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SQL Server 2016 Business Intelligence: Integration Services and Analysis Services

Duration: 5 Days

Price: $2795 *California residents and government employees call for pricing.

Discounts: We offer multiple discount options. Click here for more info.

Delivery Options: Attend face-to-face in the classroom, remote-live or on-demand training.

Registration: Click here to register for face-to-face or remote-live sessions, or click here to register for on-demand training.

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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 2016 provides a rich environment for business intelligence development. The focus of this five day 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 HOTT's 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

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Course Benefits

Course materials include student guide, hands-on lab manual and USB flash drive for examples and lab work
Students receive a certificate of completion at the end of class
Students can retake any portion of a live class that has been completed, within 12 months at no extra cost
There are no registration fees or cancellation fees

Reviews

Very informative and useful. Exactly the training I was looking for. Instructor was very easy to understand and very personable; easy to ask questions and approach. Training manual was very useful.
— M.M., RTP Company

Course Schedule

Choose a city below to view a schedule. If you have any questions, please call us at 978-250-4299 between 9:00 am - 5:00 pm EST.

Integration and Analysis Services Training Course

Attend face-to-face, remote-live, on-demand or on site at your facility.

SQL Server 2016 Business Intelligence: Integration Services and Analysis Services

Students Will Learn

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Integration and Analysis Services Training Course

Attend face-to-face, remote-live, on-demand or on site at your facility.

SQL Server 2016 Business Intelligence: Integration Services and Analysis Services

Students Will Learn

Address

Contact

Useful Links

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