Under den här kursen lär du dig metoder och praxis för att implementera och hantera enterprise-lösningar för dataanalys med hjälp av Microsoft Fabric.
Du lär dig hur man använder Microsoft Fabric-komponenter, inklusive lakehouses, data warehouses, notebooks, dataflows, datapipelines och semantiska modeller, för att skapa och distribuera analysresurser.
Kursen är förberedande för certifieringstestet DP-600, Implementing Analytics Solutions Using Microsoft Fabric.
Den här kursen vänder sig till dig som arbetar med dataanalys och vill lära dig bygga lösningar med Microsoft Fabric. Kursen är förberedande för certifieringen Implementing Analytics Solutions Using Microsoft Fabric, DP-600.
Du bör ha förkunskaper om Azure som dataplattform motsvarande kursen MDP-900, Microsoft Azure Data Fundamentals. Dessutom rekommenderas kunskaper om Power BI motsvarande kursen MPL-300, Microsoft Power BI Data Analyst.
Kursmaterialet är på engelska, med detta innehåll:
Learn how to describe the full analytics workflow in Fabric, identify the roles and teams involved, and understand how to enable and use the Fabric service in their tenant.
This section introduces the lakehouse architecture in Fabric—contrasting data lakes and data warehouses—and explains how a lakehouse unifies flexible storage with SQL-based querying for analytics. Participants also learn to load data into a lakehouse using notebooks, Dataflows Gen2, pipelines, and shortcuts, and to explore and transform that data with Power BI and Spark tools.
This part covers the low-code graphical environment of Dataflow Gen2, showing how to extract, transform, and load data for reuse in pipelines and detailing its benefits and limitations.
Discover how to build, run, and monitor Data Factory–style pipelines in Fabric, including copying data, using templates, and scheduling jobs.
This section introduces Spark pools and notebooks in Fabric, teaching how to ingest, transform, analyze, and visualize big data at scale with PySpark and Spark SQL.
Learn the fundamentals of relational warehousing in Fabric, including schema design (star and snowflake), table types, and how to create and visualize a warehouse in the Fabric portal.
This part details the four ingestion methods (COPY T-SQL, pipelines, Dataflows Gen2, cross-warehouse), how to stage and transform data, and how to load dimensions and facts with T-SQL.
Participants practice writing T-SQL and DAX queries against warehouse tables, using visual query editors, ranking functions, and exporting results for downstream reporting.
This section covers monitoring techniques using the Fabric Capacity Metrics app, Dynamic Management Views (DMVs), and Query Insights views to track performance, workloads, and long-running queries.
Here you learn to apply Dynamic Data Masking, Row-Level and Column-Level Security, and fine-grained SQL permissions to protect sensitive data in your warehouse.
This module introduces DAX, explains implicit versus explicit measures, calculated columns and tables, and teaches how filter context and the CALCULATE function shape dynamic calculations.
Participants choose storage modes (Import, DirectQuery, Direct Lake), enable large storage and incremental refresh, and apply modeling best practices for performance and maintainability.
Learn to use Performance Analyzer, optimize DAX formulas and relationships, reduce cardinality, and create aggregations to speed up report rendering and query execution.
This section shows how to build core and specialized semantic models, use PBIT and Power BI Project files, manage changes via CI/CD pipelines, endorse content, and work with the XMLA endpoint.
Participants configure Row-Level and Object-Level Security in Power BI models, apply dynamic and static rules, and follow development practices to test and validate permissions.
This module covers the basics of Kusto Query Language (KQL), the Queryset canvas, converting between T-SQL and KQL, and rendering visualizations and charts from streaming data.
Here you learn Fabric’s multi-layer security model, workspace and item-level permissions, granular T-SQL controls, and OneLake data access roles for securing files and folders.
Participants explore Fabric’s architecture, tenant and capacity concepts, use the Admin portal and Capacity Metrics app, manage licenses and user access, and set up governance via endorsements and lineage.
