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Implementing a SQL Data Warehouse (M20767)

Implementing a SQL Data Warehouse (M20767)

Learn to implement a data warehouse platform with Microsoft SQL Server 2016.

GK# 4398

$895 - $3095 USD

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Course Details

Course Overview

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In this course, you will learn how to implement a data warehouse platform to support a business intelligence (BI) solution. You will discover how to create a data warehouse, how to implement extract, transform, and load (ETL) with SQL Server Integration Services (SSIS), and how to validate and cleanse data with Data Quality Services (DQS) and Master Data Services.

This course incorporates material from the Official Microsoft Learning Product 20767: and it can assist you in your preparation for Exam 70-767: Implementing a SQL Data Warehouse.

GK Digital Learning is also available with digital Microsoft Official Courseware (dMOC). Click here to purchase.

Schedule

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What You'll Learn

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  • Overview of data warehousing
  • Considerations for building a data warehouse
  • Design and implementation for a data warehouse
  • Columnstore indexes
  • Azure SQL Data Warehouse
  • ETL with SSIS
  • Implement control flow in an SSIS package
  • Debug and troubleshoot SSIS packages
  • Incremental ETL and modified data extraction
  • Microsoft DQS
  • Master Data Services concepts and implementation
  • Extend SSIS
  • Deploy and configure SSIS packages
  • BI tools with Azure SQL Data Warehouse

Outline

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Classroom Live Outline

1. Introduction to Data Warehousing

  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution

2. Planning Data Warehouse Infrastructure

  • Considerations for Building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances

3. Designing and Implementing a Data Warehouse

  • Designing dimension tables
  • Designing fact tables
  • Physical Design for a Data Warehouse

4. Columnstore Indexes

  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes

5. Implementing an Azure SQL Data Warehouse

  • Advantages of Azure SQL Data Warehouse
  • Implementing an Azure SQL Data Warehouse
  • Developing an Azure SQL Data Warehouse
  • Migrating to an Azure SQ Data Warehouse

6. Creating an ETL Solution

  • ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow

7. Implementing Control Flow in an SSIS Package

  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers

8. Debugging and Troubleshooting SSIS Packages

  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Implementing an Event Handler
  • Handling Errors in Data Flow

9. Implementing a Data Extraction Solution

  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading Modified Data
  • Temporal Tables

10. Enforcing Data Quality

  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data

11. Using Master Data Services

  • Master Data Services Concepts
  • Implementing a Master Data Services Model
  • Hierarchies and Collections
  • Creating a Master Data Hub

12. Extending SQL Server Integration Services (SSIS)

  • Using Custom Components in SSIS
  • Using Scripting in SSIS

13. Deploying and Configuring SSIS Packages

  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution

14. Consuming Data in a Data Warehouse

  • Business Intelligence
  • Reporting
  • Data Analysis
  • Analyzing Data with Azure SQL Data Warehouse

Labs

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Classroom Live Labs

Lab 1: Exploring a Data Warehouse Solution
Lab 2: Planning Data Warehouse Infrastructure
Lab 3: Implementing a Data Warehouse Schema
Lab 4: Using Columnstore Indexes
Lab 5: Implementing an Azure SQL Data Warehouse
Lab 6: Implementing Data Flow in an SSIS Package
Lab 7: Implementing Control Flow in an SSIS Package
Lab 8: Using Transactions and Checkpoints
Lab 9: Debugging and Troubleshooting an SSIS Package
Lab 10: Extracting Modified Data
Lab 11: Loading Incremental Changes
Lab 12: Cleansing Data
Lab 13: De-duplicating Data
Lab 14: Implementing Master Data Services
Lab 15: Using Scripts
Lab 16: Deploying and Configuring SSIS Packages
Lab 17: Using a Data Warehouse

Prerequisites

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  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.
  • Some experience with database design

Related Certifications

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Earning an MCSA: SQL 2016 Business Intelligence Development certification validates your extract, transform, and load (ETL) and data warehouse skills, along with those for implementing BI solutions using multidimensional and tabular data models and online analytical processing (OLAP) cubes. This certification will qualify you for a position as a BI developer.

Who Should Attend

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  • Database professionals who need to fulfill a BI developer role focused on hands-on work by creating BI solutions, including data warehouse implementation, ETL and data cleansing
  • Database professionals responsible for implementing a data warehouse, developing SSIS packages for data ETL, enforcing data integrity using Microsoft Data Services and cleansing data using Data Quality Services

Vendor Credits

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SATV Redemption

Redeeming your Microsoft Software Assurance Training Vouchers:

  • 5 Day SATV for a Classroom Live session
  • 5 Day SATV for a Virtual Classroom Live session
  • 2 Day SATV for an individual GK Digital Learning course
Training Exclusives

This course comes with 12 months access to the following benefits:

  • Practice Labs
  • 24x7 Mentoring
  • Indexed Class Recordings
  • Unlimited Retakes
  • Digital Courseware
Find out more
Course Delivery

This course is available in the following formats:

Classroom Live

Receive face-to-face instruction at one of our training center locations.

Duration: 5 day

Virtual Classroom Live

Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.

Duration: 5 day

GK Digital Learning

Experience high-quality online learning combined with reliable expert guidance and skills development activities.



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