Mastering Advanced SQL Query Optimization for Enterprise Data Systems
You're deep in the trenches of enterprise data systems, but your queries still crawl when they should fly. The systems you manage are critical, and every millisecond of latency costs your organisation in performance, scalability, and user trust. You know suboptimal SQL isn't just a technical debt-it's a business risk. You’ve tried indexes, query rewrites, and execution plan reviews, yet results are inconsistent. Without a systematic, advanced framework for query optimization, you're stuck firefighting instead of leading innovation. Mastering Advanced SQL Query Optimization for Enterprise Data Systems is your blueprint to transform reactive troubleshooting into proactive mastery. This course takes you from query uncertainty to delivering high-efficiency, scalable SQL solutions in under 30 days, complete with a performance-validated optimization playbook ready for production deployment. A senior data architect at a Fortune 500 financial institution used these exact methods to reduce query runtime by 92% across their transaction reporting layer-cutting their cloud compute spend by $370,000 annually. This isn’t just theory. It’s battle-tested, enterprise-hardened practice used by top-tier performance engineers at high-load organisations. Here’s how this course is structured to help you get there.Course Format & Delivery Details This is a premium, self-paced learning experience designed for senior database professionals, enterprise data engineers, and performance-focused SQL architects who demand precision, clarity, and immediate applicability. Immediate, Lifetime Access – No Expiry, No Limits
Once enrolled, you gain full online access to all course materials with no time restrictions. The course is delivered on-demand, allowing you to learn at your own pace, on your schedule, with no fixed start dates or deadlines. - Typical completion time: 4 to 6 weeks with 6–8 hours per week of focused study
- Many learners implement core optimizations and see tangible query performance improvements in as little as 7 to 10 days
- All content is mobile-friendly and accessible 24/7 from any device, anywhere in the world
- Lifetime access ensures you can revisit modules, reinforce skills, and apply new techniques as your systems evolve
All future updates, advanced techniques, and newly validated strategies are included at no extra cost-your investment remains current, relevant, and powerful for years. Direct Instructor Guidance & Enterprise-Grade Support
You're not learning in isolation. This course includes structured guidance through expert-curated pathways, detailed examples, and real enterprise scenarios. Targeted support ensures your questions are addressed with precision. - Access to direct instructor insights via curated troubleshooting frameworks
- Regularly updated best practices based on real production systems
- Step-by-step walkthroughs of complex optimization sequences used in high-transaction environments
Certificate of Completion from The Art of Service
Upon finishing the course, you’ll earn a formal Certificate of Completion issued by The Art of Service-a globally trusted name in professional data and systems training. This certificate validates your advanced SQL optimization expertise and is recognised by enterprise hiring managers, internal promotion boards, and technical leadership teams. Transparent, One-Time Pricing – No Hidden Fees
The investment is straightforward and includes everything: all learning resources, performance frameworks, diagnostic templates, and certification. - No recurring fees
- No upcharges for updates or tools
- Payment accepted via Visa, Mastercard, and PayPal
Zero-Risk Enrollment with Full Satisfaction Guarantee
We remove all risk with a clear promise: If you complete the first two modules and don’t feel this course delivers exceptional value, insight, and immediate applicability, contact us for a full refund. Your access begins as soon as payment is confirmed, and your enrolment details will be sent in a follow-up email once your course access is fully prepared. “Will This Work For Me?” – Addressing Your Biggest Concern
This course works even if: - You’re managing legacy systems with complex, undocumented queries
- Your environment mixes OLTP and data warehouse workloads
- Your team uses multiple SQL platforms including Oracle, PostgreSQL, SQL Server, or MySQL
- You’ve already implemented indexes but still face performance bottlenecks
- You’re under pressure to reduce cloud costs tied to database compute
One data lead at a multinational e-commerce firm said: “I’ve read dozens of performance blogs and tuning guides. This is the first program that gives me a repeatable, audit-proof method to justify every optimization-my CTO now requests my reports before any schema changes.” The strategies are vendor-agnostic, platform-resilient, and built on deep query analysis patterns-not fleeting tricks. If you write, review, or optimise SQL in mission-critical systems, this course is engineered for your success.
Module 1: Foundations of Enterprise SQL Performance - Understanding the lifecycle of a SQL query in enterprise systems
- Differences between OLTP, OLAP, and hybrid workloads
- Key performance metrics: execution time, CPU cost, I/O operations, memory usage
- Core concepts: logical reads vs physical reads
- Query compilation and plan caching fundamentals
- Importance of statistics and cardinality estimation
- How parameter sniffing impacts consistent performance
- Role of the query optimizer across major database platforms
- Common misconceptions in query tuning
- Architectural limits of shared-nothing vs shared-disk databases
Module 2: Query Analysis & Diagnostic Frameworks - Systematic approach to query performance diagnosis
- Using execution plans to identify bottlenecks
- Reading and interpreting graphical and textual execution plans
- Identifying high-cost operators: scans, sorts, spills, and key lookups
- Correlating wait types with query inefficiency
- Using dynamic management views (DMVs) for performance insights
- Query store usage for historical plan comparison
- How to isolate top resource-consuming queries
- Baseline creation for performance regression detection
- Building a query performance scorecard for executive reporting
Module 3: Indexing at Scale – Beyond the Basics - Filtered indexes for high-cardinality, sparse data conditions
- Index design for covering queries with minimal overhead
- Columnstore indexes in transactional and analytical workloads
- Clustered vs non-clustered index trade-offs in large tables
- Index maintenance strategies for low-downtime environments
- Index fragmentation analysis and intelligent defragmentation
- Index usage statistics interpretation for cleanup decisions
- Composite index column order and selectivity principles
- Spatial and XML index optimization in enterprise schemas
- Index impact on insert, update, and delete performance
- Using missing index suggestions without falling into traps
- Index consolidation to reduce maintenance overhead
- Partitioning aligned indexes for large-scale data
- Index compression techniques for storage and speed
- Using function-based and expression indexes effectively
Module 4: Query Rewriting & Anti-Pattern Elimination - Eliminating implicit conversions in WHERE clauses
- Replacing cursors with set-based logic
- Transforming correlated subqueries into joins
- Avoiding SELECT * in production queries
- Using EXISTS instead of IN for large datasets
- Optimising NOT EXISTS and NOT IN scenarios
- Replacing UNION with UNION ALL when possible
- Minimising function usage in predicates
- Handling NULL comparisons efficiently
- Eliminating redundant joins and cartesian products
- Refactoring dynamic SQL for plan reuse
- Unnesting complex nested queries
- Common Table Expressions (CTEs) versus temp tables
- Strategic use of window functions to avoid self-joins
- Removing unnecessary sorting and DISTINCT operations
- Optimising CASE expressions in SELECT and WHERE
- Handling large IN lists with table joins
- Avoiding scalar user-defined functions in queries
Module 5: Join Optimization & Execution Strategies - Understanding nested loops, hash matches, and merge joins
- Choosing optimal join types based on data size and distribution
- Impact of join order on query plan efficiency
- Using hints selectively and responsibly
- Forcing join order with query structure
- Statistics-driven join estimation errors and corrections
- Optimising outer joins for minimal overhead
- Handling cross joins in aggregate reporting safely
- Adaptive joins and their enterprise implications
- Batch mode processing for large join sets
- Join elimination through constraints and logical inference
- Optimising joins on computed columns
- Index spooling and its performance implications
- Memory grant issues in hash join operations
- Tuning join conditions with inequality operators
Module 6: Temp Tables, CTEs, and Intermediate Storage - When to use temp tables versus table variables
- Statistics on temp objects and their impact on plans
- Indexed temp tables for repeated access
- CTEs and materialization behaviour across platforms
- Reducing recompilation of procedures using temp tables
- Global temp tables in multi-user scenarios
- Disk vs memory tempdb configurations
- Monitoring tempdb contention and spills
- Partitioning strategies for intermediate result sets
- Using derived tables to short-circuit execution
- Staging tables for ETL performance tuning
- Reducing I/O in temp object operations
- Architecting for minimal spooling
- Plan forcing for temp table queries
- Caching intermediate results without side effects
Module 7: Stored Procedures & Parameterization - Plan reuse and procedure cache management
- Parameter sniffing: causes, consequences, and control
- Using OPTIMIZE FOR and OPTIMIZE FOR UNKNOWN
- Local variable assignment to break sniffing
- Using RECOMPILE selectively for dynamic workloads
- Plan guides for legacy procedures
- Forcing parameterization and its risks
- Handling optional parameters efficiently
- Reducing compile time in frequently executed procs
- Using multiple statement procedures wisely
- Logging and monitoring procedure performance over time
- Managing transaction scope in stored logic
- Dynamic SQL execution and security considerations
- Preparing for procedure migration to APIs
Module 8: Concurrency & Locking Performance - Identifying blocking chains and deadlocks
- Using isolation levels to reduce lock contention
- Snapshot isolation and its impact on tempdb
- Read uncommitted risks versus benefits
- Lock escalation and prevention strategies
- Row versioning overhead analysis
- Minimising shared locks in reporting queries
- Using NOLOCK responsibly with caveats
- Indexing to reduce lock duration
- Deadlock graph interpretation and resolution
- Lock hints and their strategic application
- Concurrency control in distributed transactions
- Monitoring lock waits and duration
- Partition-level locking benefits
- Balancing consistency and performance
Module 9: Statistics & Cardinality Deep Dive - Automatic vs manual statistics creation
- Statistics update thresholds and tuning
- Fullscan vs sampled statistics for accuracy
- Impact of histogram steps on estimation
- Multi-column statistics and correlation
- Filtered statistics for skewed data
- Trace flags for advanced statistics control
- Statistics persistence in availability groups
- Monitoring statistic staleness proactively
- Cardinality estimation models: legacy vs new
- Query optimizer behaviour under estimation errors
- Using query hints to adjust cardinality
- Statistics on computed and JSON columns
- System-generated statistics management
- Testing statistics impact with controlled workloads
Module 10: Execution Plan Analysis & Plan Forcing - Interpreting cost percentages accurately
- Understanding estimated vs actual plans
- Identifying implicit conversions in plans
- Operator cost versus I/O and CPU breakdown
- Memory grant warnings and their resolution
- Operator parallelism and degree of parallelism tuning
- Parallel vs serial plan trade-offs
- Forcing plans with plan guides and query store
- Handling plan regression with forced execution
- Persisting optimal plans across restarts
- Plan freezing in production-critical queries
- Monitoring plan changes with automated alerts
- XML execution plan analysis for automation
- Comparing multiple plans for regression analysis
- Using plan hints to guide without over-constraining
Module 11: Partitioning & Large Table Strategies - Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Understanding the lifecycle of a SQL query in enterprise systems
- Differences between OLTP, OLAP, and hybrid workloads
- Key performance metrics: execution time, CPU cost, I/O operations, memory usage
- Core concepts: logical reads vs physical reads
- Query compilation and plan caching fundamentals
- Importance of statistics and cardinality estimation
- How parameter sniffing impacts consistent performance
- Role of the query optimizer across major database platforms
- Common misconceptions in query tuning
- Architectural limits of shared-nothing vs shared-disk databases
Module 2: Query Analysis & Diagnostic Frameworks - Systematic approach to query performance diagnosis
- Using execution plans to identify bottlenecks
- Reading and interpreting graphical and textual execution plans
- Identifying high-cost operators: scans, sorts, spills, and key lookups
- Correlating wait types with query inefficiency
- Using dynamic management views (DMVs) for performance insights
- Query store usage for historical plan comparison
- How to isolate top resource-consuming queries
- Baseline creation for performance regression detection
- Building a query performance scorecard for executive reporting
Module 3: Indexing at Scale – Beyond the Basics - Filtered indexes for high-cardinality, sparse data conditions
- Index design for covering queries with minimal overhead
- Columnstore indexes in transactional and analytical workloads
- Clustered vs non-clustered index trade-offs in large tables
- Index maintenance strategies for low-downtime environments
- Index fragmentation analysis and intelligent defragmentation
- Index usage statistics interpretation for cleanup decisions
- Composite index column order and selectivity principles
- Spatial and XML index optimization in enterprise schemas
- Index impact on insert, update, and delete performance
- Using missing index suggestions without falling into traps
- Index consolidation to reduce maintenance overhead
- Partitioning aligned indexes for large-scale data
- Index compression techniques for storage and speed
- Using function-based and expression indexes effectively
Module 4: Query Rewriting & Anti-Pattern Elimination - Eliminating implicit conversions in WHERE clauses
- Replacing cursors with set-based logic
- Transforming correlated subqueries into joins
- Avoiding SELECT * in production queries
- Using EXISTS instead of IN for large datasets
- Optimising NOT EXISTS and NOT IN scenarios
- Replacing UNION with UNION ALL when possible
- Minimising function usage in predicates
- Handling NULL comparisons efficiently
- Eliminating redundant joins and cartesian products
- Refactoring dynamic SQL for plan reuse
- Unnesting complex nested queries
- Common Table Expressions (CTEs) versus temp tables
- Strategic use of window functions to avoid self-joins
- Removing unnecessary sorting and DISTINCT operations
- Optimising CASE expressions in SELECT and WHERE
- Handling large IN lists with table joins
- Avoiding scalar user-defined functions in queries
Module 5: Join Optimization & Execution Strategies - Understanding nested loops, hash matches, and merge joins
- Choosing optimal join types based on data size and distribution
- Impact of join order on query plan efficiency
- Using hints selectively and responsibly
- Forcing join order with query structure
- Statistics-driven join estimation errors and corrections
- Optimising outer joins for minimal overhead
- Handling cross joins in aggregate reporting safely
- Adaptive joins and their enterprise implications
- Batch mode processing for large join sets
- Join elimination through constraints and logical inference
- Optimising joins on computed columns
- Index spooling and its performance implications
- Memory grant issues in hash join operations
- Tuning join conditions with inequality operators
Module 6: Temp Tables, CTEs, and Intermediate Storage - When to use temp tables versus table variables
- Statistics on temp objects and their impact on plans
- Indexed temp tables for repeated access
- CTEs and materialization behaviour across platforms
- Reducing recompilation of procedures using temp tables
- Global temp tables in multi-user scenarios
- Disk vs memory tempdb configurations
- Monitoring tempdb contention and spills
- Partitioning strategies for intermediate result sets
- Using derived tables to short-circuit execution
- Staging tables for ETL performance tuning
- Reducing I/O in temp object operations
- Architecting for minimal spooling
- Plan forcing for temp table queries
- Caching intermediate results without side effects
Module 7: Stored Procedures & Parameterization - Plan reuse and procedure cache management
- Parameter sniffing: causes, consequences, and control
- Using OPTIMIZE FOR and OPTIMIZE FOR UNKNOWN
- Local variable assignment to break sniffing
- Using RECOMPILE selectively for dynamic workloads
- Plan guides for legacy procedures
- Forcing parameterization and its risks
- Handling optional parameters efficiently
- Reducing compile time in frequently executed procs
- Using multiple statement procedures wisely
- Logging and monitoring procedure performance over time
- Managing transaction scope in stored logic
- Dynamic SQL execution and security considerations
- Preparing for procedure migration to APIs
Module 8: Concurrency & Locking Performance - Identifying blocking chains and deadlocks
- Using isolation levels to reduce lock contention
- Snapshot isolation and its impact on tempdb
- Read uncommitted risks versus benefits
- Lock escalation and prevention strategies
- Row versioning overhead analysis
- Minimising shared locks in reporting queries
- Using NOLOCK responsibly with caveats
- Indexing to reduce lock duration
- Deadlock graph interpretation and resolution
- Lock hints and their strategic application
- Concurrency control in distributed transactions
- Monitoring lock waits and duration
- Partition-level locking benefits
- Balancing consistency and performance
Module 9: Statistics & Cardinality Deep Dive - Automatic vs manual statistics creation
- Statistics update thresholds and tuning
- Fullscan vs sampled statistics for accuracy
- Impact of histogram steps on estimation
- Multi-column statistics and correlation
- Filtered statistics for skewed data
- Trace flags for advanced statistics control
- Statistics persistence in availability groups
- Monitoring statistic staleness proactively
- Cardinality estimation models: legacy vs new
- Query optimizer behaviour under estimation errors
- Using query hints to adjust cardinality
- Statistics on computed and JSON columns
- System-generated statistics management
- Testing statistics impact with controlled workloads
Module 10: Execution Plan Analysis & Plan Forcing - Interpreting cost percentages accurately
- Understanding estimated vs actual plans
- Identifying implicit conversions in plans
- Operator cost versus I/O and CPU breakdown
- Memory grant warnings and their resolution
- Operator parallelism and degree of parallelism tuning
- Parallel vs serial plan trade-offs
- Forcing plans with plan guides and query store
- Handling plan regression with forced execution
- Persisting optimal plans across restarts
- Plan freezing in production-critical queries
- Monitoring plan changes with automated alerts
- XML execution plan analysis for automation
- Comparing multiple plans for regression analysis
- Using plan hints to guide without over-constraining
Module 11: Partitioning & Large Table Strategies - Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Filtered indexes for high-cardinality, sparse data conditions
- Index design for covering queries with minimal overhead
- Columnstore indexes in transactional and analytical workloads
- Clustered vs non-clustered index trade-offs in large tables
- Index maintenance strategies for low-downtime environments
- Index fragmentation analysis and intelligent defragmentation
- Index usage statistics interpretation for cleanup decisions
- Composite index column order and selectivity principles
- Spatial and XML index optimization in enterprise schemas
- Index impact on insert, update, and delete performance
- Using missing index suggestions without falling into traps
- Index consolidation to reduce maintenance overhead
- Partitioning aligned indexes for large-scale data
- Index compression techniques for storage and speed
- Using function-based and expression indexes effectively
Module 4: Query Rewriting & Anti-Pattern Elimination - Eliminating implicit conversions in WHERE clauses
- Replacing cursors with set-based logic
- Transforming correlated subqueries into joins
- Avoiding SELECT * in production queries
- Using EXISTS instead of IN for large datasets
- Optimising NOT EXISTS and NOT IN scenarios
- Replacing UNION with UNION ALL when possible
- Minimising function usage in predicates
- Handling NULL comparisons efficiently
- Eliminating redundant joins and cartesian products
- Refactoring dynamic SQL for plan reuse
- Unnesting complex nested queries
- Common Table Expressions (CTEs) versus temp tables
- Strategic use of window functions to avoid self-joins
- Removing unnecessary sorting and DISTINCT operations
- Optimising CASE expressions in SELECT and WHERE
- Handling large IN lists with table joins
- Avoiding scalar user-defined functions in queries
Module 5: Join Optimization & Execution Strategies - Understanding nested loops, hash matches, and merge joins
- Choosing optimal join types based on data size and distribution
- Impact of join order on query plan efficiency
- Using hints selectively and responsibly
- Forcing join order with query structure
- Statistics-driven join estimation errors and corrections
- Optimising outer joins for minimal overhead
- Handling cross joins in aggregate reporting safely
- Adaptive joins and their enterprise implications
- Batch mode processing for large join sets
- Join elimination through constraints and logical inference
- Optimising joins on computed columns
- Index spooling and its performance implications
- Memory grant issues in hash join operations
- Tuning join conditions with inequality operators
Module 6: Temp Tables, CTEs, and Intermediate Storage - When to use temp tables versus table variables
- Statistics on temp objects and their impact on plans
- Indexed temp tables for repeated access
- CTEs and materialization behaviour across platforms
- Reducing recompilation of procedures using temp tables
- Global temp tables in multi-user scenarios
- Disk vs memory tempdb configurations
- Monitoring tempdb contention and spills
- Partitioning strategies for intermediate result sets
- Using derived tables to short-circuit execution
- Staging tables for ETL performance tuning
- Reducing I/O in temp object operations
- Architecting for minimal spooling
- Plan forcing for temp table queries
- Caching intermediate results without side effects
Module 7: Stored Procedures & Parameterization - Plan reuse and procedure cache management
- Parameter sniffing: causes, consequences, and control
- Using OPTIMIZE FOR and OPTIMIZE FOR UNKNOWN
- Local variable assignment to break sniffing
- Using RECOMPILE selectively for dynamic workloads
- Plan guides for legacy procedures
- Forcing parameterization and its risks
- Handling optional parameters efficiently
- Reducing compile time in frequently executed procs
- Using multiple statement procedures wisely
- Logging and monitoring procedure performance over time
- Managing transaction scope in stored logic
- Dynamic SQL execution and security considerations
- Preparing for procedure migration to APIs
Module 8: Concurrency & Locking Performance - Identifying blocking chains and deadlocks
- Using isolation levels to reduce lock contention
- Snapshot isolation and its impact on tempdb
- Read uncommitted risks versus benefits
- Lock escalation and prevention strategies
- Row versioning overhead analysis
- Minimising shared locks in reporting queries
- Using NOLOCK responsibly with caveats
- Indexing to reduce lock duration
- Deadlock graph interpretation and resolution
- Lock hints and their strategic application
- Concurrency control in distributed transactions
- Monitoring lock waits and duration
- Partition-level locking benefits
- Balancing consistency and performance
Module 9: Statistics & Cardinality Deep Dive - Automatic vs manual statistics creation
- Statistics update thresholds and tuning
- Fullscan vs sampled statistics for accuracy
- Impact of histogram steps on estimation
- Multi-column statistics and correlation
- Filtered statistics for skewed data
- Trace flags for advanced statistics control
- Statistics persistence in availability groups
- Monitoring statistic staleness proactively
- Cardinality estimation models: legacy vs new
- Query optimizer behaviour under estimation errors
- Using query hints to adjust cardinality
- Statistics on computed and JSON columns
- System-generated statistics management
- Testing statistics impact with controlled workloads
Module 10: Execution Plan Analysis & Plan Forcing - Interpreting cost percentages accurately
- Understanding estimated vs actual plans
- Identifying implicit conversions in plans
- Operator cost versus I/O and CPU breakdown
- Memory grant warnings and their resolution
- Operator parallelism and degree of parallelism tuning
- Parallel vs serial plan trade-offs
- Forcing plans with plan guides and query store
- Handling plan regression with forced execution
- Persisting optimal plans across restarts
- Plan freezing in production-critical queries
- Monitoring plan changes with automated alerts
- XML execution plan analysis for automation
- Comparing multiple plans for regression analysis
- Using plan hints to guide without over-constraining
Module 11: Partitioning & Large Table Strategies - Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Understanding nested loops, hash matches, and merge joins
- Choosing optimal join types based on data size and distribution
- Impact of join order on query plan efficiency
- Using hints selectively and responsibly
- Forcing join order with query structure
- Statistics-driven join estimation errors and corrections
- Optimising outer joins for minimal overhead
- Handling cross joins in aggregate reporting safely
- Adaptive joins and their enterprise implications
- Batch mode processing for large join sets
- Join elimination through constraints and logical inference
- Optimising joins on computed columns
- Index spooling and its performance implications
- Memory grant issues in hash join operations
- Tuning join conditions with inequality operators
Module 6: Temp Tables, CTEs, and Intermediate Storage - When to use temp tables versus table variables
- Statistics on temp objects and their impact on plans
- Indexed temp tables for repeated access
- CTEs and materialization behaviour across platforms
- Reducing recompilation of procedures using temp tables
- Global temp tables in multi-user scenarios
- Disk vs memory tempdb configurations
- Monitoring tempdb contention and spills
- Partitioning strategies for intermediate result sets
- Using derived tables to short-circuit execution
- Staging tables for ETL performance tuning
- Reducing I/O in temp object operations
- Architecting for minimal spooling
- Plan forcing for temp table queries
- Caching intermediate results without side effects
Module 7: Stored Procedures & Parameterization - Plan reuse and procedure cache management
- Parameter sniffing: causes, consequences, and control
- Using OPTIMIZE FOR and OPTIMIZE FOR UNKNOWN
- Local variable assignment to break sniffing
- Using RECOMPILE selectively for dynamic workloads
- Plan guides for legacy procedures
- Forcing parameterization and its risks
- Handling optional parameters efficiently
- Reducing compile time in frequently executed procs
- Using multiple statement procedures wisely
- Logging and monitoring procedure performance over time
- Managing transaction scope in stored logic
- Dynamic SQL execution and security considerations
- Preparing for procedure migration to APIs
Module 8: Concurrency & Locking Performance - Identifying blocking chains and deadlocks
- Using isolation levels to reduce lock contention
- Snapshot isolation and its impact on tempdb
- Read uncommitted risks versus benefits
- Lock escalation and prevention strategies
- Row versioning overhead analysis
- Minimising shared locks in reporting queries
- Using NOLOCK responsibly with caveats
- Indexing to reduce lock duration
- Deadlock graph interpretation and resolution
- Lock hints and their strategic application
- Concurrency control in distributed transactions
- Monitoring lock waits and duration
- Partition-level locking benefits
- Balancing consistency and performance
Module 9: Statistics & Cardinality Deep Dive - Automatic vs manual statistics creation
- Statistics update thresholds and tuning
- Fullscan vs sampled statistics for accuracy
- Impact of histogram steps on estimation
- Multi-column statistics and correlation
- Filtered statistics for skewed data
- Trace flags for advanced statistics control
- Statistics persistence in availability groups
- Monitoring statistic staleness proactively
- Cardinality estimation models: legacy vs new
- Query optimizer behaviour under estimation errors
- Using query hints to adjust cardinality
- Statistics on computed and JSON columns
- System-generated statistics management
- Testing statistics impact with controlled workloads
Module 10: Execution Plan Analysis & Plan Forcing - Interpreting cost percentages accurately
- Understanding estimated vs actual plans
- Identifying implicit conversions in plans
- Operator cost versus I/O and CPU breakdown
- Memory grant warnings and their resolution
- Operator parallelism and degree of parallelism tuning
- Parallel vs serial plan trade-offs
- Forcing plans with plan guides and query store
- Handling plan regression with forced execution
- Persisting optimal plans across restarts
- Plan freezing in production-critical queries
- Monitoring plan changes with automated alerts
- XML execution plan analysis for automation
- Comparing multiple plans for regression analysis
- Using plan hints to guide without over-constraining
Module 11: Partitioning & Large Table Strategies - Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Plan reuse and procedure cache management
- Parameter sniffing: causes, consequences, and control
- Using OPTIMIZE FOR and OPTIMIZE FOR UNKNOWN
- Local variable assignment to break sniffing
- Using RECOMPILE selectively for dynamic workloads
- Plan guides for legacy procedures
- Forcing parameterization and its risks
- Handling optional parameters efficiently
- Reducing compile time in frequently executed procs
- Using multiple statement procedures wisely
- Logging and monitoring procedure performance over time
- Managing transaction scope in stored logic
- Dynamic SQL execution and security considerations
- Preparing for procedure migration to APIs
Module 8: Concurrency & Locking Performance - Identifying blocking chains and deadlocks
- Using isolation levels to reduce lock contention
- Snapshot isolation and its impact on tempdb
- Read uncommitted risks versus benefits
- Lock escalation and prevention strategies
- Row versioning overhead analysis
- Minimising shared locks in reporting queries
- Using NOLOCK responsibly with caveats
- Indexing to reduce lock duration
- Deadlock graph interpretation and resolution
- Lock hints and their strategic application
- Concurrency control in distributed transactions
- Monitoring lock waits and duration
- Partition-level locking benefits
- Balancing consistency and performance
Module 9: Statistics & Cardinality Deep Dive - Automatic vs manual statistics creation
- Statistics update thresholds and tuning
- Fullscan vs sampled statistics for accuracy
- Impact of histogram steps on estimation
- Multi-column statistics and correlation
- Filtered statistics for skewed data
- Trace flags for advanced statistics control
- Statistics persistence in availability groups
- Monitoring statistic staleness proactively
- Cardinality estimation models: legacy vs new
- Query optimizer behaviour under estimation errors
- Using query hints to adjust cardinality
- Statistics on computed and JSON columns
- System-generated statistics management
- Testing statistics impact with controlled workloads
Module 10: Execution Plan Analysis & Plan Forcing - Interpreting cost percentages accurately
- Understanding estimated vs actual plans
- Identifying implicit conversions in plans
- Operator cost versus I/O and CPU breakdown
- Memory grant warnings and their resolution
- Operator parallelism and degree of parallelism tuning
- Parallel vs serial plan trade-offs
- Forcing plans with plan guides and query store
- Handling plan regression with forced execution
- Persisting optimal plans across restarts
- Plan freezing in production-critical queries
- Monitoring plan changes with automated alerts
- XML execution plan analysis for automation
- Comparing multiple plans for regression analysis
- Using plan hints to guide without over-constraining
Module 11: Partitioning & Large Table Strategies - Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Automatic vs manual statistics creation
- Statistics update thresholds and tuning
- Fullscan vs sampled statistics for accuracy
- Impact of histogram steps on estimation
- Multi-column statistics and correlation
- Filtered statistics for skewed data
- Trace flags for advanced statistics control
- Statistics persistence in availability groups
- Monitoring statistic staleness proactively
- Cardinality estimation models: legacy vs new
- Query optimizer behaviour under estimation errors
- Using query hints to adjust cardinality
- Statistics on computed and JSON columns
- System-generated statistics management
- Testing statistics impact with controlled workloads
Module 10: Execution Plan Analysis & Plan Forcing - Interpreting cost percentages accurately
- Understanding estimated vs actual plans
- Identifying implicit conversions in plans
- Operator cost versus I/O and CPU breakdown
- Memory grant warnings and their resolution
- Operator parallelism and degree of parallelism tuning
- Parallel vs serial plan trade-offs
- Forcing plans with plan guides and query store
- Handling plan regression with forced execution
- Persisting optimal plans across restarts
- Plan freezing in production-critical queries
- Monitoring plan changes with automated alerts
- XML execution plan analysis for automation
- Comparing multiple plans for regression analysis
- Using plan hints to guide without over-constraining
Module 11: Partitioning & Large Table Strategies - Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Horizontal partitioning for query pruning
- Choosing partition keys based on access patterns
- Partition switching for fast data loads
- Handling partition elimination in queries
- Indexing across partitioned tables
- Aligning indexes with partition scheme
- Maintenance automation for large partitions
- Sliding window pattern for data retention
- Handling cross-partition queries efficiently
- Statistics on partitioned tables
- Partition splitting and merging strategies
- Archiving strategies using partitioning
- Monitoring partition health and balance
- Using partitioning in cloud-based systems
- Performance gain validation techniques
Module 12: Cloud & Distributed Database Optimization - Query optimization in AWS Aurora, Azure SQL, and Google Cloud SQL
- Managing performance in serverless database tiers
- Understanding cloud-specific wait types
- Scaling read replicas effectively
- Latency considerations in distributed queries
- Tuning for elastic pools and DTU models
- Monitoring CPU and memory limits in cloud
- Cost-based optimization to reduce cloud spend
- Data locality and federated query performance
- Shard-aware query routing principles
- Using distributed cache alongside SQL
- Handling connection pooling in cloud apps
- Auto-tuning features in managed services
- Backup and restore impact on query workloads
- Monitoring cloud database performance with third-party tools
Module 13: Query Optimization in ETL & Data Pipelines - Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Minimising logging in bulk operations
- Optimising INSERT SELECT patterns
- Using minimal logging with TABLOCK and bulk operations
- Batching large updates and deletes
- Using merge statements efficiently
- Handling slowly changing dimensions with performance in mind
- Indexing strategies during ETL loads
- Temp table reuse in staging areas
- Parallelising ETL streams without contention
- Monitoring pipeline duration and bottlenecks
- Reducing transaction log growth in ETL
- Using change data capture vs triggers
- Partition switching in data warehouse loads
- Pre-aggregating data for downstream queries
- Handling incremental loads with window functions
Module 14: Monitoring, Governance & Performance Culture - Building a query performance dashboard
- Setting up alerts for long-running queries
- Creating a query review checklist for code commits
- Enforcing optimization standards in CI/CD
- Developing a performance tuning playbook
- Conducting query performance audits
- Reporting optimization savings to finance teams
- Training junior developers on optimization principles
- Integrating query reviews into sprint planning
- Using query fingerprints for duplicate detection
- Automating regression testing for SQL changes
- Documenting optimization rationale for audit trails
- Establishing a production change approval workflow
- Performance benchmarking before and after changes
- Creating executive summaries from technical data
Module 15: Advanced Optimization Case Studies & Real-World Projects - Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework
Module 16: Certification, Next Steps & Career Advancement - Final assessment: diagnose and optimise a production-grade query set
- Submit your optimization report for review
- Receive feedback and performance score
- Earn your Certificate of Completion from The Art of Service
- Add the certification to LinkedIn and professional profiles
- Strategies for demonstrating ROI to your manager
- Using your playbook in promotion discussions
- Preparing for advanced roles: Principal DBA, Data Architect, Performance Lead
- Accessing exclusive community forums for alumni
- Staying updated with new optimization patterns
- Leveraging the course materials for internal training
- Building a personal brand around SQL excellence
- Contributing case studies to enterprise knowledge bases
- Transitioning from tactical fixes to strategic influence
- Where to focus next: AI query tuning, real-time analytics, or platform architecture
- Optimising a 12-hour financial roll-up to under 45 minutes
- Fixing parameter sniffing in a high-frequency trading log query
- Reducing I/O in a customer 360 report with 18 joins
- Resolving a deadlock storm in a global inventory system
- Refactoring a cursor-based reconciliation process to set logic
- Improving concurrency in a multi-tenant SaaS application
- Scaling a key customer dashboard from 20 to 20,000 users
- Reducing cloud spend by 68% in a data warehouse
- Handling a 2.3 billion row table with sub-second response
- Optimising JSON querying in a document-heavy schema
- Fixing a memory grant timeout in a reporting aggregate
- Tuning a geospatial query with spatial indexes
- Improving a recursive hierarchy query with materialised paths
- Handling time-series data with optimal partitioning
- Reducing log shipping latency through query tuning
- Building a reusable performance validation framework