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Huge inventory of un-managed assets
Timely maintenance of infrastructure and applications
Multiple data sources
Workflow spanning different applications
Applications based on multiple/old technologies
Lack of resources for monitoring and maintenance
Slow processes and bottlenecks in the system
End-to-end engagement model with DataOps principles
Dedicated 24x7 support teams for smooth operations
Modern data warehousing stack with Azure services and Power BI
Specialized data teams for focused tasks
Effective change management process
Proprietary tools for end-to-end data management
Backend system and application migration expertise
Successful on-premises to Azure Databricks data migration
24x7 monitoring, alerts, and performance optimization
Application development and support
Reduced cost spent on infrastructure and resources by 30% by using cloud native architecture.
$1.5 million saved per year from cost and process efficiencies
50% faster reporting with performance-tuning activities
90% reduction in server downtime with efficient data backup and DR
40% improvement in process and workflows
Reduced data silos to minimum
24 X 7 monitoring of application and infrastructure
Automated 30% of workflows
Improved data refresh efficiency by 50%
By implementing CI/CD DevOps process, we were able to deploy more business features in every sprint or monthly two deployment
