MICROSOFT SQL SERVER 2022 - IMPLEMENTING DATA MODELS & REPORTS WITH SQL SERVER
The Microsoft SQL Server 2022 - Implementing Data Models & Reports with SQL Server course is a professional, analytics-focused program designed to equip participants with the skills required to design analytical data models and deliver reliable, high-performance reports using SQL Server-based data platforms. Built on data and analytics technologies from Microsoft, this course emphasizes data modeling for reporting, semantic layer design, query optimization for analytics, and report-ready data structures. Participants learn how to transform raw transactional data into clean, consistent, and performant models that support dashboards, operational reports, and business intelligence use cases. The program is ideal for professionals involved in reporting, analytics, BI development, and data preparation for decision-making. Course Objectives By the end of this course, participants will be able to: Design analytical data models optimized for reporting Implement star and snowflake schemas for BI workloads Prepare SQL Server data structures for reports and dashboards Write efficient analytical queries for reporting scenarios Manage data quality, consistency, and performance Support reporting tools with reliable, well-structured datasets
Course Curriculum
1
- Reporting and analytics concepts
- OLTP vs analytical workloads
- Role of data models in reporting
- SQL Server as an analytics platform
2
- End-to-end reporting architecture
- Data sources, staging, and presentation layers
- Data flow for reports
- Performance and scalability considerations
3
- Analytical data modeling principles
- Facts and dimensions
- Measures, attributes, and hierarchies
- Choosing the right model for reporting
4
- Star schema design
- Snowflake schema design
- Trade-offs and performance implications
- Real-world modeling scenarios
5
- Data cleansing and transformation concepts
- Handling missing and inconsistent data
- Aggregation strategies
- Managing slowly changing dimensions (overview)
6
- Designing fact tables
- Designing dimension tables
- Keys and relationships
- Managing historical data
7
- Analytical query patterns
- GROUP BY, HAVING, and aggregations
- Window functions for reporting
- Performance-aware reporting queries
8
- Creating reporting views
- Abstracting complexity from reports
- Managing schema stability
- Security considerations for reporting layers
9
- Indexing strategies for analytics
- Partitioning concepts
- Reducing query execution time
- Managing large data volumes
10
- Data refresh strategies
- Incremental updates
- Handling late-arriving data
- Scheduling and automation concepts
11
- Securing reporting datasets
- Row-level and object-level security concepts
- Managing access for report users
- Auditing and compliance considerations
12
- Supporting operational and analytical reports
- Optimizing datasets for dashboards
- Managing concurrency and workload isolation
- User experience considerations
13
- Data validation techniques
- Reconciliation and accuracy checks
- Managing data lineage
- Building trust in reporting data
14
- Monitoring report performance
- Diagnosing slow queries
- Identifying data model issues
- Troubleshooting data consistency problems
15
- Designing a complete reporting data model
- Implementing analytical queries
- Optimizing performance for reports
- Real-world reporting and analytics scenarios
16
- Business intelligence and reporting developers
- Data analysts and analytics professionals
- Database developers supporting reporting systems
- IT professionals responsible for enterprise reporting platforms
17
- Understanding of relational database concepts
- Basic SQL querying skills
- Familiarity with SQL Server environments is beneficial
This course includes
- 17+ Activity Modules
- 40 hours + lessons
- Lifetime access
- Certificate of completion
- Available on desktop and mobile
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