Implement analytics solutions using Microsoft Fabric (DP-600)
- Código del Curso M-DP600
- Duración 4 días
Otros Métodos de Impartición
Salta a:
Método de Impartición
Este curso está disponible en los siguientes formatos:
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Cerrado
Cerrado
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Clase de calendario
Aprendizaje tradicional en el aula
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Aprendizaje Virtual
Aprendizaje virtual
Solicitar este curso en un formato de entrega diferente.
Temario
Parte superiorPrepare, enrich, and serve data for analysis by consumers such as data analysts, report developers, and AI agents.
This 4-day course equips learners with the skills to design and implement end-to-end analytics solutions using Microsoft Fabric. Participants explore the platform’s capabilities, progressing through data ingestion and preparation, semantic modelling, and delivering insights while supporting the full analytics lifecycle. The updated course follows a more structured learning path, ensuring a seamless journey from platform fundamentals to advanced implementation and operational support.
Updated 19/05/2026
Calendario
Parte superior-
- Método de Impartición: Aprendizaje Virtual
- Fecha: 22-25 junio, 2026 | 10:30 AM to 6:00 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Inglés
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- Método de Impartición: Aprendizaje Virtual
- Fecha: 13-16 julio, 2026 | 8:30 AM to 2:30 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Español
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- Método de Impartición: Aprendizaje Virtual
- Fecha: 03-06 agosto, 2026 | 9:30 AM to 5:00 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Inglés
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- Método de Impartición: Aprendizaje Virtual
- Fecha: 19-22 octubre, 2026 | 8:30 AM to 2:30 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Español
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- Método de Impartición: Aprendizaje Virtual
- Fecha: 19-22 octubre, 2026 | 10:30 AM to 6:00 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Inglés
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- Método de Impartición: Aprendizaje Virtual
- Fecha: 30 noviembre-03 diciembre, 2026 | 9:30 AM to 5:00 PM
- Sede: Aula Virtual (W. Europe )
- Idioma: Inglés
Dirigido a
Parte superiorObjetivos del Curso
Parte superiorStudents will learn how to,
- Explore and navigate Microsoft Fabric to understand its analytics capabilities
- Ingest, transform, and prepare data using Fabric data tools
- Design and build semantic models to support business intelligence scenarios
- Create and deliver actionable insights using reporting and visualisation tools
- Implement end-to-end analytics solutions across the data lifecycle
- Manage and optimise analytics solutions, including performance and governance considerations
Contenido
Parte superiorModule 1: Explore analytics data stores in Microsoft Fabric
- Introduction to end-to-end analytics using Microsoft Fabric
- Discover and connect to data in OneLake
- Get started with lakehouses in Microsoft Fabric
- Get started with data warehouses in Microsoft Fabric
- Get started with Real-Time Intelligence in Microsoft Fabric
Module 2: Design and transform analytics data in Microsoft Fabric
- Choose data stores in Microsoft Fabric
- Design dimensional models for analytics in Microsoft Fabric
- Transform data using Dataflows Gen2 in Microsoft Fabric
- Transform data using notebooks in Microsoft Fabric
- Transform data using T-SQL in Microsoft Fabric
Module 3: Design and manage semantic models in Microsoft Fabric
- Create DAX calculations in semantic models
- Design semantic models for scale in Microsoft Fabric
- Optimize semantic model performance
- Enforce semantic model security
- Manage the semantic model development lifecycle
Module 4: Prepare AI-ready analytics data in Microsoft Fabric
- Prepare the semantic layer for AI in Microsoft Fabric
- Understand Microsoft Fabric IQ fundamentals
- Create an ontology with Fabric IQ
Module 5: Secure and govern analytics data in Microsoft Fabric
- Secure data access in Microsoft Fabric
- Secure a Microsoft Fabric data warehouse
- Govern data in Microsoft Fabric with Purview
- Govern analytics data in Microsoft Fabric
Pre-requisitos
Parte superior- Foundational knowledge of data concepts, including relational and non-relational data.
- Basic understanding of data analytics or business intelligence concepts.
- Familiarity with Azure or cloud-based data services .
- Experience with data transformation and querying (e.g., SQL or similar tools).
- Prior exposure to Power BI or data visualisation tools recommended.