Overview

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This course focuses on modern data architectures, including lakehouse environments, and demonstrates how to turn raw data into actionable insights that drive business decisions. Throughout the course, learners will develop practical skills in advanced data transformation, organizing data across data warehouses and data lakes, and processing real-time data streams. By applying these techniques, participants will be able to build scalable data pipelines and deliver meaningful analytics outcomes. What sets this course apart is its blend of foundational concepts with hands-on applications, enabling learners to design semantic models and create interactive reports using modern tools like Fabric. This ensures a balance between theoretical understanding and real-world implementation. This course is ideal for data professionals, analysts, and IT practitioners looking to enhance their data engineering and analytics capabilities. A basic understanding of data concepts and analytics tools will be beneficial. This course is part two of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization

Syllabus

Advanced Data Transformation

This module guides learners through advanced techniques for transforming raw data into actionable insights using Microsoft Fabric. You will explore the stages of data transformation, evaluate and implement various tools and methods such as T-SQL and dataflows, and orchestrate complex workflows with solutions like Apache Airflow. By the end, you'll be equipped to select, execute, and manage sophisticated data transformation processes in modern analytics environments.

Organizing data between Data Warehouse and Data Lake

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.

Processing and Analyzing Real-Time Data

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.

Designing Semantic Models

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.

Business Analysis and 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.