Introduction to Database Development
Before beginning to work with Microsoft Azure SQL Server in either a development or an administration role,
it is important to understand the scope of the SQL Server platform. In particular, it is useful to understand
that SQL Server is not just
a database engineâ€”it is a complete platform for managing enterprise data.
SQL Server provides a strong data platform for all sizes of organizations, in addition to a comprehensive set of
tools to make development easier,
and more robust.
- Introduction to the SQL Server Platform
- Azure SQL Database Development Tasks
Designing and Implementing Tables
In a relational database management system (RDBMS), user and system data is stored in tables. Each table
consists of a set of rows
that describe entities and a set of columns that hold the attributes of an entity. For example, a Customer table
might have columns such as
CustomerName and CreditLimit, and a row for each customer. In Azure SQL databases
tables are contained within schemas
that are very similar in concept to folders that contain files in the operating system. Designing tables is one
of the most important tasks
that a database developer undertakes, because incorrect table design leads to the inability to query the data
After an appropriate design has been created, it is important to know how to correctly implement the design.
- Designing Tables
- Data Types
- Working with Schemas
- Creating and Altering Tables
- Lab : Designing and Implementing Tables
Advanced Table Designs
The physical design of a database can have a significant impact on the ability of the database to meet the
storage and performance
requirements set out by the stakeholders. Designing a physical database implementation includes planning
partitioning to manage large tables, and using compression to improve storage and performance. Temporal tables
offer a straightforward solution to collecting changes to your data.
- Partitioning Data
- Compressing Data
- Temporal Tables
- Lab : Using Advanced Table Designs
Ensuring Data Integrity through Constraints
The quality of data in your database largely determines the usefulness and effectiveness of applications that
rely on itâ€”the success or failure of an organization or a business venture could depend on it. Ensuring data
integrity is a critical step in maintaining high-quality data.
You should enforce data integrity at all levels of an application from first entry or collection through
storage. SQL Server Management Studio provides a range of features to simplify the job.
- Enforcing Data Integrity
- Implementing Data Domain Integrity
- Implementing Entity and Referential Integrity
- Lab : Using Data Integrity Through Constraints
Introduction to Indexes
An index is a collection of pages associated with a table. Indexes are used to improve the performance of
queries or enforce uniqueness. Before learning to implement indexes, it is helpful to understand how they work,
how effective different data types are when used within indexes, and how indexes can be constructed from
multiple columns. This module discusses table structures that do not have indexes, and the different index types
available in Azure SQL databases.
- Core Indexing Concepts
- Data Types and Indexes
- Heaps, Clustered, and Nonclustered Indexes
- Single Column and Composite Indexes
- Lab : Implementing Indexes
Designing Optimized Index Strategies
Indexes play an important role in enabling SQL Server to retrieve data from a database quickly and efficiently.
This module discusses advanced index topics including covering indexes, the INCLUDE clause, query hints, padding
and fill factor, statistics, using DMVs, the Database Tuning Advisor, and Query Store.
- Index Strategies
- Managing Indexes
- Execution Plans
- The Database Engine Tuning Advisor
- Query Store
- Lab : Optimizing Indexes
Columnstore indexes are used in large data warehouse solutions by many
organizations. This module highlights the benefits of using these indexes on large datasets and the
considerations needed to use columnstore indexes
effectively in your solutions.
- Introduction to Columnstore Indexes
- Creating Columnstore Indexes
Designing and Implementing Views
This module describes the design and implementation of views. A view is a special type of queryâ€”one that is
stored and can be used in other queriesâ€”just like a table. With a view, only the query definition is stored
on disk; not the result set. The only exception to this is indexed views, when the result set is also stored
on disk, just like a table.
Views simplify the design of a database by providing a layer of abstraction, and hiding the complexity of
table joins. Views are also a way of securing your data by giving users permissions to use a view, without
giving them permissions to the underlying objects. This means data can be kept private, and can only be
viewed by appropriate users.
- Introduction to Views
- Creating and Managing Views
- Performance Considerations for Views
- Lab : Designing and Implementing Views
Designing and Implementing Stored Procedures
This module describes the design and implementation of stored procedures.
- Introduction to Stored Procedures
- Working with Stored Procedures
- Implementing Parameterized Stored Procedures
- Controlling Execution Context
- Lab : Designing and Implementing Stored Procedures
Designing and Implementing User-Defined Functions
Functions are routines that you use to encapsulate frequently performed logic. Rather than having to repeat
the function logic in many places, code can call the function. This makes code more maintainable, and easier
In this module, you will learn to design and implement user-defined functions (UDFs) that enforce business
rules or data consistency. You will also learn how to modify and maintain existing functions.
- Overview of Functions
- Designing and Implementing Scalar Functions
- Designing and Implementing Table-Valued Functions
- Considerations for Implementing Functions
- Alternatives to Functions
- Lab : Designing and Implementing User-Defined Functions
Responding to Data Manipulation via Triggers
Data Manipulation Language (DML) triggers are powerful tools that you can use to enforce domain, entity,
referential data integrity and business logic. The enforcement of integrity helps you to build reliable
applications. In this module, you will learn what DML triggers are, how they enforce data integrity, the
different types of trigger that are available to you, and how to define them in your database.
- Designing DML Triggers
- Implementing DML Triggers
- Advanced Trigger Concepts
- Lab : Responding to Data Manipulation by Using Triggers
Using In-Memory Tables
Higher tiers of Azure SQL databases support in-memory online transaction processing (OLTP)
functionality features to improve the performance of OLTP workloads. You will see several enhancements,
such as the ability to alter a memory-optimized table without recreating it. Memory-optimized tables are
primarily stored in memory, which provides the improved performance by reducing hard disk access.
Natively compiled stored procedures further improve performance over traditional interpreted Transact-SQL.
- Memory-Optimized Tables
- Natively Compiled Stored Procedures
- Lab : Using In-Memory Database Capabilities
SQL Server Concurrency
Concurrency control is a critical feature of multiuser database systems; it allows
data to remain consistent when many users are modifying data at the same time. This module covers the
implementation of concurrency in Microsoft SQL Server. You will learn about how Azure SQL databases implement
concurrency controls, and the different ways you can configure and work with concurrency settings.
- Concurrency and Transactions
- Locking Internals
- Lab : Concurrency in Azure SQL databases
Performance and Monitoring
This module looks at how to measure and monitor the performance of your SQL Server
databases. The first two lessons look at SQL Server Extended Events, a flexible, lightweight event-handling
system built into the Microsoft SQL Server Database Engine. These lessons focus on the architectural
concepts, troubleshooting strategies and usage scenarios.
- Extended Events
- Working with extended Events
- Live Query Statistics
- Optimize Database File Configuration
- Lab : Monitoring, Tracing, and Baselining