DP-600: Microsoft Fabric Analytics Engineer

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.
In this module, you'll learn how to:

• Describe Dataflow capabilities in Microsoft Fabric
• Create Dataflow solutions to ingest and transform data
• Include a Dataflow in a pipeline

Ingest data with Spark and Microsoft Fabric notebooks

Discover how to use Apache Spark and Python for data ingestion into a Microsoft Fabric lakehouse. Fabric notebooks provide a scalable and systematic solution.
In this module, you'll learn how to:

• Ingest external data to Fabric lakehouses using Spark
• Configure external source authentication and optimization
• Load data into lakehouse as files or as Delta tables

Use Data Factory pipelines in Microsoft Fabric

Microsoft Fabric includes Data Factory capabilities, including the ability to create pipelines that orchestrate data ingestion and transformation tasks.
In this module, you'll learn how to:

• Describe pipeline capabilities in Microsoft Fabric
• Use the Copy Data activity in a pipeline
• Create pipelines based on predefined templates
• Run and monitor pipelines

Get started with lakehouses in Microsoft Fabric

Lakehouses merge data lake storage flexibility with data warehouse analytics. Microsoft Fabric offers a lakehouse solution for comprehensive analytics on a single SaaS platform.
In this module, you'll learn how to:

• Describe core features and capabilities of lakehouses in Microsoft Fabric
• Create a lakehouse
• Ingest data into files and tables in a lakehouse
• Query lakehouse tables with SQL

Organize a Fabric lakehouse using medallion architecture design

Explore the potential of the medallion architecture design in Microsoft Fabric. Organize and transform your data across Bronze, Silver, and Gold layers of a lakehouse for optimized analytics.
In this module, you'll learn how to:

• Describe the principles of using the medallion architecture in data management.
• Apply the medallion architecture framework within the Microsoft Fabric environment.
• Analyze data stored in the lakehouse using DirectLake in Power BI.
• Describe best practices for ensuring the security and governance of data stored in the medallion architecture.

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 in a Lakehouse at scale.
In this module, you'll learn how to:

• Configure Spark in a Microsoft Fabric workspace
• Identify suitable scenarios for Spark notebooks and Spark jobs
• Use Spark dataframes to analyze and transform data
• Use Spark SQL to query data in tables and views
• Visualize data in a Spark notebook

Work with Delta Lake tables in Microsoft Fabric

Tables in a Microsoft Fabric lakehouse are based on the Delta Lake storage format commonly used in Apache Spark. By using the enhanced capabilities of delta tables, you can create advanced analytics solutions.
In this module, you'll learn how to:

• Understand Delta Lake and delta tables in Microsoft Fabric
• Create and manage delta tables using Spark
• Use Spark to query and transform data in delta tables
• Use delta tables with Spark structured streaming

Get started with data warehouses in Microsoft Fabric

Data warehouses are analytical stores built on a relational schema to support SQL queries. Microsoft Fabric enables you to create a relational data warehouse in your workspace and integrate it easily with other elements of your end-to-end analytics solution.
In this module, you'll learn how to:

• Describe data warehouses in Fabric
• Understand a data warehouse vs a data Lakehouse
• Work with data warehouses in Fabric
• Create and manage fact tables and dimensions within a data warehouse

Load data into a Microsoft Fabric data warehouse

Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.
In this module, you'll:

• Learn different strategies to load data into a data warehouse in Microsoft Fabric.
• Learn how to build a data pipeline to load a warehouse in Microsoft Fabric.
• Learn how to load data in a warehouse using T-SQL.
• Learn how to load and transform data with dataflow (Gen 2).

Query a data warehouse in Microsoft Fabric

Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.
In this module, you'll:

• Use SQL query editor to query a data warehouse.
• Explore how visual query editor works.
• Learn how to connect and query a data warehouse using SQL Server Management Studio.

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.
After completing this module, you'll be able to:

• Monitor capacity unit usage with the Microsoft Fabric Capacity Metrics app.
• Monitor current activity in the data warehouse with dynamic management views.
• Monitor querying trends with query insights views.

Understand scalability in Power BI

Scalable data models enable enterprise-scale analytics in Power BI. Implement data modeling best practices, use large dataset storage format, and practice building a star schema to design analytics solutions that can scale.
By the end of this module, you’ll be able to:

• Describe the importance of building scalable data models
• Implement Power BI data modeling best practices
• Use the Power BI large dataset storage format

Create Power BI model relationships

Power BI model relationships form the basis of a tabular model. Define Power BI model relationships, set up relationships, recognize DAX relationship functions, and describe relationship evaluation.
By the end of this module, you’ll be able to:

• Understand how model relationship work.
• Set up relationships.
• Use DAX relationship functions.
• Understand relationship evaluation.

Use tools to optimize Power BI performance

Use tools to develop, manage, and optimize Power BI data model and DAX query performance.
After completing this module, you'll be able to:

• Optimize queries using performance analyzer.
• Troubleshoot DAX performance using DAX Studio.
• Optimize a data model using Tabular Editor.

Enforce Power BI model security

Enforce model security in Power BI using row-level security and object-level security.
By the end of this module, you’ll be able to:

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

1. Hva koster kurset?

Pris: 24 500 NOK.

2. Hvor lenge varer kurset, og når?

Kurset varer i 4 dager, kl. 09:00–16:00.

3. Hvordan foregår kurset?

Instruktørledet som klasseromskurs eller live virtuelt. Undervisningen kombinerer forelesning, demonstrasjoner og praktiske gjennomganger av Fabric-komponenter.

4. Hvilket språk undervises kurset på?

Engelsk kursmateriell, engelsktalende instruktør.

5. Hvem passer dette kurset for?

Data Analysts og Data Engineers med erfaring fra datamodellering, ETL/ELT og analyse, som skal bygge og forvalte enterprise-scale analy seløsninger i Microsoft Fabric.

6. Hvilke forkunnskaper bør jeg ha?

Kurset er best egnet for deltakere med PL-300-kompetanse (Power BI: transformasjon, modellering, visualisering, deling) eller tilsvarende erfaring, samt praktisk arbeid med analyse-løsninger i virksomhet.

7. Hva lærer jeg i kurset?

• Ingest/transform med Dataflows Gen2, pipelines og Copy Data

• Lakehouse i Fabric: Spark, Delta Lake, og medallion-arkitektur (Bronze/Silver/Gold)

• Data warehouse i Fabric: lasting, T-SQL-spørringer, sikkerhet og overvåkning

• Sanntid med Eventstreams og eventhouse, samt real-time dashboards

• Power BI for enterprise-skala: skalerbare datamodeller, relasjoner, ytelsesverktøy (Performance Analyzer, DAX Studio, Tabular Editor) og RLS/OLS

• Miljøstyring, CI/CD og monitorering i Fabric

8. Gir kurset sertifisering?

Kurset forbereder til eksamen DP-600: Implementing Analytics Solutions Using Microsoft Fabric, som gir Microsoft Certified: Fabric Analytics Engineer Associate. (Eksamen er ikke inkludert.)

9. Hva er inkludert i kursavgiften?

Digital kursdokumentasjon. Ved klasseromskurs er lunsj og bevertning inkludert.

10. Trenger jeg egen tenant eller spesielle verktøy?

Egen Fabric-/M365-tilgang er en fordel for videre arbeid, men du får veiledning i oppsett og bruk under kurset.

11. Kan kurset skreddersys og leveres bedriftsinternt?

Ja – vi skreddersyr agenda, kildedata og øvelser til deres miljø og leverer gjerne bedriftsinternt (norsk/engelsk).

Vil du bygge videre etter DP-600? Her er naturlige steg for team som jobber med data-til-innsikt i Fabric og Power BI. Alle kurs kan skreddersys og leveres bedriftsinternt. 

• DP-700: Microsoft Fabric Data Engineer – datainntak, orkestrering og sanntid.

• DP-601: Implementing a Lakehouse with Microsoft Fabric (Applied Skills) – lakehouse og medallion i praksis.

• DP-602: Implement a Data Warehouse with Microsoft Fabric (Applied Skills) – last, spørre, sikre og overvåke DW.

• DP-603: Implementing Real-Time Intelligence with Microsoft Fabric (Applied Skills) – eventstreams, eventhouse og real-time dashboards.

• DP-604: Implement a data science and machine learning solution for AI with Microsoft Fabric (Applied Skills) – ML/AI-scenarier på Fabric.

• PL-300: Design and Manage Analytics Solutions Using Power BI – ytelse, modellkvalitet og deling.

Tips: For et komplett Fabric-løp: DP-700 → DP-601/DP-602 → DP-600, og legg til DP-603 for sanntid og DP-604 når ML/AI-scenarier skal inn i plattformen.