Implementing a SQL Data Warehouse MOC 20767 (70-767)

  • Jan 15
    Monday 15/01/2018 - Wednesday 17/01/2018
    09:00 AM - 17:00 PM Horsens
    • Kr.18,695.00 ekskl. MOMS
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  • Jan 15
    Monday 15/01/2018 - Wednesday 17/01/2018
    09:00 AM - 17:00 PM Værløse
    • Kr.18,695.00 ekskl. MOMS
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  • Feb 26
    Monday 26/02/2018 - Wednesday 28/02/2018
    09:00 AM - 17:00 PM Værløse
    • Kr.18,695.00 ekskl. MOMS
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  • Feb 26
    Monday 26/02/2018 - Wednesday 28/02/2018
    09:00 AM - 17:00 PM Horsens
    • Kr.18,695.00 ekskl. MOMS
    Ekskl. moms
  • Apr 09
    Monday 09/04/2018 - Wednesday 11/04/2018
    09:00 AM - 17:00 PM Horsens
    • Kr.18,695.00 ekskl. MOMS
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  • Apr 09
    Monday 09/04/2018 - Wednesday 11/04/2018
    09:00 AM - 17:00 PM Værløse
    • Kr.18,695.00 ekskl. MOMS
    Ekskl. moms
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Kursusinfo

  • Dette kursus varer 3 dage
  • Der medfølger kursusmateriale til dette kursus
  • Dette kursus koster 4 klip på dit klippekort.
  • Fuld forplejning (Morgenmad, frokost, kage, kaffe og sodavand ad libitum)
  • Fuld beståelsesgaranti er inkluderet i prisen - Læs mere her
  • Eksamen er inkluderet i prisen
  • Med i prisen hører Practice Test
  • Du har i alt adgang til din kursus-pc i 3 uger

Varighed

Dette kursus varer 3 dage

Materialer

Der medfølger kursusmateriale til dette kursus

Klip på klippekort

Dette kursus koster 4 klip på dit klippekort.

Forplejning

Fuld forplejning (Morgenmad, frokost, eftermiddagskage samt kaffe og sodavand ad libitum)

Garanti for beståelse

Fuld beståelsesgaranti er inkluderet i prisen - Læs mere her

Eksamen

Alle eksamensforsøg er inkluderet i prisen

Practice Tests

Med i prisen hører Practice Test

Remote adgang

Du har i alt adgang til din kursus-pc i 3 uger

Download PDF

Hen PDF om kurset her

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"Implementing a SQL Data Warehouse" er et af de nye certificeringsrettede SQL Server 2016 kurser fra Microsoft. I alt kommer der 6 nye certificeringer, som leder op til 3 nye Microsoft MCSA SQL Server 2016 titler. For at opnå en MCSA SQL Server 2016 skal man bestå 2 eksamener.

 "Implementing a SQL Data Warehouse" indgår som første kursus i titlen: MCSA SQL Server 2016 Business Intelligence Development, som du kan læse mere om her

 

About this course

This 3-day instructor led 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:

Describe the key elements of a data warehousing solution
Describe the main hardware considerations for building a data warehouse
Implement a logical design for a data warehouse
Implement a physical design for a data warehouse
Create columnstore indexes
Implementing an Azure SQL Data Warehouse
Describe the key features of SSIS
Implement a data flow by using SSIS
Implement control flow by using tasks and precedence constraints
Create dynamic packages that include variables and parameters
Debug SSIS packages
Describe the considerations for implement an ETL solution
Implement Data Quality Services
Implement a Master Data Services model
Describe how you can use custom components to extend SSIS
Deploy SSIS projects
Describe BI and common BI scenarios

Course Outline

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
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 Building a Data Warehouse
Data Warehouse Reference Architectures and Appliances

Lab : 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
Logical Design for a Data Warehouse
Physical Design for a Data Warehouse

Lab : Implementing a Data Warehouse Schema
After completing this module, you will be able to:
Implement a logical design for a 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
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

Lab : Implementing an Azure SQL Data Warehouse
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 a SSIS package.

Lessons
Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow

Lab : Implementing Data Flow in an SSIS Package
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

Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and 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
After completing this module, you will be able to:
Debug an SSIS package
Log SSIS package events
Handle errors in an SSIS package

Module 9: Implementing an Incremental ETL Process
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

Lab : Extracting Modified Data
Lab : Loading Incremental Changes
After completing this module, you will be able to:
Describe incremental ETL
Extract 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
Lab : De-duplicating Data
After completing this module, you will be able to:
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 source.

Lessons
Master Data Services Concepts
Implementing a Master Data Services Model
Managing Master Data
Creating a Master Data Hub

Lab : Implementing Master Data Services
After completing this module, you will be able to:
Describe the key concepts of master data services
Implement a master data service model
Manage master data
Create a master data hub

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 and Custom Components
After completing this module, you will be able to:
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
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 Business Intelligence Tools
After completing this module, you will be able to:
Describe at a high level business intelligence
Show an understanding of reporting
Show an understanding of data analysis
Analyze data with Azure SQL data warehouse

Lignende kurser

Perform Big Data Engineering on Microsoft Cloud Services 20776 (70-776) 11 Dec
Developing SQL Databases MOC 20762 (70-762) 08 Jan 18
MCSE SQL 2016: Data Management & Analytics inkl. MCSA BI (70-767 & 70-768 & 70-473) 15 Jan 18
MCSE SQL 2016: Data Management & Analytics inkl. MCSA Database Admin (70-764 & 70-765 & 70-473) 18 Dec
Updating Your Skills to SQL Server 2016 (MOC 10986) 04 Dec