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- Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Discover the capabilities Fabric has to offer, understand how it works, and identify how you can use Fabric for your analytics needs.
In this module, you learn how to:
- Identify the capabilities of Microsoft Fabric.
- Implement Microsoft Fabric to meet your enterprise's analytics needs.
- Describe how Fabric supports AI capabilities through Copilot, data agents, and Fabric IQ.
- Lakehouses in Microsoft Fabric combine data lake flexibility with data warehouse analytics. Learn how to create, load, and query a lakehouse on a single platform.
In this module, you learn how to:
- Describe core features and capabilities of lakehouses in Microsoft Fabric.
- Create a lakehouse.
- Ingest and transform data in a lakehouse.
- Query and analyze lakehouse data with SQL and Spark.
- Understand the key components and design considerations for implementation of data warehouses in Microsoft Fabric.
In this module, you learn how to:
Describe data warehouse concepts and dimensional modeling fundamentals.
Create tables, load data, and understand ingestion methods in a Fabric warehouse.
Query and transform data using T-SQL and the visual query editor.
Model warehouse data for reporting and downstream consumption.
Secure and monitor a data warehouse.
- Real-Time Intelligence in Microsoft Fabric has capabilities that help you ingest, process, store, visualize, and act on data in motion to gain immediate insights from events as they happen.
In this module, you learn how to:
- Describe real-time analytics, streams and events.
- Understand Real-Time Intelligence components in Fabric.
- Ingest data and transform data in motion.
- Store and query data in KQL databases.
- Visualize streaming data with Real-Time Dashboards.
- Automate actions with Activator.
- Get started with data science in Microsoft Fabric by learning how to train a model in a notebook, and track your metrics with MLflow and experiments.
In this module, you'll learn how to:
- Understand the data science process
- Train models with notebooks in Microsoft Fabric
- Track model training metrics with MLflow and experiments
- Learn how SQL Database in Microsoft Fabric works, the key concepts, and practical examples to help users SQL Database effectively as part of their analytics solutions.
By the end of this module, you'll be able to:
- Explain how SQL database in Fabric works.
- Understand security options in SQL database.
- Explain how to use Copilot to enhance troubleshooting.
- Explore mirroring and data virtualization capabilities.
- Design semantic models for scale in Microsoft Fabric. Choose storage modes, design star schema relationships, create scalable calculation patterns, and configure settings for large datasets and concurrent consumption.
By the end of this module, you'll be able to:
- Choose a storage mode based on data freshness, performance, and source location.
- Design star schema relationships for clarity and performance in a semantic model.
- Design calculations that stay performant and maintainable as data volumes and team size grow.
- Configure semantic model settings that support large-scale consumption.
- Learn the fundamentals of Microsoft Fabric IQ, including how ontologies create a shared business vocabulary, the components that make up the Fabric IQ ecosystem, and how ontology modeling differs from traditional data modeling approaches.
By the end of this module, you'll be able to:
- Explain what Fabric IQ is and how ontologies define business vocabulary
- Describe the role of ontology items in creating entity types, properties, and relationships
- Distinguish between the roles of each Fabric IQ component: ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models
- Compare ontology modeling's concept-driven approach with traditional use-case-driven data modeling
