20767 – Implementing a SQL Data Warehouse

  A Distancia On demand

Objetivo: Este curso provee a los estudiantes los conocimientos y técnicas necesarias para la implementación de una plataforma de data warehouse, para dar soporte a una solución de BI. Requisitos: Haber completado los cursos Querying Data with Transact-SQL (20761) y Administering a SQL Database Infrastructure (20764) o acreditar conocimientos equivalentes. Duración: 40 horas Temario:

  • Introduction to Data Warehousing
  • Considerations for a Data Warehouse Solution
  • Considerations for Building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances
  • Logical Design for a Data Warehouse
  • Physical Design for a Data Warehouse
  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes
  • 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
  • Introduction to ETL with SSIS
  • Creating an ETL Solution with SSIS
  • Exploring Source Data
  • Implementing Data Flow
  • Implementing Control Flow in an SSIS Package
  • Creating Dynamic Packages
  • Using Containers
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Temporal Tables
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
  • Introduction to Master Data Services
  • Implementing a Master Data Services Model
  • Managing Master Data
  • Creating a Master Data Hub
  • Extending SQL Server Integration Services
  • Using Custom Components in SSIS
  • Using Scripts in SSIS
  • 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

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13 diciembre, 2016

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