SQL Server 2017 Business Intelligence: Integration Services and Analysis Services
presented by Hands-On Technology Transfer
Summary
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.
Workshop Description/Agenda
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 Description
SQL
Server 2017 provides a rich environment for business
intelligence development. 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.
Course Prerequisites
Familiarity with database
concepts, Windows desktop navigation and software installation
techniques. Attendance at the SQL
Programming course
or Microsoft
Transact-SQL Programming course is highly
recommended although not required.
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
|
Who Should Attend
SQL Server administrators
Additional Information
Training Provider: Hands-On Technology Transfer
Course Topics: Computers / IT Training >
Database
Training Course Summary: 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.
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