This case study demonstrates how a major discount brokerage firm leveraged iceDQ to solve critical customer data synchronization challenges between their operational databases and cloud platform.
Download the full case study to discover how iceDQ automated daily data monitoring, ensuring 100% data accuracy while significantly reducing operational costs and compliance risks.
In today’s digital financial services landscape, accurate customer data is crucial for everything from tax calculations to marketing communications. When customer data resides in multiple systems, maintaining consistency becomes a complex challenge that can impact regulatory compliance and customer experience.
Key Challenges Addressed:
Tax calculation errors due to incorrect address and domicile information
Marketing compliance violations and campaign inefficiencies
A leading brokerage firm faced these exact challenges when their customer data, spread across multiple DB2 databases, needed to be synchronized with a centralized Snowflake cloud platform. Manual reconciliation attempts proved costly and inefficient.
Solution Implementation with iceDQ provided an automated data monitoring solution that performed:
Source data validation in DB2
Source-to-target reconciliation between DB2 and Snowflake
Business validation of consolidated data
Daily count checks and weekly detailed data comparisons
Over 200 validation rules across 50 tables
Key Results:
Enhanced operational efficiency through automation
Improved data accuracy and integrity
Faster implementation of monitoring rules
Better resource utilization
Accelerated marketing initiatives
Comprehensive reporting for quick issue resolution
Download the complete case study to learn how iceDQ can help your organization ensure data reliability and business readiness through automated data monitoring.
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