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DP-600 Course: Microsoft Fabric Analytics Engineer
This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric . Students will leverage existing analytics expertise and learn how to use Microsoft Fabric components—including data lakes, data warehouses, notebooks, dataflows, data pipelines, and semantic models—to build and deploy analytics assets. 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 deploying enterprise-level data analytics solutions.
The course includes a certification exam and a bonus opportunity for a virtual gift! *Promotion valid until August 31st, for customers in Spain only. Does not apply to self-learning.
Course aimed at
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.
Elements of the DP-600 formation
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Introduction to end-to-end analytics with Microsoft Fabric
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Manage Microsoft Fabric
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Ingesting data with Dataflows Gen2 in Microsoft Fabric
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Data Ingestion with Spark Notebooks and Microsoft Fabric
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Use Data Factory pipelines in Microsoft Fabric
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Get started with lake houses on Microsoft Fabric
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Stage a fabric lake house using an architectural medallion design
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Use Apache Spark on Microsoft Fabric
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Working with Delta Lake tables in Microsoft Fabric
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Get started with data warehouses in Microsoft Fabric
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Load data into a Microsoft Fabric data store
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Query a data store in Microsoft Fabric
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Monitor a Microsoft Fabric datastore
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Understanding scalability in Power BI
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Create Power BI model relationships
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Use tools to optimize Power BI performance
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Apply Power BI model security
DP-600 Course Content
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.
Prerequisites
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.
Language
Microsoft Associate Certification: Fabric Analytics Engineer Associate
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