The SQL Server Administrator bootcamp includes coverage of relational database fundamentals, SQL programming and administering SQL Server 2016 databases.
This bootcamp provides a solid understanding of relational database design concepts, coding and utilizing SQL queries and database management tools. It includes comprehensive coverage of SQL syntax including complex queries, as well as creating and using stored procedures, functions, views and triggers. Administration topics include installing and configuring SQL Server, backing up and restoring databases, configuring security as well as monitoring and optimizing performance of a SQL Server.
Program Highlights:
- Designing normalized table structures for relational databases
- Creating databases and tables
- Writing SQL queries
- Using subqueries
- Using triggers and stored procedures
- Installing and configuring SQL Server 2016
- Using the SQL Server client tools to manage and configure SQL Server
- Configuring security in SQL Server
- Backing up and restoring databases
- Replicating data using SQL Server replication
- Monitoring events and data changes on a SQL Server
- Managing multiple SQL Server instances using central management
Required Courses:
- SQL Programming (21 hours)
- Microsoft SQL Server 2016 Administration (35 hours)
Optional Course: SQL Server 2016 Business Intelligence: Integration Services and Analysis Services (35 hours)
Course Track Options:
- 2-course track: $2,400
- 3-course track: $3,600
Note: This is an on-demand class and the student can start anytime after purchase. Date posted is just a tentative start dateSQL Programming
This SQL programming course teaches students relational database fundamentals and SQL programming skills. Topics covered include relational database architecture, database design techniques, and simple and complex query skills. This class is intended for analysts, developers, designers, administrators, and managers new to the SQL programming language. Upon completion, participants will understand SQL functions, join techniques, database objects and constraints, and will be able to write useful SELECT, INSERT, UPDATE and DELETE statements. Comprehensive hands on exercises are integrated throughout to reinforce learning and develop real competency.
Duration: 21 hours
Prerequisites: None.
Students Will Learn:
- Introduction to Relational Databases and SQL
- Designing Relational Databases
- Creating Databases and Tables
- Working with Records
- JOIN Statements
- Advanced SELECT Statements
- Understanding Subqueries
- SQL Procedural Programming
- Views and Triggers
- Database Security and Transactions
Course Overview:
Relational Database Fundamentals
- Overview of Relational Database Concepts
- Relational Databases and Relational Database Management Systems
- Data Normalization
- DDL Syntax
Writing Basic SQL Queries- Displaying Table Structures
- Retrieving Column Data From a Table or View
- Selecting Unique Values
- Filtering Rows Using the WHERE Clause
- Sorting Results Using ORDER BY
- Joining Multiple Tables
- Using Column and Table Aliases
Creating a Database- Database Development Methodology Overview
- Building a Logical Data Model
- Identifying Entities and Attributes
- Isolating Keys
- Relationships Between Entities
- Creating Entity-Relationship Diagrams - Transforming to Physical Design
- Migrating Entities to Tables
- Selecting Primary Keys
- Defining Columns
- Enforcing Relationships with Foreign Keys - Constructing the Database Using DDL
- Creating Tables, Indexes, Constraints and Views
- Dropping Tables, Indexes, Constraints and Views
- Modifying Tables, Indexes, Constraints and Views
Manipulating Query Results- Using Row Functions
- Character
- Numeric
- Date and Time
- Data Conversion (CAST and CONVERT) - Using the CASE Function
- Handling Null Values
Advanced Query Techniques- Inner Joins
- Outer Joins (Left, Right, Full)
- Performing Self-Joins
- Subqueries
- Simple
- Correlated - Using the EXISTS Operator
- Tips for Developing Complex SQL Queries
- Using Aggregate Functions
- AVG
- COUNT
- SUM
- MIN
- MAX - Performing Set Operations
- UNION
- INTERSECT
- EXCEPT/MINUS - Aggregating Results Using GROUP BY
- Restricting Groups with the HAVING Clause
- Creating Temporary Tables
Manipulating Table Data Using SQL's Data Manipulation Language (DML)- Inserting Data into Tables
- Updating Existing Data
- Deleting Records
- Truncating Tables
- Implementing Data Integrity with Transactions
- Beginning Explicit Transactions
- Committing Transactions
- Rolling Back Transactions
User-Defined Functions- Definition and Benefits of Use
- CREATE FUNCTION
- Syntax
- RETURN Clause and the RETURNS Statement
- Scalar vs. Table Functions - Comparison with Stored Procedures
- Returning Scalar Values and Tables
- ALTER and DROP FUNCTION
Stored Procedures- Definition and Benefits of Use
- CREATE PROCEDURE
- Syntax - - Variables and Parameters
- Control of Program Flow
- ALTER and DROP PROCEDURE
- Implementation Differences
Triggers- Definition and Benefits of Use
- Alternatives (e.g., Constraints)
- CREATE TRIGGER
- Syntax
- Trigger Types - "Inserted" (or "NEW") and "Deleted" (or "OLD") Tables
- Event Handling and Trigger Execution
- ALTER and DROP TRIGGER
Working with Table Expressions- Overview of Table Expressions
- Working with Views
- Using Derived Tables
- Common Table Expressions
- Table-Valued Functions
Microsoft SQL Server 2016 Administration
This course provides students who administer and maintain SQL Server 2016 databases with the knowledge and skills to administer a SQL Server database infrastructure.
The primary audience for this course is individuals who administer and maintain SQL Server databases. These individuals perform database administration and maintenance as their primary area of responsibility, or work in environments where databases play a key role in their primary job.
Duration: 35 hours
Prerequisites: Familiarity with database concepts
Students Will Learn:
- Installing and configuring SQL Server 2016
- Authenticating and authorizing users
- Assigning server and database roles
- Authorizing users to access resources
- Protecting data with encryption and auditing
- Recovery models and backup strategies
- Backing up SQL Server databases
- Restoring SQL Server databases
- Automating database management
- Configuring security for the SQL Server agent
- Managing alerts and notifications
- Tracing access to SQL Server
- Monitoring a SQL Server infrastructure
- Troubleshooting a SQL Server infrastructure
- Importing and exporting data
- Creating a high availability solution
Course Overview:Installation and Configuration
- Installing Multiple Instances of SQL Server 2016
- Applying a Service Pack
- Creating Aliases
- Setting up a Central Management Server
Authenticating and Authorizing Users- Authenticating Connections to SQL Server
- Authorizing Logins to Access Databases
- Authorization Across Servers
- Partially Contained Databases
Assigning Server and Database Roles- Working with Server Roles
- Working with Fixed Database Roles
- Creating User-Defined Database Roles
Authorizing Users to Access Resources- Authorizing User Access to Objects
- Authorizing Users to Execute Code
- Configuring Permissions at the Schema Level
Protecting Data with Encryption and Auditing- Options for Auditing Data Access in SQL Server
- Implementing SQL Server Audit
- Managing SQL Server Audit
- Protecting Data with Encryption
SQL Server Recovery Models- Backup Strategies
- Understanding SQL Server Transaction Logging
- Planning a SQL Server Backup Strategy
Backup of SQL Server Databases- Backing up Databases and Transaction Logs
- Managing Database Backups
- Working with Backup Options
Restoring SQL Server Databases- Understanding the Restore Process
- Restoring Databases
- Working with Point-in-time Recovery
- Restoring System Databases and Individual Files
Tracing Access to SQL Server- Capturing Activity Using SQL Server profiler
- Improving Performance with the Database Engine Tuning Advisor
- Working with Tracing Options
Monitoring SQL Server- Monitoring Activity
- Capturing and Managing Performance Data
- Analyzing Collected Performance Data
Troubleshooting SQL Server- Resolving Service Related Issues
- Resolving Login and Connectivity Issues
- Troubleshooting Common Issues
Importing and Exporting Data- Transferring Data to/from SQL Server
- Importing and Exporting Table Data
- Using BCP and BULK INSERT to Import Data
Maintaining High Availability of Data- Windows Clustering
- AlwaysOn Availability Groups
- Implementing AlwaysOn
- Implementing Log Shipping
Optional Course: SQL Server 2016 Business Intelligence: Integration Services and Analysis Services
The focus of this course is to familiarize developers with the use of SQL Server Engine, SQL Server Integration Services (SSIS) and SQL Server Analysis Services (SSAS) to create and populate data warehouses through ETL processing and build Multidimensional and Tabular models to use and reporting data sources.
Students will learn how to design and build data warehouses and marts using SQL Server Management Studio. In a series of exercises, students develop SSIS packages designed to maintain a data warehouse using the Data Flow control flow task. Also demonstrated are other control flow tasks that can interact with an NTFS file system, FTP server, execute Win32 processes, send emails, and run .NET scripts.
Based on the populated data warehouse they have created, students will then learn how to develop both Multidimensional and Tabular SSAS models using the languages Multidimensional Expressions (MDX) and Data Analysis Expressions (DAX). Cubes will be customized to include Key Performance Indicators (KPIs), Calculated Members, Named Sets, Navigational Hierarchies, and Perspectives.
Duration: 35 hours
Prerequisites: Familiarity with database concepts
Students Will Learn:
- Structure and function of a data warehouse or data mart
- Data warehouse design to support enterprise reporting
- The role of SSIS within the business intelligence framework
- Developing SSIS Extract Transform Load (ETL) processes to populate data warehouses
- Functionality of all SSIS Control Flow tasks
- Deploying SSIS projects to SSIS Catalogs
- Configuring SSIS environments, runtime variables and parameters
- BI Semantic Model
- Multidimensional Expressions (MDX) syntax
- Developing SSAS Multidimensional models
- Data Analysis Expressions (DAX)
- Developing SSAS Tabular models
- Deploying and securing Multidimensional and Tabular models
- Implementing SSAS Data Mining models for predictive analysis
- Consuming the BI Semantic Model in reports and dashboards
Course Overview:Business Intelligence Framework Overview
- SQL Server Data Tools Overview
- Installation and Configuration
- Components of a BI Solution
- Introduction to the BI Semantic Model
Integration Services Architecture- Architecture of the SSIS Data Engine
- Using Data Transformation Tasks
- Managing Connections to Sources and Destinations
- ADO.NET Data Source and Destination
- Understanding Data Buffers
- Control Flow Tasks and Containers
Common SSIS Tasks- Executing SQL Statements
- Connecting to FTP Servers
- Sending E-mail
- Notifying Administrators of Errors
- Completing Bulk Inserts
- Copying, Moving and Deleting Files and Folders
Data Transformations- Converting Data Types
- Merging Data from Multiple Sources
- Splitting Data to Multiple Destinations
- Counting Rows
- Sampling and Sorting Records
- Copying Columns
Advanced SSIS Tasks- Executing .NET Scripts and Win32 Processes
- Using the Windows Management Instrumentation (WMI) Tasks
- Performing Database Maintenance and Backups During SSIS Routines
- Using Variables and Input Parameters
- Profiling Database Tables
- Comparing XML Files Against Schemas
Advanced Data Transformations- Filling in Missing Data with Lookups
- Locating Near Duplicate Rows with Fuzzy Grouping
- Adding Audit Information to Results
- Counting the Occurrence of Keywords
- Sending Rows that Process Correctly and Incorrectly to Different Destinations
- Responding to Truncation Errors
SSIS Administration and Automation- Deploying SSIS Projects
- Manually Running SSIS Tasks
- Automating SSIS Package Execution
- Configuring Notifications for Execution Success, Failure or Both
- SSIS Security
- Troubleshooting Techniques
Data Warehouse Design- Understanding Fact and Dimension Tables
- Modeling Slowly Changing and Rapidly Changing Dimensions
- Modeling Fact Tables
- Using Star and Snowflake Schemas for Dimension Tables
- Implementing Surrogate Keys
- Defining Business Keys
Creating and Populating Data Warehouses- Creating Data Warehouses (OLAP Databases)
- Adding Fact Tables
- Adding Dimension Tables and Joining Them to Fact Tables
- Loading Data into Fact and Dimension Tables
- Validation Techniques for Data Loads
Creating and Managing Cubes- Creating Data Sources to Connect to Data Warehouses
- Using SSAS to Create Cubes
- Applying Friendly Names to Measures and Attributes
- Customizing Dimensions and Measures
- Setting up Navigational Hierarchies
- Optimizing Cubes with Attribute Relationships
Multidimensional (MDX) Essentials- Using MDX Queries to Pull Data from Cubes
- Understanding Tuples and Sets
- MDX Expressions vs. Queries
- Grouping Attribute Values into Named Sets
- Adding Custom Calculations for Cubes Using MDX
MDX Functions- Using MDX Aggregate Functions
- Using Navigations Functions to Move Though Hierarchies
- Grouping, Filtering and Sorting Functions
- Time-Based MDX Functions
Customizing Cubes- Adding Key Performance Indicators (KPIs)
- Customizing Dimensions and Attributes
- Adding Translations to Support Multiple Languages
- Adding Custom Calculations
- Subdividing Cubes Using Perspectives
Cube Deployment and Administration- Cube Storage Calculations
- Configuring Desired Aggregation
- Configuring Caching
- Deploying and Processing Cubes
- Connecting to Cubes from Excel and Other Clients
- Partitioning and Processing Cubes
- Backing Up and Restoring Options
- Securing Cubes
Creating and Customizing Tabular Models- Creating Tabular Modules in SSDT
- Introducing DAX
- Customizing Tabular Models
- Refreshing Data in Tabular Models
Understanding the Data Mining Process- Types of Business Analysis Supported by Data Mining
- Data Mining Process Explained
- Understanding the Key Components of Data Mining
- Using Built-In Data Mining Algorithms
- Matching Mining Algorithms to Business Needs
Working with Data Mining Structures- Adding Data Mining Structures
- Mining for Hidden Information
- Discovering Patterns in Data
- Creating Predictive Models
- Using the Data Mining Wizard
- Modifying Mining Structures with the Data Mining Designer
Using the Semantic Models in the Presentation Layer- Using SSAS Data Sources in Excel and Power View
- Using SSAS Data Sources in SSRS
- Using SSAS Data Sources in Power BI
- Using SSAS Data Sources in SharePoint Performance Point Services