DP-602 Implement a Data Warehouse with Microsoft Fabric
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Duration
1 day
Location
Course Language English
Training Solutions Online Live
Scalable analytics require clean data structures and reliable platforms. Microsoft Fabric combines key functions for building modern data warehouses and creates transparency across data flows, storage, and usage within an integrated cloud environment.
Key topics
- Services and functionality of Microsoft Fabric.
- Design of modern data warehouse architectures.
- Data ingestion, transformation, and storage.
- Performance optimization and monitoring.
- Roles, permissions, and compliance.
- Operation of analytical data platforms.
Prerequisite
Solid knowledge of SQL and a basic understanding of cloud architectures.
Target audience
Data engineers, analytics professionals, and technical architects.
A structured architectural approach enables stable, expandable, and powerful analytics solutions.
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Course content
Data warehouses
- Understanding the basics of data warehouses
- Understanding data warehouses in Fabric
- Querying and transforming data
- Preparing data for analysis and reporting
- Securing and monitoring data warehouses
Data in Microsoft Fabric
- Explore data loading strategies
- Using data pipelines for warehouse loading
- Load data with T-SQL
- Load and transform data with Dataflow Gen2
Data warehouses in Microsoft Fabric
- Use SQL Editor
- Explore the visual editor
- Use client tools for warehouse queries
Monitoring the data warehouse
- Monitor capacity
- Monitor activity
- Observe queries
What exactly is being implemented in connection with Microsoft Fabric?
- Development of a scalable data warehouse, including data integration, modeling, and performance optimization for real-world business scenarios.
Why is data warehousing with Microsoft Fabric so popular right now?
- Companies centralize their data, break down silos, and make informed decisions more quickly—a clear competitive advantage.
What practical skills are developed?
- Designing modern data architectures, leveraging lakehouse approaches, and efficiently processing large volumes of data.
What risks become apparent without in-depth expertise?
- A lack of structure, slow queries, and high costs resulting from inefficient data pipelines can quickly slow down projects.
For which roles is this topic particularly relevant?
- Data engineers, BI professionals, and IT specialists with a focus on cloud computing, analytics, and scalable data platforms.
Which tools and technologies are the focus?
- Integration of data flows, SQL endpoints, and modern storage concepts within a unified platform.
How practical is the implementation?
- Real-world use cases demonstrate how data sources are connected, transformed, and made available for analysis.
What direct benefits does this knowledge bring to your daily work?
- Faster data delivery, higher-quality analysis, and more efficient decision-making processes within the company.
