Course Introduction
The Microsoft SQL Server Administration for Analytics Training Course provides a comprehensive framework for administering SQL Server environments that support business intelligence, data warehousing, reporting, advanced analytics, and enterprise data platforms. It equips participants with practical skills for configuring, securing, monitoring, optimizing, and maintaining SQL Server environments that handle complex analytical workloads and growing data volumes.
The course explores the full administration lifecycle of Microsoft SQL Server, including installation, configuration, database management, storage, security, backup and recovery, maintenance, monitoring, performance tuning, and capacity planning. Particular attention is given to the requirements of analytics environments, where large datasets, complex queries, concurrent users, data transformation processes, reporting workloads, and resource-intensive operations can significantly affect database performance.
A major focus is placed on SQL Server performance monitoring and workload analysis. Participants learn how to monitor CPU, memory, storage I/O, wait statistics, query execution, indexing, blocking, concurrency, tempdb utilization, and database activity. They develop the ability to establish performance baselines, identify bottlenecks, investigate abnormal workloads, and implement structured optimization strategies for analytical databases.
The program also addresses SQL Server capabilities supporting modern analytics, including data warehouse administration, columnstore indexing, partitioning, analytical query optimization, integration with ETL processes, reporting workloads, and scalable storage architectures. Participants examine how database configuration and administrative decisions influence data loading, transformation, reporting, dashboard performance, and analytical query execution.
Through practical exercises, participants develop SQL Server administration procedures, security models, backup and recovery plans, monitoring dashboards, performance baselines, indexing strategies, maintenance schedules, capacity plans, and analytical workload optimization recommendations. The training emphasizes realistic administration scenarios involving data warehouses, reporting databases, business intelligence platforms, and enterprise analytical applications.
By the end of the Microsoft SQL Server Administration for Analytics Training Course, participants will be able to administer SQL Server environments supporting analytics, monitor and optimize database performance, manage analytical workloads, secure data platforms, implement reliable recovery processes, and support scalable data warehouse operations. They will also be able to establish proactive monitoring and continuous improvement practices that improve reliability, performance, and availability for analytics services.
Duration
10 days
Who Should Attend
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SQL Server database administrators responsible for managing databases that support business intelligence, reporting, analytics, and data warehousing.
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Database engineers responsible for SQL Server configuration, maintenance, performance optimization, availability, and analytical workload management.
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Data engineers working with SQL Server data warehouses, ETL pipelines, analytical databases, and enterprise data platforms.
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Business intelligence professionals responsible for reporting environments, analytical applications, dashboards, and data warehouse operations.
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Data analysts and analytics professionals seeking stronger technical knowledge of SQL Server administration and analytical database performance.
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Systems administrators managing Windows infrastructure, storage, compute resources, networking, and platforms hosting SQL Server environments.
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DevOps and platform engineers responsible for SQL Server deployment, automation, monitoring, infrastructure management, and operational reliability.
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Cloud engineers administering SQL Server workloads across Microsoft Azure, hybrid infrastructure, virtualized environments, and enterprise platforms.
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SQL developers seeking advanced understanding of database performance, indexing, query execution, storage, and analytical workload behavior.
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Data warehouse professionals responsible for dimensional models, large analytical datasets, data loading, partitioning, and warehouse performance.
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IT operations professionals monitoring database availability, resource consumption, incidents, service performance, and operational capacity.
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Cybersecurity and database security professionals responsible for authentication, authorization, auditing, encryption, and SQL Server data protection.
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Performance engineers and technical specialists investigating SQL Server bottlenecks, query performance, resource contention, and workload behavior.
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IT managers and technical leads overseeing SQL Server infrastructure, analytics platforms, database performance, and operational governance.
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Consultants and technical professionals implementing SQL Server modernization, analytics infrastructure, data warehouse, migration, and performance improvement initiatives.
Course Objectives
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Develop a comprehensive understanding of Microsoft SQL Server architecture, components, administration principles, and analytical database operating requirements.
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Install, configure, and manage SQL Server environments designed to support business intelligence, reporting, data warehousing, and analytical workloads.
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Create and administer databases, schemas, users, roles, permissions, storage structures, filegroups, and other essential SQL Server objects.
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Configure SQL Server security, authentication, authorization, encryption, auditing, access controls, and governance mechanisms for analytics environments.
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Monitor SQL Server health and performance using dynamic management views, performance counters, Query Store, logs, wait statistics, and workload metrics.
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Analyze query execution plans and analytical workloads to identify inefficient operations, resource bottlenecks, indexing problems, and optimization opportunities.
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Optimize SQL Server performance through indexing, partitioning, statistics management, memory configuration, tempdb optimization, and query tuning.
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Administer data warehouse environments by managing large tables, columnstore indexes, partitioning strategies, data loading processes, and analytical storage structures.
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Implement SQL Server backup, restore, disaster recovery, high availability, and business continuity practices suitable for enterprise analytics platforms.
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Diagnose blocking, deadlocks, storage bottlenecks, excessive resource consumption, slow queries, ETL-related issues, and analytical workload performance problems.
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Establish monitoring dashboards, performance baselines, alerts, capacity plans, and operational metrics that support proactive SQL Server performance management.
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Develop an integrated SQL Server administration strategy that supports analytics reliability, scalability, security, availability, performance, and long-term data platform efficiency.
Comprehensive Course Outline
Module 1: SQL Server Architecture and Analytics Administration Foundations
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Microsoft SQL Server architecture, database engine components, instances, databases, schemas, storage structures, services, and administrative dependencies.
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Understanding SQL Server processes, connections, sessions, transactions, memory structures, buffer pool, storage engine, query processor, and analytical workloads.
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Differences between transactional and analytical database requirements, including workload patterns, concurrency, data volume, query complexity, and resource utilization.
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Establishing administration standards for SQL Server analytics environments covering documentation, configuration management, maintenance, monitoring, security, and change control.
Module 2: SQL Server Installation, Configuration and Environment Management
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Installing and configuring SQL Server instances for development, testing, staging, production, data warehouse, reporting, and analytics environments.
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Managing server and database configuration parameters covering memory, parallelism, cost thresholds, connections, storage, recovery models, and workload requirements.
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Configuring SQL Server services, database files, filegroups, storage locations, tempdb, startup options, and environment-specific settings.
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Developing standardized SQL Server configurations that support analytical performance, operational consistency, maintainability, scalability, and controlled administration.
Module 3: Database, Schema and Security Administration
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Creating and managing SQL Server databases, schemas, tables, views, stored procedures, functions, sequences, synonyms, and analytical database objects.
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Managing logins, database users, roles, permissions, ownership, application accounts, service accounts, and administrative privileges.
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Implementing role-based access control and least-privilege principles for analysts, developers, applications, administrators, reporting users, and data engineering teams.
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Establishing SQL Server security administration practices covering access reviews, privilege management, separation of duties, and secure database operations.
Module 4: SQL Server Security, Auditing and Data Protection
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Configuring Windows and SQL Server authentication, contained database users, service accounts, credential management, and secure access controls.
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Applying encryption technologies, including Transparent Data Encryption, encrypted connections, backup encryption, and appropriate key management practices.
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Configuring SQL Server auditing, extended events, security logs, access monitoring, and administrative activity tracking for analytics environments.
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Assessing security configurations to identify excessive privileges, weak controls, exposed services, inappropriate access, and data protection gaps.
Module 5: Storage Architecture and Data Warehouse Administration
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Designing SQL Server storage architectures using data files, transaction logs, filegroups, partition schemes, storage tiers, and appropriate disk configurations.
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Administering data warehouse tables, large datasets, staging areas, fact tables, dimension tables, aggregates, and analytical storage structures.
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Managing data growth, storage utilization, file expansion, capacity forecasting, data placement, and storage performance requirements.
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Applying storage management practices that balance analytical performance, scalability, availability, maintenance requirements, and infrastructure costs.
Module 6: Backup, Restore and Disaster Recovery for Analytics
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Designing SQL Server backup strategies using full, differential, transaction log, copy-only, and specialized backup approaches for analytical environments.
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Managing recovery models, backup schedules, retention policies, backup validation, restoration procedures, and point-in-time recovery.
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Developing disaster recovery plans for data warehouses, reporting databases, analytical applications, and critical data services.
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Conducting recovery testing and validating database consistency, data availability, service dependencies, restoration performance, and recovery objectives.
Module 7: SQL Server Monitoring and Performance Observability
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Monitoring SQL Server CPU, memory, storage I/O, database activity, connections, waits, transactions, queries, tempdb, and system resource utilization.
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Using Dynamic Management Views, Performance Monitor, Extended Events, Query Store, SQL Server Agent, and database logs for operational monitoring.
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Establishing performance baselines for analytical workloads covering query duration, throughput, concurrency, resource consumption, data loading, and reporting activity.
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Designing monitoring dashboards and alerting frameworks that identify abnormal performance, resource exhaustion, failed processes, and emerging operational risks.
Module 8: Query Performance Analysis and Optimization
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Understanding SQL Server query optimization, execution plans, operators, joins, scans, seeks, sorting, aggregation, parallelism, and cost-based query processing.
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Using execution plans and Query Store to identify expensive analytical queries, regressions, inefficient operations, and workload-specific optimization opportunities.
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Optimizing SQL queries through rewriting, filtering, join strategies, aggregation techniques, statistics management, and appropriate indexing.
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Establishing query performance management processes that measure optimization outcomes and prevent recurring analytical workload degradation.
Module 9: Indexing, Partitioning and Columnstore Optimization
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Designing clustered, nonclustered, filtered, covering, composite, and columnstore indexes according to analytical workload and data warehouse requirements.
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Managing clustered columnstore and nonclustered columnstore indexes to improve large-scale analytical query performance and storage efficiency.
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Implementing table and index partitioning based on date ranges, data lifecycle requirements, loading patterns, query access patterns, and maintenance needs.
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Evaluating index fragmentation, statistics, compression, partition distribution, index maintenance costs, and performance trade-offs across analytical workloads.
Module 10: Data Loading, ETL Support and Analytical Workload Management
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Administering SQL Server environments supporting ETL and ELT processes, staging databases, data transformation workloads, and scheduled analytical data loads.
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Monitoring data loading performance, bulk operations, transaction log growth, resource utilization, locking, concurrency, and dependencies between data engineering processes.
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Optimizing database configurations for recurring data loads while maintaining acceptable performance for reporting, dashboards, and concurrent analytical queries.
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Coordinating database administration with data engineering teams to improve load reliability, data availability, transformation performance, and analytical service continuity.
Module 11: Tempdb, Concurrency and Resource Management
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Understanding tempdb architecture, allocation, temporary objects, version stores, spills, sorting, hashing, and workload-related tempdb activity.
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Configuring tempdb files, sizing, placement, growth settings, and monitoring practices to support demanding analytical and reporting workloads.
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Investigating blocking, deadlocks, long-running queries, concurrency issues, resource contention, and transaction-related performance problems.
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Developing systematic troubleshooting procedures that combine SQL Server metrics, query evidence, operating-system information, application behavior, and historical performance data.
Module 12: High Availability, Replication and Analytics Service Continuity
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Understanding SQL Server high-availability and disaster-recovery technologies, including Always On availability groups, failover clustering, log shipping, and replication.
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Designing availability architectures for reporting databases, data warehouses, analytical applications, and business intelligence platforms.
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Monitoring synchronization, failover readiness, replica health, data movement, latency, and recovery performance across SQL Server environments.
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Developing continuity procedures covering planned failover, unplanned recovery, service restoration, validation, communication, and post-recovery assessment.
Module 13: SQL Server Analytics in Cloud and Hybrid Environments
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Administering SQL Server analytics workloads across Microsoft Azure, virtual machines, managed database services, hybrid infrastructure, and enterprise cloud environments.
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Managing cloud storage, compute, networking, automated backups, monitoring, security, scaling, and resource configuration for SQL Server workloads.
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Evaluating workload migration requirements, compatibility, performance baselines, licensing considerations, connectivity, security, and operational dependencies.
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Developing hybrid administration practices that provide consistent monitoring, governance, performance management, backup, security, and operational control.
Module 14: Automation, SQL Server Agent and DevOps Operations
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Using SQL Server Agent for scheduled jobs, maintenance plans, backups, data processing, monitoring tasks, alerts, notifications, and operational automation.
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Automating database provisioning, configuration, security administration, maintenance, monitoring, backup validation, and performance reporting.
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Integrating SQL Server administration with DevOps, source control, CI/CD pipelines, infrastructure as code, database deployment, and controlled change processes.
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Establishing automation governance covering testing, approvals, logging, error handling, rollback, security, monitoring, and operational accountability.
Module 15: Advanced Performance Management and Capacity Planning
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Developing advanced SQL Server performance management frameworks that correlate database metrics with analytical applications, ETL workloads, infrastructure, and business services.
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Applying workload profiling, wait-statistics analysis, Query Store history, performance baselines, trend analysis, and anomaly detection to identify emerging issues.
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Forecasting database growth, compute requirements, storage capacity, memory demand, query workload expansion, reporting concurrency, and analytical platform requirements.
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Building continuous performance improvement programs based on monitoring results, optimization outcomes, capacity trends, incidents, and changing analytics requirements.
Module 16: Integrated SQL Server Administration for Analytics Project
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Designing an end-to-end SQL Server analytics administration environment covering database configuration, security, storage, monitoring, backup, recovery, and performance management.
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Conducting a practical performance investigation involving analytical queries, indexing, columnstore structures, tempdb activity, blocking, resource contention, and data loading workloads.
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Developing a comprehensive monitoring dashboard, performance baseline, optimization plan, maintenance strategy, backup and recovery framework, and capacity management approach.
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Presenting an integrated SQL Server administration project demonstrating how effective database management can improve analytical workload performance, reliability, scalability, and service availability.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
