Our Client:

Our customer is a leading insurance company and platform P&C insurers trust to engage, innovate, and grow efficiently. It combines digital, core, analytics, and AI to deliver our platform as a cloud service. More than 450 insurers, from new ventures to the largest and most complex in the world, depend on them.

Objective:

It was a venture to modernize the Enterprise Data Warehouse by consolidating on-prem data marts and data warehouses and designing a central Snowflake Cloud Data Warehouse (EDW) for analytics use-cases and an Integration Data Hub (IDH) for real-time application integration. This will help our customer to process the data at scale, provide real-time data access to the data team, reduce operational costs and offera self-service Tableau cloud-based analytics platform to derive data-driven business insights.

Challenges:

Our customer’s mandate was to implement Snowflake Enterprise Data Warehouse (EDW) and Integration Data Hub (IDH) and go live within six months. The goal was to decommission the on-prem servers and processes and consolidate the data integration and analytics tools platform to simplify the architecture. The existing systems had Complex Architecture, Redundant Data Silos, limited compute resources, performance issues impacting SLAs, and a large number of legacy, complex stored procedures which were not documented.

Complex Architecture, Legacy integration with undocumented complex stored procedures
Multiple copies of the data are extracted from different tools and processes
Infometry needs to Consolidate, Centralize, Merge and Migrate various SQL Server databases to Snowflake.
Retire existing systems within six months
Large number of applications to be integrated
1200+ Database objects to be migrated
Migrate 200+ dashboards from Qlik to Tableau Online
Real-time application integration to be implemented using Mule 4 Micro Services based design
Change Management: It was had to educate/convince Qlik users to adopt new Tableau-based visualization Complex Architecture, Legacy integration with undocumented complex stored procedures

"We are impressed by infometry's s matured approach and immense knowledge in designing complex cloud data warehouses, etl/elt, esb, data quality, and analytics: we appreciate infometry for delivering the customer data warehouse modernization project of this magnitude and complexity as a turn-key project with aggressive timelines with the highest quality." — senior it leadership"

Solutions:

The customer hired Infometry to deliver the entire Data Warehouse modernization project as a turn-key solution within six months. Infometry team implemented highly scalable, highly available Snowflake Data Warehouse, Information Hub and integration across multiple Cloud and On-prem applications in near-time leveraging best practices, using Infometry’s pre-built data models, integration templates and automation. As part of the Data Warehouse modernization project,

With Data Hub strategy eliminated redundancy in data collection and streamlined data flow with proper data governance and parallelism
With Optimum data model and aggregation layer, reduced complex data transformation logic and reduced dependencies on complex stored procedures
With templatized mapping framework, simplified the ETL/ELT and Micro Services-based ESB interfaces
Leveraged S3 bucket to optimize data loads
Effectively handled Change Management for Qlik to Tableau conversion
1300+ Database Objects from SQL Server were migrated
1200+ Qlik Dashboards Migrated
1200 Informatica Cloud Mappings
300+ MuleSoft Interfaces

"The productivity gains have been huge, and it's creating a tremendous advantage for the company." — Head of Business Intelligence and Data Transformation Leader

Results:

By engaging with Infometry, the customer could build an Enterprise Data Warehouse and Analytics solution to automate data collection and processing and build operational and executive dashboards leveraging historical and real-time data.

Technologies Used:

Snowflake, MuleSoft ESB, Informatica, Tableau, Qlik