DP-600 Microsoft Fabric Analytics Engineer

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

Huomioithan, että Microsoft Fabricista on myös toinen koulutus DP-700 Microsoft Fabric Data Engineer, joka on osin päällekkäinen tämän koulutuksen kanssa, mutta painottuu enemmän Apache Sparkin käyttöön ja reaaliaikaisen datan käsittelyyn.

Tavoite

Opi yritystason data-analytiikkaratkaisujen toteuttaminen Microsoft Fabricilla.

Kenelle

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

Koulutukseen osallistujalla on suositeltavaa olla Power BI osaaminen (esim. PL-300 Microsoft Power BI Data Analyst -koulutus tai vastaava) sekä osaamista SQL:n ja/tai DAX:in perusteista.

Lisätiedot

Koulutus valmentaa Microsoftin viralliseen Microsoft Certified: Fabric Analytics Engineer Associate -sertifiontitestiin.

Koulutuksen  sisältö

Explore end-to-end analytics with Microsoft Fabric

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

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

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

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

Use Apache Spark in Microsoft Fabric

• Prepare to use Apache Spark
• Work with Data using Spark notebooks
• Visualize data in Spark notebook

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.

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.

Secure a Microsoft Fabric data warehouse

• Dynamic data Masking.
• Row level security
• Column level security.

Add measures to Power BI semantic models

• Understand implicit and explicit measures.
• Create measures, calculated columns, and calculated tables.
• Identify when to use a measure or calculated column

Design scalable semantic models

• Choose appropriate storage modes for your semantic model.
• Enable large semantic model storage format and incremental refresh.
• Create relationships between tables in a semantic model.
• Design dynamic elements to extend calculations in a semantic model.

Optimize a model for performance in Power BI

• Review the performance of measures, relationships, and visuals.
• Improve performance by reducing cardinality levels.
• Optimize DirectQuery models with table level storage.
• Create and manage aggregations.

Create and manage Power BI assets

• Create core and specialized semantic models.
• Create Power BI Template and Power BI Project files.
• Use lineage view and endorse data assets in Power BI service.
• Use XMLA endpoint to connect semantic models.

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.

Get started with Real-Time Intelligence with Microsoft Fabric

• Use basic syntax and of Kusto Query Language (KQL) and querysets.
• Describe how to execute T-SQL queries in the Queryset canvas.
• Copy, export, and share data results.

Secure data access in Microsoft Fabric

• Understand Fabric security model
• Configure workspace and item permissions
• Apply granular permissions.

Administer Microsoft Fabric

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

Avainsanat

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