novembre, 2020

16nov(nov 16)00:0020(nov 20)00:00MOC 20767 - Implementing a SQL Data Warehouse

Dettaglio evento

16,17,18,19,20 Novembre 2020

35 ore – 9.00-13.00 / 14.00-17.00

 Presentazione del corso

Lo scopo di questo corso Microsoft MOC 20767 – Implementing a SQL Data Warehouse è che gli studenti apprendano come implementare una piattaforma di data warehouse per supportare una soluzione di Business Intelligence. Nel corso gli allievi imparano a creare un data warehouse con SQL Server 2016 e con Azure SQL Data Warehouse, a implementare ETL con SQL Server Integration Services e a validare e purificare i dati con SQL Server Data Quality Services e SQL Server Master Data Services.

Obiettivi

Al termine del corso gli allievi saranno in grado di:

  • 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

Prerequisiti

Per partecipare con profitto a questo corso è necessario che gli allievi:

  • almeno 2 anni di esperienza di lavoro con i database relazionali;
  • capacità di disegnare un database normalizzato;
  • capacità di creare tabelle e relazioni;
  • capacità di scrivere query con il linguaggio Transact-SQL;
  • capacità di scrivere semplici procedure di programmazione (ad esempio un ciclo);
  • è inoltre preferibile conoscere alcuni concetti di business, quali il fatturato, la profittabilità, la gestione finanziaria.

Destinatari

Business Intelligence Developer.

Contenuti

Introduction to Data Warehousing

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

Planning Data Warehouse Infrastructure

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

Designing and Implementing a Data Warehouse

  • Logical Design for a Data Warehouse
  • Physical Design for a Data Warehouse

Columnstore Indexes

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

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

Creating an ETL Solution

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

Implementing Control Flow in an SSIS Package

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

Debugging and Troubleshooting SSIS Packages

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

Implementing an Incremental ETL Process

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

Enforcing Data Quality

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

Using Master Data Services

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

Extending SQL Server Integration Services (SSIS)

  • Using Custom Components in SSIS
  • Using Scripting in SSIS

Deploying and Configuring SSIS Packages

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

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

Durata

35 ore

Prezzo

1.600,00 € +iva  a partecipante corso in aula

1.360,00€ + iva a partecipante corso in aula virtuale

Docente

Trainer esperto

Ora

16 (Lunedì) 00:00 - 20 (Venerdì) 00:00

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