FORMACIÓN OFICIAL MICROSOFT | CURSOS EN MADRID


DP-500 Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

Duración: 20 horas

Curso de Diseño e implementación de soluciones de análisis a escala empresarial con Microsoft Azure y Microsoft Power BI

La formación en Diseño e implementación de soluciones de análisis a escala empresarial con Microsoft Azure y Microsoft Power BI cubre métodos y prácticas para realizar análisis de datos avanzados a escala. Los estudiantes se basarán en la experiencia analítica existente y aprenderán a implementar y administrar un entorno de análisis de datos, consultar y transformar datos, implementar y administrar modelos de datos y explorar y visualizar datos.


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Requisitos Previos

Antes de asistir al curso DP-500, es recomendado haber realizado la formación DP-900 Microsoft Azure Data Fundamentals  y PL-300 Power BI Data Analyst 

Modalidad formativa

  • Presencial en Gadesoft: Madrid.
  • Presencial en cliente: En sus instalaciones. Toda la península.
  • Online Direct: Mediante herramientas de videoconferencia (Microsoft Teams), en directo con el instructor. Pantalla compartida, interacción, seguimiento total.

Objetivos

En el curso DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI aprenderás a:

  • Implementar y administrar un entorno de análisis de datos
  • Consulta y transformación de datos
  • Implementar y administrar modelos de datos
  • Explore y visualice datos

Contenidos

  • Manual oficial de Microsoft.
  • Laboratorios de prácticas.
  • Opcional: Voucher de certificación.

Fechas

Próximas fechas de convocatoria para el curso:

Certificación

El curso DP-500: Diseño e implementación de soluciones de análisis a escala empresarial con Microsoft Azure y Microsoft Power BI prepara para obtener la certificación DP-500 que lleva su mismo nombre.

TEMARIO

Module 1: Introduction to data analytics on Azure

  • Explore Azure data services for modern analytics
  • Understand concepts of data analytics
  • Explore data analytics at scale

Module 2: Govern data across an enterprise

  • Introduction to Microsoft Purview
  • Discover trusted data using Microsoft Purview
  • Catalog data artifacts by using Microsoft Purview
  • Manage Power BI artifacts by using Microsoft Purview

Module 3: Model, query, and explore data in Azure Synapse

  • Introduction to Azure Synapse Analytics.
  • Implement star schema design and query relational data in Azure.
  • Analyze data with a serverless SQL pool in Azure Synapse Analytics.
  • Optimize data warehouse query design.
  • Analyze data with a Spark Pool in Azure Synapse Analytics.

Lab 1: Query data in Azure.

Lab 2: Explore data in Spark notebooks.

Lab 3: Create a star schema model.

Module 4: Prepare data for tabular models in Power BI

  • Choose a Power BI model framework.
  • Understand scalability in Power BI.
  • Optimize Power Query for scalable solutions.
  • Create and manage scalable Power BI dataflows.

Lab 1: Create a dataflow.

Module 5: Design and build scalable tabular models

  • Create Power BI model relationships.
  • Enforce model security.
  • Implement DirectQuery.
  • Create calculation groups.

Lab 1: Create model relationships.

Lab 2: Enforce model security.

Lab 3: Design and build tabular models.

Lab 4: Create calculation groups.

Module 6: Optimize enterprise-scale tabular models

  • Optimize performance using Synapse and Power BI.
  • Improve query performance with hybrid tables, dual storage mode, and aggregations.
  • Use tools to optimize Power BI performance.

Lab 1: Use tools to optimize Power BI performance.

Lab 2: Improve query performance using aggregations.

Lab 3: Improve query performance with dual storage mode.

Lab 4: Improve performance with hybrid tables.

Module 7: Implement advanced data visualization techniques by using Power BI

  • Understand advanced data visualization concepts.
  • Customize core data models.
  • Monitor data in real-time with Power BI.
  • Create and distribute paginated reports in Power BI report builder.

Lab 1: Monitor data in real-time with Power BI.

Lab 2: Create and distribute paginated reports in Power BI Report Builder.

Module 8: Implement and manage an analytics environment

  • Recommend Power BI administration settings.
  • Recommend a monitoring and auditing solution for a data analytics environment.
  • Configure and manage Power BI capacity.
  • Establish a data access infrastructure in Power BI.

Module 9: Manage the analytics development lifecycle

  • Recommend a deployment strategy for Power BI assets.
  • Recommend a source control strategy for Power BI assets.
  • Perform impact analysis of downstream dependencies from dataflows and datasets.
  • Recommend automation solutions for the analytics development lifecycle, including Power BI REST API.
  • Deploy and manage datasets by using the XMLA endpoint.
  • Deploy reusable assets.

Lab 1: Create reusable Power BI assets.

Module 10: Integrate an analytics platform into an existing IT infrastructure

  • Recommend and configure a Power BI tenant or workspace.
  • Identify requirements for a solution, including features, performance, and licensing strategy.
  • Integrate an existing Power BI workspace into Azure Synapse Analytics.
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