DP-600 Microsoft Fabric Analytics Engineer

Opi yritystason data-analytiikkaratkaisujen toteuttaminen Microsoft Fabricilla tällä 4 päivän koulutuksella.

Tavoite

Tässä koulutuksessa käydään läpi kattavasti Microsoft Fabricin komponentit (Lakehouse, Data Warehouse, Notebooks, DataFlows, Data Pipelines, Semantic Models), joiden avulla toteutetaan analytiikkaratkaisut.

Kenelle

Koulutus on suunnattu Data Analytics ja Data Engineer -asiantuntijoille, arkkitehdeille ja kaikille, joiden tulee osata Microsoft Fabric -tekniikat.

Lisätiedot

Koulutus valmentaa Microsoftin viralliseen DP-600 Implementing Analytics Solutions Using Microsoft Fabric -sertifiontitestiin.

Esitietoina osallistujilla olisi hyvä olla Power BI osaaminen (esim. PL-300 koulutus tai vastaava) sekä mielellään osaamista SQL:n ja Pythonin perusteista.

Koulutuksen sisältö

Administer Microsoft Fabric

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

Ingest Data with Dataflows Gen2 in Microsoft Fabric

• Describe Dataflow (Gen2) capabilities in Microsoft Fabric
• Create Dataflow (Gen2) solutions to ingest and transform data
• Include a Dataflow (Gen2) in a pipeline

Ingest data with Spark and Microsoft Fabric notebooks

• 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

• 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

• 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

• 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

• 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

• 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

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

Load data into a Microsoft Fabric data warehouse

• 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

• 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.

Get started with data warehouses in Microsoft Fabric

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

Monitor a Microsoft Fabric data warehouse

• 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

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

Get started with data warehouses in Microsoft Fabric

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

Create Power BI model relationships

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

Use tools to optimize Power BI performance

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

Enforce Power BI model security

• 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.

Avainsanat

Microsoft Fabric, Data Analytics, Power BI, Lakehouse, Dataflow, Data Factory, Data Warehouse