DP-600: Implement analytics solutions with Microsoft Fabric

The primary audience for this course is data professionals with experience in data modeling, mining, and analysis. DP-600 is designed for professionals who want to use Microsoft Fabric to build and deploy enterprise-scale data analytics solutions.

• Introduction to end-to-end analytics with Microsoft Fabric

• Manage Microsoft Fabric

• Ingesting data with Dataflows Gen2 in Microsoft Fabric

• Data Ingestion with Spark Notebooks and Microsoft Fabric

• Use Data Factory pipelines in Microsoft Fabric

• Get started with lake houses on Microsoft Fabric

• Stage a fabric lake house using an architectural medallion design

• Use Apache Spark on Microsoft Fabric

• Working with Delta Lake tables in Microsoft Fabric

• Get started with data warehouses in Microsoft Fabric

• Load data into a Microsoft Fabric data store

• Query a data store in Microsoft Fabric

• Monitor a Microsoft Fabric datastore

• Understanding scalability in Power BI

• Create Power BI model relationships

• Use tools to optimize Power BI performance

• Apply Power BI model security

Exploring End-to-End Analytics with Microsoft Fabric

• Describes end-to-end analytics in Microsoft Fabric
• Understand data teams and roles that use Fabric
• Describes how to enable and use Fabric

Microsoft Fabric Management

• Describe Fabric admin tasks
• Navigate the admin center
• Manage user access

Data Ingestion with Gen2 Dataflows in Microsoft Fabric

Data Ingestion with Spark Notebooks and Microsoft Fabric

Using Data Factory Pipelines in Microsoft Fabric

Introduction to Lake Warehouses in Microsoft Fabric

Using Apache Spark in Microsoft Fabric

Using Delta Lake tables in Microsoft Fabric

Protect your Fabric Lake Warehouse

Introduction to data warehouses in Microsoft Fabric

Loading data into a Microsoft Fabric data warehouse

Querying a data warehouse in Microsoft Fabric

Monitoring a Microsoft Fabric Data Warehouse

Protect your Fabric data storage

Scalability in Power BI

• Description of the importance of creating scalable semantic models
• Implementing Power BI data modeling best practices
• Using the Power BI Large Dataset Storage Format

Create model relationships

• Build relationships.
• Using DAX relational functions.
• Understanding relationship assessment.

Using tools to optimize Power BI performance

• Optimize solutions using aggregations, dual-storage mode, and hybrid tables.
• Optimize queries with Performance Analyzer.
• Troubleshoot DAX performance issues using DAX Studio.
• Optimize a data model using the Tabular Editor

Apply semantic model security

• Restrict access to Power BI model data with RLS.
• Restrict access to Power BI model objects with OLS.
• Apply best development practices to enforce security for Power BI models.

This course is best suited for those with a PL-300 certification or similar experience using Power BI for data transformation, modeling, visualization, and exchange. Additionally, students should have prior experience building and implementing enterprise-level data analytics solutions.

• Course: English / Spanish

• Labs: English / Spanish

Microsoft Certified: Fabric Analytics Engineer Associate

As a Fabric Analytics Associate Engineer, you should have experience designing, building, and implementing enterprise-scale data analytics solutions.

Level: Intermediate
Role: Data Engineer, Data Analyst
Product: Microsoft Fabric
Subject: Data And AI