80% Query Performance Improvement for Ministry of Finance
The Challenge
The Ministry of Finance's SQL Server database was experiencing severe performance degradation, with critical financial reporting queries taking 15-20 minutes to execute. End-of-month closing processes were delayed by hours, impacting government operations and financial transparency. The existing infrastructure lacked proper indexing strategies, had inefficient query patterns, and showed signs of resource contention during peak usage periods.
The Strategy
- 1 Conduct comprehensive database performance audit to identify bottlenecks and root causes
- 2 Implement targeted index optimization strategy based on workload analysis and execution plans
- 3 Refactor critical queries using best practices and eliminate anti-patterns
- 4 Establish performance monitoring framework to prevent future degradation
🔍 Database Performance Audit
The Problem We Found
Initial analysis revealed missing indexes on high-traffic tables, inefficient join patterns in stored procedures, and outdated statistics causing poor execution plan choices. Heavy tempdb usage during peak hours indicated sorting and spilling issues.
Our Approach
- Deployed SQL Server Extended Events to capture query patterns and resource consumption
- Analyzed execution plans for top 50 resource-intensive queries
- Identified missing index recommendations and validated against workload
- Reviewed table statistics and fragmentation levels across all user databases
The Result
Identified 23 critical performance bottlenecks and created a prioritized remediation roadmap. Discovered that 5 frequently-executed stored procedures accounted for 65% of total CPU consumption.
Metrics
📊 Index Optimization Strategy
The Problem We Found
Critical tables had no covering indexes for common query patterns. Several tables had over-indexing on rarely-used columns, causing write performance degradation.
Our Approach
- Created 15 new covering indexes based on query workload analysis
- Removed 8 redundant and unused indexes to improve write performance
- Implemented filtered indexes for frequently-queried subsets of data
- Updated all statistics and enabled auto-update statistics with full scan
The Result
Query execution plans shifted from table scans to efficient index seeks. Average logical reads reduced by 85%. Insert/update operations saw 30% performance improvement due to reduced index overhead.
Metrics
⚡ Query Refactoring
The Problem We Found
Stored procedures contained scalar functions in WHERE clauses, implicit conversions, and inefficient cursor-based logic. Financial reporting queries used SELECT * and fetched unnecessary columns.
Our Approach
- Refactored 12 critical stored procedures to use set-based operations instead of cursors
- Eliminated scalar functions from WHERE clauses and rewrote as inline table-valued functions
- Added explicit data type conversions to avoid implicit conversion penalties
- Implemented column-level SELECT statements to reduce data transfer overhead
The Result
Monthly financial reporting process completion time reduced from 4.5 hours to 55 minutes. Real-time dashboard queries now execute in under 2 seconds, enabling live financial monitoring.
Metrics
Impact & Results
The performance optimization initiative transformed the Ministry of Finance's data operations. Query execution times improved by 80%, enabling real-time financial monitoring and reducing end-of-month closing procedures from 4.5 hours to under an hour. CPU utilization decreased from 92% to 45%, providing headroom for future growth. The finance team now processes critical reports 5x faster, improving government financial transparency and operational efficiency.
"Zatsys transformed our database performance beyond expectations. What used to take hours now completes in minutes. Our team can finally focus on financial analysis instead of waiting for reports to generate."
Facing Similar Challenges?
Let's discuss how we can help transform your data infrastructure.