MS-20767 Implementing a SQL Data Warehouse

Kluczowe zagadnienia szkolenia wg trenera CBSG Polska:

  • planowanie i projektowanie hurtowni danych
  • indeksy columnstore
  • tworzenie i wdrażanie pakietów SSIS
  • DQS i MDS czyli dbanie o jakość danych

Bartosz Ratajczyk, Microsoft Certified Trainer

Certyfikacje zawodowe

Tematyka szkolenia pokrywa zagadnienia wymagane na ścieżce:

  • MCSA: SQL Server 2016 Business Intelligence Development
MTA   MCS  MCSA  MCSE
MCSD

Dowiedz się więcej o certyfikacjach Microsoft

Poziom szkolenia wg standardów Microsoft

podstawowy średniozaawansowany zaawansowany ekspercki
100 200 300 400

Czas trwania

  • 40 godzin lekcyjnych (5 dni)

Tematyka zajęć

  • Module 1: Introduction to Data Warehousing
    Overview of Data Warehousing
    Considerations for a Data Warehouse Solution
    Lab : Exploring a Data Warehouse Solution

 

  • Module 2: Planning Data Warehouse Infrastructure
    Considerations for Building a Data Warehouse
    Data Warehouse Reference Architectures and Appliances
    Lab : Planning Data Warehouse Infrastructure

 

  • Module 3: Designing and Implementing a Data Warehouse
    Logical Design for a Data Warehouse
    Physical Design for a Data Warehouse
    Lab : Implementing a Data Warehouse Schema

 

  • Module 4: Columnstore Indexes
    Introduction to Columnstore Indexes
    Creating Columnstore Indexes
    Working with Columnstore Indexes
    Lab : Using Columnstore Indexes

 

  • Module 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
    Lab : Implementing an Azure SQL Data Warehouse

 

  • Module 6: Creating an ETL Solution
    Introduction to ETL with SSIS
    Exploring Source Data
    Implementing Data Flow
    Lab : Implementing Data Flow in an SSIS Package

 

  • Module 7: Implementing Control Flow in an SSIS Package
    Introduction to Control Flow
    Creating Dynamic Packages
    Using Containers
    Lab : Implementing Control Flow in an SSIS Package
    Lab : Using Transactions and Checkpoints

 

  • Module 8: Debugging and Troubleshooting SSIS Packages
    Debugging an SSIS Package
    Logging SSIS Package Events
    Handling Errors in an SSIS Package
    Lab : Debugging and Troubleshooting an SSIS Package

 

  • Module 9: Implementing an Incremental ETL Process
    Introduction to Incremental ETL
    Extracting Modified Data
    Temporal Tables
    Lab : Extracting Modified Data
    Lab : Loading Incremental Changes

 

  • Module 10: Enforcing Data Quality
    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

 

  • Module 11: Using Master Data Services
    Master Data Services Concepts
    Implementing a Master Data Services Model
    Managing Master Data
    Creating a Master Data Hub
    Lab : Implementing Master Data Services

 

  • Module 12: Extending SQL Server Integration Services (SSIS)
    Using Custom Components in SSIS
    Using Scripting in SSIS
    Lab : Using Scripts and Custom Components

 

  • Module 13: Deploying and Configuring SSIS Packages
    Overview of SSIS Deployment
    Deploying SSIS Projects
    Planning SSIS Package Execution
    Lab : Deploying and Configuring SSIS Packages

 

  • Module 14: Consuming Data in a Data Warehouse
    Introduction to Business Intelligence
    Introduction to Reporting
    An Introduction to Data Analysis
    Analyzing Data with Azure SQL Data Warehouse
    Lab : Using Business Intelligence Tools
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Wszystkie dostępne terminy kursu:

  • 13.11.2017 - 17.11.2017
  • 04.12.2017 - 08.12.2017
  • 22.01.2018 - 26.01.2018
  • 05.03.2018 - 09.03.2018
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