Module 3: 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 the filegroups, how to use partitioning to manage large tables, and using compression to improve storage and performance. Temporal tables are a new feature in SQL Server 2016 and offer a straightforward solution to collecting changes to your data.
Lessons
Partitioning Data
Compressing Data
Temporal Tables
Lab : Using Advanced Table Designs
Partitioning Data
Compressing Data
Module 4: Ensuring Data Integrity through Constraints
The quality of data in your database largely determines the usefulness and effectiveness of applications that rely on it—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. Microsoft SQL Server data management software provides a range of features to simplify the job.
Lessons
Enforcing Data Integrity
Implementing Data Domain Integrity
Implementing Entity and Referential Integrity
Lab : Using Data Integrity Through Constraints
Add Constraints
Test the Constraints
Module 5: 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 Microsoft SQL Server.
Lessons
Core Indexing Concepts
Data Types and Indexes
Heaps, Clustered, and Nonclustered Indexes
Single Column and Composite Indexes
Lab : Implementing Indexes
Creating a Heap
Creating a Clustered Index
Creating a Covered Index
Module 6: 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 DMOs, the Database Tuning Advisor, and Query Store.
Lessons
Index Strategies
Managing Indexes
Execution Plans
The Database Engine Tuning Advisor
Query Store
Lab : Optimizing Indexes
Using Query Store
Heaps and Clustered Indexes
Creating a Covered Index
Module 7: Columnstore Indexes
Introduced in Microsoft SQL Server 2012, columnstore indexes are used in large data warehouse solutions by many organizations. This module highlights the benefits of using these indexes on large datasets; the improvements made to columnstore indexes in SQL Server 2016; and the considerations needed to use columnstore indexes effectively in your solutions.
Lessons
Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes
Lab : Using Columnstore Indexes
Creating a Columnstore Index
Create a Memory Optimized Columnstore Table
Module 8: Designing and Implementing Views
This module describes the design and implementation of views. A view is a special type of query—one that is stored and can be used in other queries—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.
Lessons
Introduction to Views
Creating and Managing Views
Performance Considerations for Views
Lab : Designing and Implementing Views
Creating Standard Views
Creating an Updateable view
Module 9: Designing and Implementing Stored Procedures
This module describes the design and implementation of stored procedures.
Lessons
Introduction to Stored Procedures
Working with Stored Procedures
Implementing Parameterized Stored Procedures
Controlling Execution Context
Lab : Designing and Implementing Stored Procedures
Create Stored procedures
Create Parameterized Stored procedures
Changes Stored Procedure Execution Context
Module 10: 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 to debug. 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.
Lessons
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
Format Phone numbers
Modify an Existing Function
Module 11: 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.
Lessons
Designing DML Triggers
Implementing DML Triggers
Advanced Trigger Concepts
Lab : Responding to Data Manipulation by Using Triggers
Create and Test the Audit Trigger
Improve the Audit Trigger
Module 12: Using In-Memory Tables
Microsoft SQL Server 2014 data management software introduced in-memory online transaction processing (OLTP) functionality features to improve the performance of OLTP workloads. SQL Server 2016 adds 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.
Lessons
Memory-Optimized Tables
Natively Compiled Stored Procedures
Lab : Using In-Memory Database Capabilities
Using Memory-Optimized Tables
Using Natively Compiled Stored procedures
Module 13: Implementing Managed Code in SQL Server
As a SQL Server professional, you are likely to be asked to create databases that meet business needs. Most requirements can be met using Transact-SQL. However, occasionally you may need additional capabilities that can only be met by using common language runtime (CLR) code. As functionality is added to SQL Server with each new release, the necessity to use managed code decreases. However, there are times when you might need to create aggregates, stored procedures, triggers, user-defined functions, or user-defined types. You can use any .NET Framework language to develop these objects. In this module, you will learn how to use CLR managed code to create user-defined database objects for SQL Server.
Lessons
Introduction to CLR Integration in SQL Server
Implementing and Publishing CLR Assemblies
Lab : Implementing Managed Code in SQL Server
Assessing Proposed CLR Code
Creating a Scalar-Valued CLR Function
Creating a Table Valued CLR Function
Module 14: Storing and Querying XML Data in SQL Server
XML provides rules for encoding documents in a machine-readable form. It has become a widely adopted standard for representing data structures, rather than sending unstructured documents. Servers that are running Microsoft SQL Server data management software often need to use XML to interchange data with other systems; many SQL Server tools provide an XML-based interface. SQL Server offers extensive handling of XML, both for storage and querying. This module introduces XML, shows how to store XML data within SQL Server, and shows how to query the XML data. The ability to query XML data directly avoids the need to extract data into a relational format before executing Structured Query Language (SQL) queries. To effectively process XML, you need to be able to query XML data in several ways: returning existing relational data as XML, and querying data that is already XML.
Lessons
Introduction to XML and XML Schemas
Storing XML Data and Schemas in SQL Server
Implementing the XML Data Type
Using the Transact-SQL FOR XML Statement
Getting Started with XQuery
Shredding XML
Lab : Storing and Querying XML Data in SQL Server
Determining when to use XML
Testing XML Data Storage in Variables
Using XML Schemas
Using FOR XML Queries
Creating a Stored Procedure to Return XML
Module 15: Storing and Querying Spatial Data in SQL Server
This module describes spatial data and how this data can be implemented within SQL Server.
Lessons
Introduction to Spatial Data
Working with SQL Server Spatial Data Types
Using Spatial Data in Applications
Lab : Working with SQL Server Spatial Data
Become Familiar with the Geometry Data Type
Add Spatial Data to an Existing Table
Find Nearby Locations
Module 16: Storing and Querying BLOBs and Text Documents in SQL Server
Traditionally, databases have been used to store information in the form of simple values—such as integers, dates, and strings—that contrast with more complex data formats, such as documents, spreadsheets, image files, and video files. As the systems that databases support have become more complex, administrators have found it necessary to integrate this more complex file data with the structured data in database tables. For example, in a product database, it can be helpful to associate a product record with the service manual or instructional videos for that product. SQL Server provides several ways to integrate these files—that are often known as Binary Large Objects (BLOBs)—and enable their content to be indexed and included in search results. In this module, you will learn how to design and optimize a database that includes BLOBs.
Lessons
Considerations for BLOB Data
Working with FILESTREAM
Using Full-Text Search
Lab : Storing and Querying BLOBs and Text Documents in SQL Server
Enabling and Using FILESTREAM Columns
Enabling and Using File Tables
Using a Full-Text Index
Module 17: SQL Server Concurrency
This module explains how to name, declare, assign values to, and use variables. It also describes how to store data in an array. 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 SQL Server implements concurrency controls, and the different ways you can configure and work with concurrency settings.
Lessons
Concurrency and Transactions
Locking Internals
Lab : SQL Server Concurrency
Implement Snapshot Isolation
Implement Partition Level Locking
Module 18: Performance and Monitoring
This module explains how to name, declare, assign values to, and use variables. It also describes how to store data in an array. 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.
Lessons
Extended Events
Working with extended Events
Live Query Statistics
Optimize Database File Configuration
Metrics
Lab : Monitoring, Tracing, and Baselining
Collecting and Analyzing Data Using Extended Events
Implementing Baseline Methodology
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