This module explores the distinctions and overlaps between data warehouses, data lakehouses, and related technologies within the Microsoft Fabric platform. Learners will gain insights into storage architectures, concurrency management, and criteria for selecting the right solution for various business needs. The module also covers emerging trends such as mirror databases and the integration of OLTP capabilities.

This module explores the end-to-end process of ingesting, processing, and analyzing real-time data streams using modern tools and platforms such as Microsoft Fabric. Learners will discover how to leverage eventstream pipelines, Change Data Capture, KQL queries, and AI-powered assistants to gain actionable insights and automate responses. The module also covers monitoring, alerting, and interpreting real-time analytics for data-driven decision making.

This module guides learners through the process of structuring, contextualizing, and optimizing data using semantic models in Power BI. You will explore key concepts such as DAX, composite models, hierarchies, translations, and performance enhancements to enable effective data analysis and reporting. By the end, you'll be equipped to design robust semantic models that support advanced analytics and multilingual reporting.

This module guides learners through transforming raw data into actionable insights using Microsoft Fabric's analytical and reporting tools. Participants will explore interactive reporting, AI-powered data exploration, dashboard creation, and best practices for effective business analysis. The module also covers advanced features like translytical task flows and paginated reports for comprehensive data-driven decision-making.