Summary
A leading U.S. mortgage company sought to modernize its data management framework to eliminate inefficiencies and improve reporting accuracy. Through a collaborative effort, a new data architecture was implemented, resulting in significant enhancements in data handling and reporting capabilities.
Client Overview
A leading U.S. mortgage company that offers a range of home loan products and engages in acquiring newly originated U.S. residential mortgage loans from small banks and independent originators.
Headquarter
California
Revenue
$490+ Million
Lines of Business
Residential Mortgage Loans
Pressure Points
Sonata implemented a voice and chatbot solution to handle loan application queries efficiently. The process flow is as follows:
Discrete nuclear data warehouses led to data redundancy and inaccurate reporting across teams
Data processing times ranged from 4 to 10 hours
High maintenance costs due to numerous licenses and hardware requirements
Anticipated explosion in data size posed scalability challenges
Heavy reliance on stored procedures for data transformation and reporting
Replicating functionalities of Data Vault architecture caused performance issues
Impact on the middle and reporting layers
Solution Highlights
Conducted a proof of concept (PoC) on Snowflake to showcase its advantages over the existing data warehousing framework
Designed a new architecture using AWS S3 as an intermediate staging area for the new EDW built on Snowflake
Categorized and replaced stored procedures based on their usage for data massaging and reporting
Developed a completely new dimension model and implemented Data Vault principles in the new data warehouse
Technology Used
- SQL server
- AWS S3
- Snowflake
- Tableau
Results that Speak Volumes
Enhanced data handling efficiency
Improved business intelligence through timely data availability
Accelerated data processing capabilities
Strengthened data security during transfer operations
