Data Quality & Observability
Data Quality
- Customer Data Integration: Ensuring that customer data from various sources is accurate, consistent, and duplicate-free to provide a single view of the customer for better service and marketing.
- Regulatory Compliance: Implementing data quality processes to meet standards set by regulations such as GDPR, HIPAA, or CCPA to ensure data is correctly processed and reported.
- Data Migration: When migrating data from legacy systems to new platforms, ensuring that the migrated data maintains its quality, is transformed correctly, and fits the new system's schema.
- Business Intelligence: Improving the accuracy of BI reports by ensuring the underlying data is clean and reliable, leading to better decision-making.
- Master Data Management (MDM): Creating and maintaining a single, consistent, and authoritative source of truth for critical business data.
Observability
- Performance Monitoring: Tracking and analyzing system performance metrics in real-time to identify and resolve issues promptly.
- Anomaly Detection: Using observability tools to detect unusual patterns that may indicate a security breach or system malfunction.
- Root Cause Analysis: Providing detailed logs, metrics, and traces to diagnose and address the underlying causes of issues in complex systems.
- User Experience Optimization: Monitoring applications to understand how users interact with them and where they may encounter issues or bottlenecks.
- Capacity Planning: Observing system utilization trends to predict scaling needs and optimize resource allocation.
- Service Level Agreement (SLA) Adherence: Monitoring systems to ensure they meet the performance and availability criteria specified in SLAs.
