Microsoft Fabric Analytics Engineer

Introduction to end-to-end analytics using Microsoft Fabric

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.

• Explore end-to-end analytics with Microsoft Fabric
• Data teams and Microsoft Fabric
• Enable and use Microsoft Fabric
• Knowledge Check

Get started with lakehouses in Microsoft Fabric

Get started with lakehouses in Microsoft Fabric

• Explore the Microsoft Fabric lakehouse
• Work with Microsoft Fabric lakehouses
• Explore and transform data in a lakehouse
• Exercise - Create a Microsoft Fabric lakehouse

Use Apache Spark in Microsoft Fabric

Apache Spark is a core technology for large-scale data analytics. Microsoft Fabric provides support for Spark clusters, enabling you to analyze and process data at scale.

• Prepare to use Apache Spark
• Run Spark code
• Work with data in a Spark dataframe
• Work with data using Spark SQL
• Visualize data in a Spark notebook
• Exercise - Analyze data with Apache Spark

Work with Delta Lake tables in Microsoft Fabric

Tables in a Microsoft Fabric lakehouse are based on the Delta Lake technology commonly used in Apache Spark. By using the enhanced capabilities of delta tables, you can create advanced analytics solutions.

• Understand Delta Lake
• Create delta tables
• Optimize delta tables
• Work with delta tables in Spark
• Use delta tables with streaming data
• Exercise - Use delta tables in Apache Spark

Orchestrate processes and data movement with Microsoft Fabric

Use Data Factory pipelines in Microsoft Fabric

• Understand pipelines
• Use the Copy Data activity
• Use pipeline templates
• Run and monitor pipelines
• Exercise - Ingest data with a pipeline

Ingest Data with Dataflows Gen2 in Microsoft Fabric

Data ingestion is crucial in analytics. Microsoft Fabric's Data Factory offers Dataflows for visually creating multi-step data ingestion and transformation using Power Query Online.

• Understand Dataflows Gen2 in Microsoft Fabric
• Explore Dataflows Gen2 in Microsoft Fabric
• Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric
• Exercise - Create and use a Dataflow Gen2 in Microsoft Fabric

Get started with data warehouses in Microsoft Fabric

Understand the key components and design considerations for implementation of data warehouses in Microsoft Fabric.

• Understand data warehouse fundamentals
• Understand data warehouses in Fabric
• Query and transform data
• Prepare data for analysis and reporting
• Secure and monitor your data warehouse
• Exercise - Analyze data in a data warehouse

Get started with Real-Time Intelligence in Microsoft Fabric

Analysis of real-time data streams is a critical capability for any modern data analytics solution. You can use the Real-Time Intelligence capabilities of Microsoft Fabric to ingest, query, and process streams of data.

• What is real-time data analytics?
• Real-Time Intelligence in Microsoft Fabric
• Ingest and transform real-time data
• Store and query real-time data
• Visualize real-time data
• Automate actions
• Exercise - Explore Real-Time Intelligence in Fabric

Get started with data science in Microsoft Fabric

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.

• Understand the data science process
• Explore and process data with Microsoft Fabric
• Train and score models with Microsoft Fabric
• Exercise - Explore data science in Microsoft Fabric

Administer a Microsoft Fabric environment

Microsoft Fabric is a SaaS solution for end-to-end data analytics. As an administrator, you can configure features and manage access to suit your organization's needs.

• Understand the Fabric Architecture
• Understand the Fabric administrator role
• Manage Fabric security
• Govern data in Fabric

Get started with data warehouses in Microsoft Fabric

Understand the key components and design considerations for implementation of data warehouses in Microsoft Fabric.

• Understand data warehouse fundamentals
• Understand data warehouses in Fabric
• Query and transform data
• Prepare data for analysis and reporting
• Secure and monitor your data warehouse
• Exercise - Analyze data in a data warehouse

Load data into a Microsoft Fabric data warehouse

Explore the process of loading data into a warehouse in Microsoft Fabric.

• Explore data load strategies
• Use data pipelines to load a warehouse
• Load data using T-SQL
• Load and transform data with Dataflow Gen2
• Exercise: Load data into a warehouse in Microsoft Fabric

Query a data warehouse in Microsoft Fabric

Learn how to query a data warehouse in Microsoft Fabric using different tools.

• Query data
• Use the SQL query editor
• Explore the visual query editor
• Use client tools to query a warehouse
• Exercise: Query a data warehouse in Microsoft Fabric

Monitor a Microsoft Fabric data warehouse

A data warehouse is a vital component of an enterprise analytics solution. It's important to learn how to monitor a data warehouse so you can better understand the activity that occurs in it.

• Monitor capacity metrics
• Monitor current activity
• Monitor queries
• Exercise - Monitor a data warehouse in Microsoft Fabric

Secure a Microsoft Fabric data warehouse

Learn the key concepts and strategies for protecting sensitive data in Microsoft Fabric data warehouses.

• Explore dynamic data masking
• Implement row-level security
• Implement column-level security
• Configure SQL granular permissions using T-SQL
• Exercise: Secure a warehouse in Microsoft Fabric

Add measures to Power BI Desktop models

In this module, you'll learn how to work with implicit and explicit measures. You'll start by creating simple measures, which summarize a single column or table. Then, you'll create more complex measures based on other measures in the model. Additionally, you'll learn about the similarities of, and differences between, a calculated column and a measure.

• Create simple measures
• Create compound measures
• Create quick measures
• Compare calculated columns with measures
• Check your knowledge
• Exercise - Create DAX Calculations in Power BI Desktop

Design scalable semantic models

Good modeling practices lead to scalable semantic models that simplify analysis and reporting of large, complex data, enhancing Power BI reports for an optimal user experience.

• Choose the best storage mode
• Configure semantic models for large data
• Work with relationships
• Write DAX for readability with complex calculations
• Create dynamic calculation elements
• Exercise - Design a scalable semantic model

Optimize a model for performance in Power BI

Performance optimization, also known as performance tuning, involves making changes to the current state of the semantic model so that it runs more efficiently. Essentially, when your semantic model is optimized, it performs better.

• Introduction to performance optimization
• Review performance of measures, relationships, and visuals
• Use variables to improve performance and troubleshooting
• Reduce cardinality
• Optimize DirectQuery models with table level storage
• Create and manage aggregations
• Check your knowledge

Create and manage Power BI assets

Create Power BI assets for your analytics environment for structure and consistency, such as Power BI template and project files. Reusable assets and using the XMLA endpoint support application lifecycle management, including continuous integration and deployment.

• Create reusable Power BI assets
• Manage development lifecycle for Power BI assets
• Use lineage view and endorse data assets
• Manage a Power BI semantic model using XMLA endpoint
• Exercise: Create reusable Power BI assets

Enforce Power BI model security

Enforce model security in Power BI using row-level security and object-level security.

• Restrict access to Power BI model data
• Restrict access to Power BI model objects
• Apply good modeling practices
• Exercise: Enforce model security

Administer a Microsoft Fabric environment

Microsoft Fabric is a SaaS solution for end-to-end data analytics. As an administrator, you can configure features and manage access to suit your organization's needs.

• Understand the Fabric Architecture
• Understand the Fabric administrator role
• Manage Fabric security
• Govern data in Fabric

Secure data access in Microsoft Fabric

Learn the key concepts and strategies for securing data access in Microsoft Fabric.

• Understand the Fabric security model
• Configure workspace and item permissions
• Apply granular permissions
• Exercise: Secure data access in Microsoft Fabric

Secure a Microsoft Fabric data warehouse

Learn the key concepts and strategies for protecting sensitive data in Microsoft Fabric data warehouses.

• Explore dynamic data masking
• Implement row-level security
• Implement column-level security
• Configure SQL granular permissions using T-SQL
• Exercise: Secure a warehouse in Microsoft Fabric

Govern data in Microsoft Fabric with Purview

Learn how Microsoft Purview enables the highest level of data governance for your Microsoft Fabric data lakes. Ensure that data is both tightly controlled and highly available for compliant analysis.

• Govern data in Microsoft Fabric
• Why use Microsoft Purview with Microsoft Fabric?
• Govern data in the Microsoft Purview hub