Microsoft 70-762: Developing SQL Databases – Complete Professional Training Course

This course provides a comprehensive foundation for understanding and applying the key skills involved in designing, implementing, optimizing and maintaining relational database solutions using Microsoft SQL Server technology. Participants will develop the knowledge necessary to build database objects, ensure data integrity, manage concurrency, and optimize infrastructure. Through this course, you will gain the practical experience and conceptual awareness required to perform database development tasks in a professional environment.
You’ll learn how to align database design with business requirements, create and manage indexes, views, stored procedures, triggers, user-defined functions, and tackle performance challenges. You will also explore how to ensure high availability, efficient resource usage, and robust concurrency control. The course aims to bridge the gap between theoretical understanding and real-world application, enabling you to build scalable, maintainable, high-performing databases.

What You Will Learn from This Course

• How to design and implement relational database schemas aligned with business scenarios including table structures, normalization, and schema organization.
  
  

• Techniques for selecting appropriate data types, developing and modifying tables, and implementing constraints to enforce business rules.
  
  

• How to design and apply indexes, including clustered, non-clustered, included columns and columnstore indexes, to improve query performance and storage efficiency.
  
  

• The creation and management of views (including updateable and partitioned views), and indexed views to expose data appropriately and optimize access paths.
  
  

• How to build programmability objects: stored procedures, triggers, user-defined functions (scalar and table-valued) and table-valued parameters, integrating error handling, output parameters and transaction control.
  
  

• Managing database concurrency: isolation levels, locking strategies, transaction design, and use of memory-optimized tables to address performance and concurrency challenges.
  
  

• How to optimize database objects and overall SQL infrastructure: analyzing query plans, troubleshooting performance bottlenecks, monitoring workload, and tuning for optimal resource utilization and responsiveness.
  
  

• Techniques for ensuring high availability and data availability: file and storage configuration, tempdb optimization, baseline performance monitoring, dynamic management objects, scaling out strategies.
  
  

• Best practices for ongoing maintenance, monitoring and trace analysis to ensure that database systems continue to perform well under real workloads.
  
  

Learning Objectives

By the end of the course, you will be able to:

1. Translate business requirements into effective database designs, including the creation of tables, schemas, constraints and views.
   
   

2. Select and implement appropriate indexing strategies to optimize performance and maintainability.
   
   

3. Develop and deploy programmability objects (procedures, functions, triggers) that implement business logic and enforce data integrity.
   
   

4. Design transactions and concurrency strategies to prevent contention, deadlocks and ensure scalable database operations under multiple users and heavy loads.
   
   

5. Analyze and interpret execution plans, wait statistics and performance metrics to diagnose and resolve bottlenecks in SQL Server workloads.
   
   

6. Configure and optimize the infrastructure of SQL Server instances and databases (files, tempdb, memory, I/O, storage) for both performance and high availability.
   
   

7. Monitor and maintain the health of a database system through trace analysis, performance baselines, extended events and dynamic management views.
   
   

8. Apply real-world strategies for scaling out database solutions, ensuring availability and reliability across business scenarios.
   
   

Requirements

To fully benefit from this course, you should:

• Have experience working with relational databases (SQL Server or similar), including creation of tables, views, indexes, and basic SQL querying.
  
  

• Be familiar with Transact-SQL (T-SQL) for querying, manipulation, and writing basic stored procedures/functions.
  
  

• Have a working knowledge of database concepts such as normalization, data types, primary/foreign keys, and referential integrity.
  
  

• Be comfortable with basic administrative tasks like database file creation, backups/restores, or at least understand their purpose in a database environment.
  
  

• Ideally, you have exposure to working in a production or test environment where performance, concurrency and scalability issues arise.
  
  

• A willingness to experiment and practice with SQL Server (or compatible editions) using labs or real-world examples to deepen understanding.

Target Audience

This course is intended for:

• Database developers and engineers who are responsible for building and maintaining relational database solutions in enterprise or business environments.
  
  

• SQL Server professionals who wish to deepen their understanding of index design, programmability, concurrency control and performance optimization.
  
  

• IT professionals who support database development teams and need to understand how design decisions impact performance, scalability and availability.
  
  

• Developers transitioning into database-centric roles—those who already write SQL queries and stored procedures, and now need to adopt best practices for design, performance and maintenance.
  
  

• Anyone preparing to validate their skills or refresh their knowledge in SQL Server database development and infrastructure optimization.

Prerequisites

Before taking this course you should have:

• Familiarity with Transact-SQL (T-SQL) including SELECT, INSERT, UPDATE, DELETE, JOINs, aggregates, subqueries and basic stored procedures/functions.
  
  

• Experience working with a relational database system (e.g., Microsoft SQL Server, MySQL, PostgreSQL) including creating tables, defining keys, and basic schema design.
  
  

• Understanding of fundamental data modelling concepts such as normalization, relationships, indexing, and schema design.
  
  

• Basic awareness of database administration topics such as backup and restore, file and storage considerations, and basic performance monitoring.
  
  

• Access to a SQL Server (or similar) environment to carry out hands-on practice (installation, lab exercises) is highly recommended.

Course Modules / Sections

This course is organised into distinct modules, each designed to build on the previous one, reinforcing core concepts while introducing more advanced practices and real-world scenarios. While you might cover them in sequence, many of the modules can also be practiced in parallel through lab sessions and applied exercises. Below is the breakdown of the modules and what each module will entail:

Module 1: Database Design and Schema Implementation

In this foundational module, you will explore how database schemas are conceived, defined and implemented in a relational database system. You will begin by examining business requirements and translating them into logical and physical database designs. You will learn how to choose appropriate data types for columns, define tables and their relationships, and apply constraints such as primary keys, foreign keys, check constraints and default values. You will practice normalising data to reduce redundancy, ensure data integrity, and support efficient querying. You will also learn how to partition schema across multiple schemas or databases if needed, and use schema-design patterns that match common business scenarios. You will implement tables using the relational engine of the database, review storage implications of different choices (for example fixed vs variable length data, nullable vs non-nullable, sparse columns), and learn how indexing decisions at the design stage affect future performance and maintainability. By the end of this module you will be able to draft a schema from scratch, implement it in code (DDL), test the integrity of the design with sample data, and propose enhancements or refactorings where necessary.

Module 2: Indexing Strategies and Query Performance Foundations

Building on the schema design, this module delves deeply into creating and maintaining indexes to support efficient data access. You will review the types of indexes typically available in modern relational systems: clustered indexes, non-clustered indexes, unique indexes, columnstore indexes, filtered indexes, included column indexes, and partitioned indexes. You will learn how to evaluate query patterns (e.g., typical searches, aggregations, range scans, joins) and map them to appropriate indexing strategies. You will also cover how index maintenance (such as rebuilds and reorganisations) affects performance and storage, and how to monitor index usage through dynamic management views or equivalent instrumentation. In this module you will also be introduced to execution plans, how to read them, and how index choices impact those plans. You will perform hands-on labs where you compare performance before and after creating or altering indexes, capture statistics, analyze fragmentation, and measure improvements. You’ll also explore the trade-offs between index maintenance overhead and runtime performance gains. By the end of Module 2 you will understand how to design indexing strategies proactively for typical workloads, how to monitor their effectiveness over time, and how to adjust strategies as the workload evolves.

Module 3: Views and Programmability Objects

Once tables and indexes are in place, this module focuses on how to present data and implement business logic within the database. You will examine views — both simple and indexed or materialised — understanding when they are appropriate, how they can simplify querying for consumers, and how they influence performance. You’ll also learn how to create user-defined functions (scalar and table-valued), stored procedures, triggers, and table-valued parameters. You will examine how to embed business logic within stored procedures (including parameter handling, transactions, error handling, and output parameters). You will explore triggers for enforcing data-integrity rules and auditing, and you will learn best practices for designing functions and procedures that are maintainable and efficient (for example avoiding nested loops, favouring set-based operations, limiting side-effecting operations, and ensuring clear transaction boundaries). Labs will include writing stored procedures to implement common operations (e.g., insert/update/delete sets of rows with error handling and rollback logic), creating functions for reusable business logic, and designing views for reporting or simplifying complex queries. At the end of this module, you will be proficient in creating a full suite of programmability objects aligned with business requirements, and you will know how to evaluate when logic should remain in the database vs when it should reside in an application layer.

Module 4: Concurrency, Transactions and Data Integrity

This module addresses one of the most challenging aspects of database development: how to safely and efficiently handle multiple users and operations occurring simultaneously. You will learn the fundamentals of transactions, why atomicity, consistency, isolation and durability (ACID) matter in database systems, and how to implement transactions that guard against data corruption while still supporting high throughput. You will explore isolation levels (read uncommitted, read committed, repeatable read, serializable, snapshot) and understand how locking, blocking and deadlocking can occur. You will examine how to monitor blocking, how to detect and resolve deadlocks, and how to design transactions to minimise contention (for example by reducing scope of locks, using shorter transactions, favouring row rather than table locks when possible, and using appropriate isolation based on business need). You will also look at optimistic concurrency models, row versioning, and memory-optimised tables/structures (if supported by your database engine). Additionally, you will delve into data-integrity mechanisms beyond constraints: you’ll review trigger-based integrity checks, staged changes via change tables, and patterns for auditing and rollback of large batches. Through labs you will simulate concurrent loads (for example several threads issuing updates/inserts on shared tables) observe the effects of different isolation levels and locking strategies, measure wait statistics and tail latency, and apply best practices to reduce contention and improve scalability. By the end of this module you will have a toolkit for designing high-concurrency operations that avoid common pitfalls, preserve integrity under load, and provide predictable performance.

Module 5: Storage, Files, Tempdb and Configuration for Performance

In this module you shift focus from logical design and programmability toward the physical layer and infrastructure of your database environment. You will explore how storage, file configuration, allocation, I/O patterns, and tempdb configuration (for SQL Server) or equivalent (for other engines) impact overall performance and scalability. Topics will include how to place data files and log files across storage subsystems (for example RAID arrays, SSD vs HDD, SAN vs local storage), how to optimise file growth settings, how to configure database options for performance (such as MAXDOP, network packet size, buffer pool size, filegroups, partitioned tables), and how to manage the system database (tempdb) if applicable. You will study real-world workload patterns, understand how to benchmark I/O latency, throughput, and queue depth, and how sub-optimal file placement or contention on tempdb can dramatically degrade performance. Labs in this module will include configuring sample instances with different file placements, running workload simulations that stress I/O and measuring latency, analysing wait statistics tied to I/O (for example PAGEIOLATCH, WRITELOG waits), and experimenting with different tempdb configurations (multiple data files, pre-allocation, dedicated drives). By the module’s end you will understand how to configure, tune and monitor the physical infrastructure of your database system to match workload needs and avoid bottlenecks.

Module 6: Monitoring, Troubleshooting and Query Optimization

Having built and configured your database system, this module equips you with the tools and techniques needed for ongoing monitoring, troubleshooting and performance tuning — a critical capability for maintaining systems in production. You will learn how to capture and interpret execution plans (both estimated and actual), identify common performance anti-patterns (for example missing indexes, scan vs seek, parameter sniffing, plan reuse issues, heavy sorts, hash vs nested loops). You will review how to use dynamic management views / catalog views to capture runtime statistics, how to interpret wait statistics and model system health (for example high CPU, high waits, blocked sessions). You will also learn how to use profiling or tracing tools, extended events, DMVs and performance counters to build baselines, track trending metrics, and detect deviations. Labs will have you inject pathological queries (for example badly designed joins, missing filters) and then apply corrective strategies (adding indexes, rewriting queries, tweaking hint options, updating statistics, restructuring queries). You will simulate production-style workloads, capture traces during peaks and interpret them, identify which queries are the performance hogs, identify index usage and missing index recommendations, and implement corrective actions. By the end of Module 6 you will be able to monitor live systems, diagnose bottlenecks, optimise queries and indexes, and propose changes that deliver measurable performance improvements.

Module 7: High Availability, Disaster Recovery and Scalability

In this module you will broaden your view from individual database operations to system-wide reliability, availability and business continuity. You will learn about high availability (HA) features such as database mirroring, log shipping, replication, Always On availability groups (or equivalent features in your database engine), how they work internally, their pros and cons, availability vs consistency trade-offs, and how to design solutions based on business uptime requirements. You will also learn about disaster recovery (DR) planning: backup types, retention, recovery models, point-in-time recovery, test restores, and how to design recovery procedures and runbooks. You'll examine scalability patterns: horizontal scaling (sharding, distribute tables/partitions), vertical scaling, read replicas, scaling out read workloads, partitioning large tables, and tiering data. Labs will ask you to configure simulated HA/DR architectures, test failover scenarios, simulate site loss or data corruption and execute recovery. You will also model how scaling out read-heavy or write-heavy workloads can be architected over time. By the module’s completion you will be able to propose a database infrastructure design that meets specified RTO (Recovery Time Objective), RPO (Recovery Point Objective), performance and growth requirements.

Module 8: Maintenance, Lifecycle Management and Continuous Improvement

The final module wraps up with the practices that keep your database environment healthy and evolving. You will cover database maintenance operations: index and statistics maintenance, database integrity checks (e.g., DBCC or equivalent), consistency checks, backup/restore verification, and automated maintenance plans. You will learn how to design a lifecycle of a database environment: development → testing → deployment → production → monitoring → decommissioning. You will explore how to implement changes safely (change management, version control, deployment pipelines, rollback strategies). You will look at how to gather metrics over time, analyse trends and plan for growth (storage, compute, I/O). You will also learn about applying new database engine features, migrating to newer versions, consolidating legacy systems, and optimising for cost and performance across the lifecycle. Labs will involve building maintenance scripts, automating routine tasks, simulating large-scale upgrades, tracking performance over months and identifying where refactoring may yield benefit. By the end of this module you will be ready not only to build and support a high-performing database system, but to maintain, evolve and improve it over time.

Key Topics Covered

The modules above cover a wide spectrum of topics critical to effective database development, operation and maintenance. Below is a consolidated view of the key topics you will engage with:

• Translating business requirements into relational database design, including entity-relationship modelling, normalization (1NF, 2NF, 3NF, and beyond where appropriate), schema design, table structures, data types, constraints, keys and referential integrity.
  
  

• Implementation of tables and schemas in the SQL engine, including DDL (Data Definition Language) scripts, schema naming conventions, table partitioning, schema design for maintainability and extensibility.
  
  

• Indexing strategy development: clustering vs non-clustering, included columns, filtered indexes, columnstore indexes, index maintenance (rebuild vs reorganise), monitoring index health (fragmentation, usage statistics) and choosing index options aligned to workload.
  
  

• Execution plan analysis: understanding cost estimates vs actual, operators (scan, seek, join types, hash, nested loops), plan caching, parameter sniffing, plan reuse, index and join columns selection, and rewrites to improve plan shape.
  
  

• Views and programmability: creation of simple and indexed views, user-defined functions (scalar and table-valued), stored procedures, triggers, table-valued parameters, error/exception handling, transaction boundaries, set-based programming patterns, avoiding procedural loops where possible.
  
  

• Transaction and concurrency control: ACID properties, isolation levels, locking vs optimistic concurrency, row versioning, blocking and deadlock detection/resolution, designing for high concurrency, memory-optimized tables (where applicable), and best practices for transactional design in heavy-load scenarios.
  
  

• Physical infrastructure and storage: filegroups, data files, log files, I/O subsystem design, SSD vs HDD, SAN considerations, latency and throughput, tempdb configuration (multiple files, pre-allocation), database file configuration settings, and workload‐driven infrastructure tuning.
  
  

• Monitoring and troubleshooting: wait statistics, dynamic management views (DMVs), execution plan analysis, extended events or trace profiling, performance counters, indexing and query bottlenecks, capturing baselines, trending and alerting, diagnosing CPU, memory, I/O, network and locking issues.
  
  

• High availability and disaster recovery: backup types (full, differential, log), restore models, point-in-time recovery, failover architectures, replication, availability groups/read-replicas, sharding/distribution, scaling strategies, designing for RTO and RPO, test failover scenarios, and site-loss simulation.
  
  

• Maintenance and life-cycle management: integrity checks, automated maintenance plans, version control of schema and objects, deployment pipelines, change management, upgrade planning, archiving, decommissioning, metrics tracking over time, performance refactoring, continuous improvement processes.
  
  

• Real-world application: each topic is contextualised through business scenarios — for example, a retail system with heavy transactional load, a reporting/analytics system requiring columnstore indexes, a global enterprise requiring multi-site availability and scalability — driving the choice of design and tuning strategies.

Teaching Methodology

The teaching methodology for this course adopts a blended and practical approach designed to ensure that you not only understand the concepts but also apply them in scenarios representative of real-world environments. The course will combine instructor-led theoretical sessions with hands-on labs, case studies, interactive discussions, peer learning and self-paced exercises.

In the instructor-led sessions, you will be guided through the theoretical underpinnings of each topic. These sessions will include slide presentations, whiteboard discussions, live demonstrations of code and database tools, and interactive Q&A segments. The goal is to build a strong conceptual foundation, explain how each part of the system works, and explore trade-offs and best practices. For example, you might see a demonstration of how changing an isolation level affects blocking under simulated load, or how placing multiple tempdb files on separate physical drives can improve throughput in a SQL Server instance.

Case studies and scenarios form another critical pillar of the methodology. You will work through sample business cases (for example, an e-commerce site, a financial ledger, or a global reporting platform) which require you to apply what you have learned. These will help you understand how design decisions that look good in isolation may have unintended consequences in a production environment. They will also prompt you to think about holistic solutions: linking schema design with indexing strategy, linking concurrency control with physical infrastructure, linking monitoring with scalability planning. By discussing case studies in small groups or class discussion, you will benefit from peer insights and alternative perspectives.

Interactive discussions and peer-learning will also be encouraged. Participants will share challenges they have observed in their own work, propose design options, critique each other’s approaches, and collectively refine best practices. This helps to bridge the gap between course content and real-world experience, and draws on the diversity of participants’ backgrounds. Where appropriate, mini-projects or group work may be assigned (for example designing a high-availability architecture for a given scenario, or conducting a post-mortem on performance issues) which fosters collaboration and deeper learning.

Finally, self-paced exercises and reflection will be encouraged. After each module you will receive recommended readings, reference materials, additional practice questions, and lab extensions. You will be prompted to reflect on how the principles apply in your environment: What would you do differently? What trade-offs would matter in your organisation? What monitoring or metrics would you capture? This reflection helps reinforce learning and ensures you integrate theory into your mindset, not just short-term memorisation.

Assessment & Evaluation

The assessment and evaluation structure of the course is designed to measure not only your theoretical understanding but also your practical proficiency and ability to apply concepts in realistic scenarios. The evaluation consists of multiple components that together provide a comprehensive view of your performance and readiness.

First, there will be module-end quizzes or short tests. After each module (for example after Module 2 or Module 4) you will complete a timed quiz that tests your understanding of key concepts, definitions, best practices and fundamental design/troubleshooting patterns. These quizzes include multiple-choice questions, short answer questions, scenario-based questions, and sample script analysis (for instance: you may be given a snippet of SQL code and asked to identify a performance issue or suggest an improved approach). The purpose of the quizzes is to ensure you have grasped the material before moving on to more advanced topics.

Second, practical labs will be assessed. For each module you will perform lab exercises that require you to implement solutions, measure outcomes, capture results and provide commentary or reflection on your design decisions. You may be required to submit your lab scripts, measured performance results (for example before/after timings, index usage statistics), and a short write-up explaining what you did and why. The instructor (or support team) will review your submissions and provide feedback. These labs assess your ability to apply the theory to concrete tasks, evaluate trade-offs, and reflect on outcomes.

Third, there will be one or more live or simulated scenario assessments. For example, midway through the course you might be given a scenario: “Your company has a 500 GB transactional database running on a medium-sized server, suffering from high I/O latency and blocking issues during peak hours. Design a strategy to improve performance, outline physical storage changes, indexing improvements, and transaction design modifications.” You will present your solution, perhaps in a written report or short presentation, and answer follow-up questions. At the end of the course there will be a capstone project or simulation: you will take a more comprehensive scenario that involves many dimensions (schema design, indexing, concurrency, storage, availability) and implement an end-to-end solution, including tests and reflections. These scenario assessments evaluate your holistic thinking, integration of multiple modules, and ability to make sound design decisions under constraints.

Benefits of the Course

Enrolling in this course provides multiple tangible and long-term benefits that go far beyond simply preparing for a certification. Participants gain deep insight into database development practices that apply directly to the challenges faced by today’s organisations. The benefits extend to your professional capabilities, employability, project success, and the efficiency of the systems you build or manage.

1. Strong Conceptual Foundation in Database Development

This course gives you a thorough understanding of relational database architecture, design principles, and the operational characteristics of SQL Server and comparable database systems. You will not only learn how to write queries or build tables, but also why certain design decisions lead to performance, scalability, or maintenance advantages. That conceptual understanding forms a foundation on which you can adapt to new technologies or evolving platforms, since the principles of good database design are universal.

2. Enhanced Technical Proficiency and Real-World Problem-Solving

Through a balance of theoretical sessions and intensive lab exercises, you will acquire hands-on skills that translate directly to workplace competence. You will learn to design databases that support real-world applications, implement indexing strategies that cut query times drastically, and troubleshoot complex performance issues. By performing these tasks in controlled labs, you build confidence that you can reproduce them in production environments.

3. Career Advancement and Industry Recognition

Completing this course signals to employers that you possess the technical expertise needed to develop and maintain robust database systems. The curriculum aligns with industry-standard competencies historically measured by the Microsoft 70-762 certification, making it directly relevant to roles such as Database Developer, Data Engineer, and SQL Developer. Mastering the covered material enhances your readiness for advanced database certifications and positions you as a valuable asset in projects involving data architecture, business intelligence, and systems optimisation.

4. Improved Ability to Design for Performance and Scalability

Many professionals can build a database that works for small datasets, but far fewer can design one that performs well as it grows. This course trains you to think about scalability and performance from the start: how to structure data, select indexes, partition workloads, tune queries, and monitor resource usage. You will learn to anticipate bottlenecks and apply proactive measures before they become critical. This foresight enables you to build systems capable of supporting large-scale transactional or analytical workloads with stability and predictability.

5. Exposure to Real-World Scenarios and Case Studies

Rather than remaining purely academic, this course immerses you in realistic business cases. You will work through scenarios such as e-commerce systems handling thousands of concurrent users, financial applications requiring strict transactional integrity, or analytical platforms processing terabytes of historical data. By repeatedly applying principles to these examples, you will learn how to adapt theory to practice and how to reason about trade-offs that depend on context, resources, and constraints.

6. Strengthened Analytical and Troubleshooting Skills

Database performance problems are often complex, involving multiple layers — queries, indexes, memory, I/O, concurrency, and configuration. This course trains you to diagnose issues systematically using execution plans, dynamic management views, wait statistics, and other diagnostic tools. You will gain the ability to interpret signals from monitoring tools and logs, identify root causes rather than symptoms, and recommend appropriate corrective actions. These analytical skills are applicable not only to databases but to many problem-solving contexts in IT.

7. Integration with Broader Data Ecosystem Skills

While the focus is on SQL Server, the principles learned here integrate naturally with broader data engineering, analytics, and software development skills. Understanding database design, optimisation, and concurrency equips you to collaborate more effectively with developers, analysts, and infrastructure teams. You will be able to design schemas that support application frameworks, optimise backend services, or provide well-structured data for reporting tools and data warehouses.

8. Preparation for Future Technologies

As organisations move toward cloud-based and distributed database systems, many of the same concepts—schema design, indexing, concurrency control, optimisation, and monitoring—remain relevant. This course ensures you have the core understanding needed to transition smoothly to Azure SQL Database, managed cloud platforms, or hybrid architectures. It builds adaptability by teaching the reasoning behind design choices rather than rote procedures.

9. Increased Confidence and Professional Independence

Upon completing the course, you will be able to approach new database projects or performance challenges with confidence. Instead of relying solely on others for troubleshooting or design advice, you will have the knowledge to analyse, decide, and implement improvements independently. That independence boosts your productivity, credibility and value within any technical team.

Course Duration

The overall course duration has been designed to provide adequate depth, reflection, and practice while remaining manageable for working professionals. The structure can vary slightly depending on delivery mode (instructor-led classroom, virtual live, or self-paced), but the typical breakdown is as follows:

Standard Duration: 8–10 Weeks

The full course is commonly delivered over approximately two and a half months, assuming a moderate study load each week. This timeline allows participants to absorb theoretical concepts gradually, complete practical labs, and reflect on learning between sessions.

Weekly Schedule

Each week focuses on one major module or theme. The typical structure includes:

• Two instructor-led sessions per week of about two hours each, devoted to explanation, demonstration, and discussion of core concepts.
  
  

• One dedicated lab session of approximately two hours where participants implement what they have learned and receive feedback.
  
  

• Independent study or assignments, estimated at two to four hours per week, allowing participants to complete exercises, readings, or research tasks at their own pace.
  
  

This results in an overall engagement of roughly six to eight hours per week, which balances learning depth with the demands of professional life.

Accelerated Bootcamp Option

For learners who prefer an intensive experience, an accelerated delivery model can compress the course into a four-week bootcamp. In this mode, sessions occur daily, typically combining morning theory sessions with afternoon labs. The content coverage remains the same, but the pacing is faster and requires full-time commitment. This format is suitable for professionals preparing for certification renewal, organisational upskilling programs, or pre-project readiness.

Extended Self-Paced Model

For self-learners, a twelve-week schedule is recommended to accommodate flexibility. In this version, recorded sessions or reading materials replace live instruction, and assignments are completed asynchronously. Learners can progress at their own speed, revisit challenging topics, and explore advanced extensions beyond the core syllabus. Optional online discussion forums or mentorship sessions provide interaction opportunities.

Module Duration Estimates

Each module from Part 2 can be allocated roughly one week of dedicated study time, with the final weeks used for revision and the capstone project.

1. Database Design and Schema Implementation – 1 week
   
   

2. Indexing Strategies and Query Performance Foundations – 1 week
   
   

3. Views and Programmability Objects – 1 week
   
   

4. Concurrency, Transactions and Data Integrity – 1 week
   
   

5. Storage, Files, Tempdb and Configuration – 1 week
   
   

6. Monitoring, Troubleshooting and Query Optimisation – 1 week
   
   

7. High Availability, Disaster Recovery and Scalability – 1 week
   
   

8. Maintenance, Lifecycle Management and Continuous Improvement – 1 week
   
   

9. Capstone Project and Review – 1 week

Tools & Resources Required

To ensure a seamless learning experience and full participation in labs and exercises, participants will need access to specific tools, software, and reference materials. These resources mirror real-world environments so that what you practice during the course is directly applicable to professional scenarios.

1. Software and Database Engine

The primary environment for this course is Microsoft SQL Server. Any of the following versions are suitable for learning and practice:

• SQL Server 2019 Developer Edition (free for development and training)
  
  

• SQL Server 2022 Developer Edition (latest features and enhancements)
  
  

• Alternatively, Azure SQL Database or SQL Server Express for learners using cloud or lightweight setups.
  
  

Participants should have the SQL Server Management Studio (SSMS) installed for interaction with the database, running queries, designing objects, and visualising execution plans. SSMS provides the interface for most labs and demonstrations.

For those working in a cross-platform or mixed environment, Azure Data Studio is an acceptable alternative that runs on Windows, macOS, or Linux and supports SQL Server connections along with notebooks for lab documentation.

2. Hardware Requirements

To run SQL Server Developer Edition locally, a moderately powerful system is recommended:

• 64-bit operating system (Windows 10/11 Professional or Server Edition)
  
  

• At least 8 GB RAM (16 GB preferred for smoother performance under lab workloads)
  
  

• Multi-core CPU (quad-core or better recommended)
  
  

• Minimum 20 GB of free disk space for sample databases, backups, and logs
  
  

• Stable internet connection if remote labs or downloads are required
  
  

For cloud-based practice, learners may instead use an Azure free trial or equivalent hosted environment, which reduces local hardware dependency.

3. Sample Databases and Datasets

The course uses realistic datasets to simulate business environments. Commonly employed sample databases include:

• AdventureWorks – a comprehensive example database from Microsoft that demonstrates an enterprise manufacturing and sales environment.
  
  

• WideWorldImporters – a newer example database illustrating modern SQL Server features such as JSON data and in-memory tables.
  
  

• Custom Training Databases – provided with the course materials to support specific labs, including transactional, analytical, and mixed-workload scenarios.
  
  

These databases allow learners to practice schema creation, indexing, query optimisation, and troubleshooting with data volumes that mimic production conditions.

4. Development and Scripting Tools

While most work occurs within SSMS, additional tools enhance the experience:

• Visual Studio Code or another code editor for writing and managing T-SQL scripts.
  
  

• SQL CMD or PowerShell for command-line automation tasks.
  
  

• Git or another version-control system for tracking changes to database scripts and practising DevOps alignment.
  
  

• Optional use of Docker images to run isolated SQL Server instances for testing.
  
  

These tools are not mandatory but expose participants to modern workflows used in professional database development environments.

5. Monitoring and Diagnostic Utilities

Performance tuning requires observation. Learners will be introduced to native and third-party tools for monitoring:

• SQL Server Profiler or Extended Events for tracing queries and capturing runtime statistics.
  
  

• Dynamic Management Views (DMVs) for real-time performance insights.
  
  

• Activity Monitor in SSMS for quick overviews of active sessions and resource usage.
  
  

• Optional open-source or enterprise utilities such as Red Gate SQL Monitor or SolarWinds Database Performance Analyzer, depending on organisational access.
  
  

Using these tools during labs helps learners practice identifying slow queries, lock contention, or resource bottlenecks.

6. Reference Documentation and Learning Resources

To complement live sessions, several reference sources are recommended:

• Microsoft Docs: the official documentation for SQL Server, T-SQL syntax, and performance-tuning guidance.
  
  

• Books Online (BOL) for offline reference within SSMS.
  
  

• Technical books such as Inside SQL Server Query Tuning or SQL Server Internals for deeper reading.
  
  

• Community blogs, forums, and Q&A sites (e.g., SQLServerCentral, Stack Overflow) for real-world tips and case discussions.
  
  

• Instructor-provided notes, cheat sheets, and white papers summarising best practices and lab instructions.
  
  

These resources remain valuable long after the course ends, forming a personal reference library for future work.

7. Cloud and Virtual Resources

If the course is delivered online or in hybrid mode, a virtual lab environment will be provided. Learners may receive access to pre-configured virtual machines or cloud instances where SQL Server and sample data are already installed. This arrangement eliminates local setup time and ensures consistency across participants. Learners connecting remotely should ensure reliable broadband and a remote-desktop client.

For self-paced learners, step-by-step installation guides and scripts are provided to set up their environment independently. The process itself reinforces useful skills in database deployment and configuration.

8. Supplementary Tools for Collaboration and Reporting

Group discussions and project submissions may rely on communication platforms such as Microsoft Teams, Slack, or discussion boards within a learning-management system. Participants will use shared repositories for submitting labs, sharing findings, or presenting results. For reporting exercises, optional tools such as Power BI or Excel may be employed to visualise performance metrics or query results from SQL Server datasets.

9. Optional Advanced Resources

For learners wishing to extend beyond the standard curriculum, optional tools include:

• Query Store for performance history analysis.
  
  

• Database Tuning Advisor to explore automated index recommendations.
  
  

• PerfMon (Performance Monitor) for Windows-level metrics collection.
  
  

• Azure Portal for cloud deployment and scaling experiments.
  
  

• Container orchestration platforms like Kubernetes for exploring micro-database deployments.
  
  

While these advanced tools are not mandatory for course completion, they enrich the learning experience for participants aiming at senior-level or architectural roles.

10. Support Materials and Templates

Each participant receives digital materials including:

• Step-by-step lab guides
  
  

• Sample scripts and stored procedures
  
  

• Database design templates (ER models, DDL skeletons)
  
  

• Troubleshooting checklists
  
  

• Performance-analysis worksheets
  
  

• Maintenance and backup plan templates
  
  

These ready-to-use artefacts can serve as reference documents in real work projects after course completion.

Career Opportunities

Completing this course opens a wide range of professional possibilities across industries where data forms the backbone of decision-making and digital operations. In today’s landscape, virtually every organisation—from small startups to multinational corporations—relies on structured data systems for daily operations, analytics, and strategic planning. The ability to design, implement, optimise, and maintain those systems is in high demand. This course prepares you with the technical depth and applied knowledge to fit seamlessly into such roles, offering both immediate and long-term career advancement opportunities.

Database Developer

One of the most direct career paths after completing this course is becoming a Database Developer. These professionals are responsible for building and maintaining databases that store, organise, and make data accessible to users and applications. The course equips you with the technical skills to design schemas, develop stored procedures, optimise queries, and ensure data integrity. As a Database Developer, you will translate business requirements into robust data structures and ensure that data remains consistent, accurate, and performant. You will also collaborate closely with application developers, data analysts, and IT administrators to ensure that systems function as intended across the entire data lifecycle.

SQL Developer

A SQL Developer focuses specifically on crafting efficient, reliable, and scalable SQL code to handle the various data manipulation needs of an organisation. This course provides a deep grounding in Transact-SQL (T-SQL) and teaches you how to build, test, and optimise complex queries, triggers, functions, and stored procedures. As a SQL Developer, you will be responsible for writing queries that extract actionable insights, transforming data for reporting, or supporting application backends. The combination of performance tuning and programming covered in this course ensures that your SQL skills go beyond the basics—enabling you to handle large datasets, complex joins, and high-concurrency environments with confidence.

Data Engineer

With the growing emphasis on data-driven systems and analytics, organisations increasingly need professionals who can manage and prepare data for analytics pipelines and data platforms. The foundation of database design, indexing, concurrency, and optimisation you gain here translates directly into the core skills of a Data Engineer. You will understand how to structure data to enable efficient ETL (Extract, Transform, Load) processes, design transactional systems that feed analytical models, and ensure data quality and consistency. Many of the database design and tuning principles learned in this course are directly applicable to cloud-based or distributed data systems, positioning you for roles in modern data engineering teams working with platforms like Azure Synapse, Databricks, or Snowflake.

Database Administrator (DBA)

For those more interested in the management, maintenance, and performance side of databases, this course provides an excellent stepping stone toward becoming a Database Administrator. The modules on concurrency, performance tuning, high availability, and maintenance offer a solid introduction to the responsibilities of DBAs. You will learn how to manage backup and recovery strategies, monitor system health, optimise resource usage, and ensure uptime. Many organisations look for hybrid professionals who can both develop and administer databases, and this course helps bridge that gap. As you gain experience, this path can lead to senior DBA, Database Architect, or Infrastructure Specialist roles.

Business Intelligence (BI) Developer

The Business Intelligence field depends heavily on well-structured and performant databases. BI Developers build and manage the data models, transformations, and aggregations that power reporting systems and dashboards. The indexing, query optimisation, and schema design principles you learn here directly affect the performance of BI tools such as Power BI, Tableau, or SSRS. With the analytical thinking and tuning mindset developed through this course, you will be well-equipped to create efficient data models and ensure that analytical queries run quickly even across large datasets. This role often combines technical work with close interaction with business users, making it an excellent option for those who enjoy bridging technology and business.

Data Analyst and Reporting Specialist

For professionals focused more on interpreting data rather than maintaining systems, the knowledge from this course enhances your analytical capabilities. Understanding how data is structured, stored, and indexed allows analysts to write more effective queries and produce accurate reports. You will know how to identify why certain queries run slowly, how to optimise them, and how to collaborate with database teams to improve performance. This insight into the underlying mechanics of data systems gives analysts a competitive advantage, making them not just consumers of data but contributors to the overall efficiency of the analytics ecosystem.

Application Developer with Database Expertise

In many software development environments, backend developers must interact with databases constantly. Whether writing APIs, building microservices, or integrating data into applications, developers who understand database performance, transaction management, and indexing produce more efficient and scalable systems. Through this course, you gain a perspective that complements application development. You will be able to design data access layers that minimise bottlenecks, reduce locking conflicts, and ensure consistent results. This hybrid skill set—application programming plus database optimisation—is highly prized, particularly in enterprise or data-intensive environments.

Cloud Database Specialist

As organisations migrate to cloud platforms, new career roles have emerged focusing on managed database services, scalability, and cost optimisation. The foundational knowledge of SQL Server and relational systems gained in this course translates easily to cloud-based implementations such as Azure SQL Database, Amazon RDS, and Google Cloud SQL. Understanding how indexing, query design, and storage configuration influence performance remains essential, even when working in the cloud. By applying the principles from this course in a cloud context, you can position yourself for modern data roles such as Cloud Database Engineer or Cloud Data Solutions Architect.

Performance Tuning Specialist

Some professionals choose to specialise deeply in the area of database optimisation and performance troubleshooting. This course provides the building blocks for that specialization by covering query plans, index design, concurrency, resource management, and workload analysis. With experience, you can pursue consulting or in-house performance tuning roles, helping organisations solve their most challenging performance problems. Such specialists are often called upon to audit systems, recommend architectural improvements, and train teams on tuning practices. It is a niche but highly respected and well-compensated area of expertise.

Technical Consultant or Solutions Architect

For those who enjoy problem-solving across multiple systems, this course supports a pathway toward technical consulting or solution architecture. Consultants must evaluate client requirements, assess data infrastructure, and design holistic solutions that include database, application, and infrastructure components. The broad coverage of this course—from schema design to high availability—equips you with a comprehensive understanding necessary for such advisory roles. Over time, experience in implementing and optimising SQL databases allows you to transition into higher-level design and architecture positions where you influence system-wide decisions and guide teams toward best practices.

Academic and Training Roles

Individuals with a passion for teaching or mentoring may leverage the knowledge from this course to become instructors, trainers, or academic lecturers in database systems. Because the course covers both theoretical principles and practical labs, it provides a foundation for teaching others how to apply relational concepts in real-world systems. With additional experience, you could develop your own workshops, write technical guides, or contribute to educational programs in universities, coding bootcamps, or corporate training environments.

Freelance and Independent Consulting Opportunities

For experienced professionals who prefer independent work, database expertise opens doors to freelance or contract consulting. Many businesses lack in-house expertise in performance tuning, migration, or database design. By applying the competencies from this course, you can offer specialised services such as optimising existing systems, designing new databases, or troubleshooting issues in production environments. This independence allows flexibility and the potential for diverse projects across industries ranging from finance and healthcare to e-commerce and logistics.

Emerging Career Trends

Beyond traditional database roles, new positions continue to evolve as data becomes more central to business strategy. Skills from this course are increasingly relevant in roles such as Data Platform Engineer, Database Reliability Engineer (DBRE), and Automation Engineer focusing on DevOps integration for data systems. These roles combine development, operations, and automation skills—areas where the practical lab work of this course proves particularly valuable. As organisations adopt Infrastructure as Code and continuous deployment pipelines for databases, professionals who can apply consistent design, testing, and tuning principles gain a clear competitive advantage.

Enroll Today

This course represents more than a technical training program—it is an investment in your professional development, long-term career stability, and the ability to contribute meaningfully to data-driven innovation. Whether you are an early-career professional seeking to establish a strong technical foundation or an experienced practitioner aiming to refine and expand your capabilities, enrolling in this course positions you at the forefront of database technology and application.

When you enroll, you gain immediate access to a comprehensive learning journey that bridges theoretical knowledge with real-world application. The curriculum’s balance between conceptual lectures, hands-on labs, and scenario-based assessments ensures that you do not merely memorise syntax or procedures but understand how to apply them effectively. You will experience the satisfaction of building working database systems, measuring performance improvements, and applying optimisation techniques that deliver tangible results. The skills you develop can be applied immediately in your workplace or personal projects, allowing you to see measurable improvement in performance, reliability, and scalability.

No matter where you currently stand in your career, this course offers a clear pathway forward. If you are a developer seeking to deepen your understanding of data systems, this course helps you design efficient backends. If you are an administrator or analyst, it enhances your ability to interpret performance data and manage systems proactively. If you aspire to move into data engineering, cloud systems, or solution architecture, this course lays the groundwork for that transition. Each module builds toward practical mastery, so that by the end, you will have both the competence and confidence to take on complex database projects.

Enrolling today also ensures that you stay aligned with the ongoing evolution of database technology. SQL Server continues to evolve with new features, and the practices of indexing, concurrency control, and optimisation remain central to performance in both on-premises and cloud contexts. As organisations modernise their data infrastructure, professionals who understand these fundamentals remain essential. By committing to this learning path now, you future-proof your career against technological shifts and position yourself as a contributor to the next generation of data solutions.

The earlier you begin, the sooner you can apply what you learn to your current role or project. The course is designed to accommodate working professionals, with flexible scheduling options, online access, and self-paced alternatives. You will receive continuous feedback, guidance, and opportunities to refine your understanding through practical exercises. Every session moves you closer to mastery, and every lab reinforces your ability to apply knowledge effectively.