Objetivos

Este curso descreve como implementar uma plataforma de armazenamento de dados para oferecer suporte a uma solução de BI. Os alunos aprenderão como criar um armazém de dados com Microsoft SQL Server 2014, implementar ETL com SQL Server Integration Services e validar e limpar dados com serviços de qualidade de dados SQL Server e o SQL Server Master Data Services. Este curso ajuda as pessoas a se prepararem para o exame 70-463.


Nota: Este curso destina-se aos que estão interessados em aprender SQL Server 2012 ou 2014. Abrange os novos recursos do SQL Server 2014, mas também os recursos importantes em toda a plataforma de dados SQL Server.


Público-alvo

Este curso destina-se a profissionais de banco de dados que precisam para criar e apoiar um solução de armazenamento de dados. Entre as principais responsabilidades incluem-se:

  • Implementação de armazém de dados.
  • Desenvolvimento de pacotes do SSIS para extração de dados, transformação e carregamento.
  • Impor integridade de dados usando o Master Data Services.
  • Limpeza de dados usando Data Quality Services.


Formação

É parte da Formação MCSE: Data Management and Analytics.


Carga-horária

40 horas | Código M20463


Conteúdo Programático

Module 1: Introduction to Data Warehousing

  • This module provides an introduction to the key components of a data warehousing solution and the high-level considerations you must take into account when you embark on a data warehousing project.


Module 2: Planning Data Warehouse Infrastructure

  • This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.


Module 3: Designing and Implementing a Data Warehouse

  • This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.


Module 4: Creating an ETL Solution with SSIS

  • This module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server Integration Services (SSIS) as a platform for building ETL solutions.


Module 5: Implementing Control Flow in an SSIS Package

  • This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.


Module 6: Debugging and Troubleshooting SSIS Packages

  • This module describes how you can debug packages to find the cause of errors that occur during execution. It then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.


Module 7: Implementing a Data Extraction Solution

  • This module describes the techniques you can use to implement an incremental data warehouse refresh process.


Module 8: Loading Data into a Data Warehouse

  • This module describes the techniques you can use to implement data warehouse load process.


Module 9: Enforcing Data Quality

  • This module introduces Microsoft SQL Server Data Quality Services (DQS), and describes how you can use it to cleanse and deduplicate data.


Module 10: Master Data Services

  • Master Data Services provides a way for organizations to standardize data and improve the quality, consistency, and reliability of the data that guides key business decisions. This module introduces Master Data Services and explains the benefits of using it.


Module 11: Extending SQL Server Integration Services

  • This module describes the techniques you can use to extend SSIS. The module is not designed to be a comprehensive guide to developing custom SSIS solutions, but to provide an awareness of the fundamental steps required to use custom components and scripts in an ETL process that is based on SSIS.


Module 12: Deploying and Configuring SSIS Packages

  • In this module, students will learn how to deploy packages and their dependencies to a server, and how to manage and monitor the execution of deployed packages.


Module 13: Consuming Data in a Data Warehouse

  • This module introduces business intelligence (BI) solutions and describes how you can use a data warehouse as the basis for enterprise and self-service BI.