurance company headquartered in the EU with 6.6+ Bn revenue and 4,400+ employees worldwide.
Business Challenges
The global insurance firm was looking to accelerate its digital transformation journey by integrating its data landscape with the Azure Data Factory (ADF).
Business CHallenges
Deliver self-service for 70% of the service requests and reduce dependency on the customer service center
Paperless delivery to reduce annual mailing volume by 50,000 – 70,000 pieces
Deliver digital experience for a positive impact on the policyholder’s satisfaction
Setting up accurate tooling for all aspects of testing to market
Reduce time/effort spent on new feature development
The business challenges were many.
The existing SAS data warehouse was not scalable for the future requirement of the business.
Multiple processes on disparate systems (SAS DI and SQL Server Integration Service) lacked synergy
The usage peaked at closing times, and there was a lack of access to data by business
The key was to minimize downtime for the migration of SAS DI to Synapse. They wanted to ensure no disruption to the business.
Our Solutions
We leveraged our proprietary cloud modernization platform, Amaze® for Data & AI, for fast-tracking the modernization of the data warehouse and analytics ecosystem.
OUR SOLUTIONS
• Carried out the automated discovery of the environment • Revalidated baselines • Evaluated dependencies & integrations with apps • Leveraged tools Movere and TSO for cloud migration discovery • Recommended Treatment (Rehost V/s Replatform)
Our SOlution
Post completion of the data ingestion, the team built a data glossary.
Discovery
Data Glossary
Data Security
The team setup data security based on roles and profiles.
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®
Amaze® for Data & AI provided the following levers in the migration journey.
The implementation methodology involved An automated assessment and migration of existing 2200+ SAS DI & SQL Server Integration Service to (Extract, Transform, and Load) ETL jobs to ADF & Ingestion of data by ADF into the Azure Synapse DW for reporting and analysis
• An Azure native approach to the architecture • Automation-led migration and validation • Pilot-based execution
Business Benefits
HIGHLIGHTS
Modernizing the data warehouse ecosystem by migrating from SAS DI to ADF/Synapse offered the following business benefits.
50% Faster
3X Better
40%-50% Cost-Effective
Minimal impact and almost nil disruptions during the pandemic as virtual agents took over the load of actual agents
API enabled platform for quick and easy plug in to capabilities ranging from content, concierge requests, user preferences, chat and self-service lifestyle functions
Reduction in number of licenses
Increase in customer satisfaction through focussed data to insights
30% faster onboarding with automation and other enhancements like quick routing
85% of interactions previously through calls are now routed through chat
Hexaware ensured the following benefits:
The Factory model for SAS DI migration to ADF ensured consistency and reduced risk
A reduced timeline in assessment and SAS DI migration through automation
Reduced Total Cost of Ownership (TCO)
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