Computer Image

Length: 5 Days | Price: $2795

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 SQL Programming course or Microsoft Transact-SQL Programming course is highly recommended although not required.

SQL Server 2016 Business Intelligence: Integration Services and Analysis Services Course Overview
  • Business Intelligence Framework Overview
  • Integration Services Architecture
  • Common SSIS Tasks
  • Data Transformations
  • Advanced SSIS Tasks
  • Advanced Data Transformations
  • SSIS Administration and Automation
  • Data Warehouse Design
  • Creating and Populating Data Warehouses
  • Creating and Managing Cubes
  • Multidimensional (MDX) Essentials
  • MDX Functions
  • Customizing Cubes
  • Cube Deployment and Administration
  • Creating and Customizing Tabular Models
  • Understanding the Data Mining Process
  • Working with Data Mining Structures
  • Using the Semantic Models in the Presentation Layer