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DP-601 Implementing a Lakehouse with Microsoft Fabric
Data landscapes are growing more complex – and the need for platforms that seamlessly connect processing, storage, and analysis is increasing. Microsoft Fabric provides this framework as an end-to-end analytics environment.
Key topics
- Build and operate lakehouse structures in Microsoft Fabric.
- Design data processes end-to-end from source to report.
- Store structured and unstructured data on a shared foundation.
- Process large data volumes efficiently with Spark.
- Set up reports and analytics on consistent, centralized data.
Prerequisite
Anyone with experience in BI, data analysis, or cloud-related technologies is well prepared for the content of this course.
Target group
Everyone responsible for projects in data engineering, business intelligence, or data-driven IT solutions.
Lakehouse skills lay the technical groundwork for analytics environments that keep pace with growing demands.
Course content
End-to-end analytics with Microsoft Fabric
- Building end-to-end analytics workflows from source to insight
- Enabling data team collaboration on a unified platform
- Setting up and using Microsoft Fabric productively
Lakehouse architecture in Fabric
- Exploring the structure and concept of the Fabric Lakehouse
- Practical use of the Lakehouse in Microsoft Fabric
- Analyzing and transforming data in the Lakehouse
Working with Apache Spark in Fabric
- Getting started with the fundamentals of Apache Spark
- Writing and executing Spark scripts
- Processing data with Spark DataFrames
- Writing SQL queries with Spark SQL
- Visualizing analysis results in Spark notebooks
Using Delta Lake tables
- Understanding the concept and benefits of Delta Lake
- Creating and configuring Delta tables
- Applying Spark operations to Delta tables
- Managing streaming data with Delta tables
Using Dataflows Gen2 in Microsoft Fabric
- How Dataflows Gen2 work and where they fit
- Exploring Dataflows Gen2 capabilities hands-on
- Combining Dataflows Gen2 with data pipelines
Configuring pipelines with Data Factory
- Structure and behavior of data pipelines
- Configuring and using Copy Data activities
- Using predefined templates for faster pipeline setup
- Starting, monitoring, and controlling pipeline runs
What value does a Lakehouse with Microsoft Fabric deliver?
- A unified data platform reduces complexity, speeds up analysis, and turns raw data into a direct foundation for decision-making.
Who benefits most from Lakehouse expertise?
- Particularly relevant for data engineering, analytics, and BI roles that plan and implement scalable data architectures.
What challenges does a Lakehouse approach address?
- Data silos, slow pipelines, and inconsistent datasets are systematically eliminated through an integrated architecture.
What prior knowledge is helpful for the course?
- A foundation in data processing, SQL, and cloud concepts makes it easier to get started and speeds up practical implementation.
How strongly is the course content aligned with real-world practice?
- Concrete use cases from everyday work are at the core: data integration, transformation, and analysis are built directly within the platform.
What makes Microsoft Fabric a sought-after platform?
- Growing data volumes and real-time requirements are driving demand for modern, centrally managed analytics platforms.
What professional opportunities does Fabric expertise open up?
- Specialized knowledge in data engineering and analytics increases market value and opens new project opportunities in the cloud space.
How does Lakehouse knowledge impact projects?
- Well-structured data flows and optimized architectures deliver faster results and consistently high data quality.
