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Microsoft Course 20767

This course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

Audience profile

The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.

At course completion

After completing this course, students will be able to:

Prerequisites

In addition to their professional experience, students who attend this training should already have the following technical knowledge:

Course Outline

Module 1: Introduction to Data Warehousing

Describe data warehouse concepts and architecture considerations.

After completing this module, students will be able to:

Module 2: Planning Data Warehouse Infrastructure

This module describes the main hardware considerations for building a data warehouse.

After completing this module, students will be able to:

Module 3: Designing and Implementing a Data Warehouse

This module describes how you go about designing and implementing a schema for a data warehouse.

After completing this module, students will be able to:

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.

After completing this module, students will be able to:

Module 5: Implementing an Azure SQL Data Warehouse

This module describes Azure SQL Data Warehouses and how to implement them.

After completing this module, students will be able to:

Module 6: Creating an ETL Solution

At the end of this module you will be able to implement data flow in a SSIS package.

After completing this module, students will be able to:

Module 7: Implementing Control Flow in an SSIS Package

This module describes implementing control flow in an SSIS package.

After completing this module, students will be able to:

Module 8: Debugging and Troubleshooting SSIS Packages

This module describes how to debug and troubleshoot SSIS packages.

After completing this module, students will be able to:

Module 9: Implementing an Incremental ETL Process

This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.

After completing this module, students will be able to:

Module 10: Enforcing Data Quality

This module describes how to implement data cleansing by using Microsoft Data Quality services.

After completing this module, students will be able to:

Module 11: Using Master Data Services

This module describes how to implement master data services to enforce data integrity at source.

After completing this module, students will be able to:

Module 12: Extending SQL Server Integration Services (SSIS)

This module describes how to extend SSIS with custom scripts and components.

After completing this module, students will be able to:

Module 13: Deploying and Configuring SSIS Packages

This module describes how to deploy and configure SSIS packages.

After completing this module, students will be able to:

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.

After completing this module, students will be able to:

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Microsoft Course 20768

This course is aimed at database professionals who fulfil a Business Intelligence (BI) developer role. This course looks at implementing multidimensional databases by using SQL Server Analysis Services (SSAS), and at creating tabular semantic data models for analysis with SSAS.

Audience profile

The primary audience for this course are database professionals who need to fulfil BI Developer role to create enterprise BI solutions. Primary responsibilities will include:

At course completion

After completing this course, students will be able to:

Prerequisites

This course requires that you meet the following prerequisites:

Course Outline

Module 1: Introduction to Business Intelligence and Data Modeling

This module introduces key BI concepts and the Microsoft BI product suite.

After completing this module, students will be able to:

Module 2: Creating Multidimensional Databases

This module describes the steps required to create a multidimensional database with analysis services.

After completing this module, students will be able to:

Module 3: Working with Cubes and Dimensions

This module describes how to implement dimensions in a cube.

After completing this module, students will be able to:

Module 4: Working with Measures and Measure Groups

This module describes how to implement measures and measure groups in a cube.

After completing this module, students will be able to:

Module 5: Introduction to MDX

This module describes the MDX syntax and how to use MDX.

After completing this module, students will be able to:

Module 6: Customizing Cube Functionality

This module describes how to customize a cube.

After completing this module, students will be able to:

Module 7: Implementing a Tabular Data Model by Using Analysis Services

This module describes how to implement a tabular data model in PowerPivot.

After completing this module, students will be able to:

Module 8: Introduction to Data Analysis Expression (DAX)

This module describes how to use DAX to create measures and calculated columns in a tabular data model.

After completing this module, students will be able to:

Module 9: Performing Predictive Analysis with Data Mining

This module describes how to use data mining for predictive analysis.

After completing this module, students will be able to:

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