Daily Customer Data Monitoring – for Business Readiness

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:

1. Tax calculation errors due to incorrect address and domicile information
2. Marketing compliance violations and campaign inefficiencies
3. Regulatory non-compliance risks (GDPR, FINRA, BCBS 239)
4. Poor customer experience from data discrepancies
5. Revenue loss from missed marketing opportunities

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:

1. Source data validation in DB2
2. Source-to-target reconciliation between DB2 and Snowflake
3. Business validation of consolidated data
4. Daily count checks and weekly detailed data comparisons
5. Over 200 validation rules across 50 tables

Key Results:

1. Enhanced operational efficiency through automation
2. Improved data accuracy and integrity
3. Faster implementation of monitoring rules
4. Better resource utilization
5. Accelerated marketing initiatives
6. 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.