Implementing a SQL Data Warehouse (20767B)

Details

Description

This five-day instructor-led course provides students with the knowledge and skills to provision a Microsoft SQL Server 2016 database. The course covers SQL Server 2016 provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.

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:

Provision a Database Server.
Upgrade SQL Server
Configure SQL Server.
Manage Databases and Files (shared).

Prerequisites

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

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

What's Included

What’s included?

  • Authorized Courseware
  • Intensive Hands on Skills Development with an Experienced Subject Matter Expert
  • Hands-on practice on real Servers and extended lab support 1.800.482.3172
  • Examination Vouchers & Onsite Certification Testing- (excluding Adobe and PMP Boot Camps)
  • Academy Code of Honor: Test Pass Guarantee
  • Optional: Package for Hotel Accommodations, Lunch and Transportation

Training Solutions

With several convenient training delivery methods offered, The Academy makes getting the training you need easy. Whether you prefer to learn in a classroom or an online live learning virtual environment, training videos hosted online, and private group classes hosted at your site. We offer expert instruction to individuals, government agencies, non-profits, and corporations. Our live classes, on-sites, and online training videos all feature certified instructors who teach a detailed curriculum and share their expertise and insights with trainees. No matter how you prefer to receive the training, you can count on The Academy for an engaging and effective learning experience.

Methods

  • Instructor Led (the best training format we offer)
  • Live Online Classroom – Online Instructor Led
  • Self-Paced Video

Speak to an Admissions Representative for complete details

Schedule

StartFinishPublic PricePublic Enroll Private PricePrivate Enroll
12/25/202312/29/2023
1/15/20241/19/2024
2/5/20242/9/2024
2/26/20243/1/2024
3/18/20243/22/2024
4/8/20244/12/2024
4/29/20245/3/2024
5/20/20245/24/2024
6/10/20246/14/2024
7/1/20247/5/2024
7/22/20247/26/2024
8/12/20248/16/2024
9/2/20249/6/2024
9/23/20249/27/2024
10/14/202410/18/2024
11/4/202411/8/2024
11/25/202411/29/2024
12/16/202412/20/2024
1/6/20251/10/2025

Curriculum

Curriculum

Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.

Lessons

Overview of Data Warehousing
Considerations for a Data Warehouse Solution

Lab: Exploring a Data Warehouse Solution

Exploring data sources
Exploring an ETL process
Exploring a data warehouse

After completing this module, you will be able to:

Describe the key elements of a data warehousing solution
Describe the key considerations for a data warehousing solution

Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.

Lessons

Considerations for data warehouse infrastructure
Planning data warehouse hardware

Lab: Planning Data Warehouse Infrastructure

Planning data warehouse infrastructure

After completing this module, you will be able to:

Describe the main hardware considerations for building a data warehouse
Explain how to use reference architectures and data warehouse appliances to create a data warehouse

Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.

Lessons

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

Lab: Implementing a Data Warehouse Schema

Implementing a star schema
Implementing a snowflake schema
Implementing a time dimension table

After completing this module, you will be able:

Implement a logical design for data warehouse
Implement a physical design for a data warehouse

Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.

Lessons

Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes

Lab: Using Columnstore Indexes

Create a Columnstore Index on the FactProductInventory table.
Create a Columnstore index on the FactInternetSales table
Create a memory-optimized Columnstore table

After completing this module, you will be able to:

Create Columnstore indexes
Work with Columnstore indexes

Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.

Lessons

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
Copying data with the Azure data factory

Lab: Implementing an Azure SQL Data Warehouse

Create an Azure SQL data warehouse database
Migrate to an Azure SQL Data warehouse database
Copy data with the Azure data factory

After completing this module, you will be able to:

Describe the advantages of Azure SQL Data Warehouse
Implement an Azure SQL Data Warehouse
Describe the considerations for developing an Azure SQL Data Warehouse
Plan for migrating to Azure SQL Data Warehouse

Module 6: Creating an ETL Solution
At the end of this module, you will be able to implement data flow in an SSIS package.

Lessons

Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow

Lab: Implementing Data Flow in an SSIS Package

Exploring source data
Transferring data by using data row task
Using transformation components in a data row

After completing this module, you will be able to:

Describe ETL with SSIS
Explore Source Data
Implement a Data Flow

Module 7: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.

Lessons

Introduction to Control Flow
Creating Dynamic Packages
Using Containers
Managing consistency.

Lab: Implementing Control Flow in an SSIS Package

Using tasks and precedence in a control flow
Using variables and parameters
Using containers

Lab: Using Transactions and Checkpoints

Using transactions
Using checkpoints

After completing this module, you will be able to:

Describe control flow
Create dynamic packages
Use containers

Module 8: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.

Lessons

Debugging an SSIS Package
Logging SSIS Package Events
Handling Errors in an SSIS Package

Lab: Debugging and Troubleshooting an SSIS Package

Debugging an SSIS package
Logging SSIS package execution
Implementing an event handler
Handling error in a data flow

After completing this module, you will be able:

Debug an SSIS package
Log SSIS package events
Handle errors in an SSIS package

Module 9: Implementing a Data Extraction Solution
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.

Lessons

Introduction to Incremental ETL
Extracting Modified Data
Temporal Tables
Loading modified data

Lab: Extracting Modified Data

Using DateTime column to incrementally extract data
Using change data capture
Using the CDC control task
Using change tracking

Lab: Loading a data warehouse

Loading data from CDC output tables
Using a lookup transformation to insert or update dimension data
Implementing a slowly changing dimension
Using the merge statement

After completing this module, you will be able to:

Describe incremental ETL
Extract modified data
Load modified data
Describe temporal tables

Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.

Lessons

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

Lab: Cleansing Data

Creating a DQS knowledge base
Using a DQS Project to cleanse data
Using DQS in an SSIS package

Lab: de-duplicating Data

Creating a matching policy
Using a DS project to match data

After completing this module, you will be able:

Describe data quality services
Cleanse data using data quality services
Match data using data quality services
De-duplicate data using data quality services

Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at the source.

Lessons

Introduction to Master Data Services
Implementing a Master Data Services Model
Hierarchies and collections
Creating a Master Data Hub

Lab: Implementing Master Data Services

Creating a master data services model
Using the master data services add-in for Excel
Enforcing business rules
Loading data into a model
Consuming master data services data

After completing this module, you will be able to:

Describe the key concepts of master data services
Implement a master data service model
Create a master data hub
Manage master data

Module 12: Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.

Lessons

Using Custom Components in SSIS
Using Scripting in SSIS

Lab: Using Scripts

Using a script task

After completing this module, you will be able:

Use custom components in SSIS
Use scripting in SSIS

Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.

Lessons

Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution

Lab: Deploying and Configuring SSIS Packages

Creating an SSIS catalog
Deploying an SSIS project
Creating environments for an SSIS solution
Running an SSIS package in SQL server management studio
Scheduling SSIS package with SQL server agent

After completing this module, you will be able to:

Describe an SSIS deployment
Deploy an SSIS package
Plan SSIS package execution

Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.

Lessons

Introduction to Business Intelligence
Introduction to Reporting
An Introduction to Data Analysis
Analyzing Data with Azure SQL Data Warehouse

Lab: Using a data warehouse

Exploring a reporting services report
Exploring a PowerPivot workbook
Exploring a power report

After completing this module, you will be able to:

Describe at a high level of business intelligence
Show an understanding of reporting
Show an understanding of data analysis
Analyze data with Azure SQL data warehouse