Learning Enterprise Data Architecture BI, AI & Cloud Foundations

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Enterprise Data Architecture BI, AI & Cloud Foundations
Published 5/2026
Created by Mohammed Adnan
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 23 Lectures ( 4h 7m ) | Size: 7.8 GB

Learn enterprise data platforms, BI architecture, semantic layers, governance, cloud foundations, and AI-ready design.
What you'll learn
Understand enterprise architecture mindset and how data, BI, cloud, and AI fit together in modern organizations.
Learn core data platform layers including ingestion, storage, transformation, governance, semantic, BI, and AI layers.
Compare lakehouse, warehouse, data mart, and semantic layer roles from an enterprise architecture perspective.
Design better BI and data architectures using governance, scalability, security, and business-consumption thinking.
Requirements
No advanced coding experience required.
Basic understanding of data, reporting, BI, or analytics will help.
Knowledge of tools like Power BI, Fabric, Tableau, SQL, or cloud platforms is useful but not mandatory.
Interest in moving from tool-level thinking to architecture-level thinking.
Description
This course is designed for data, BI, analytics, cloud, and technology professionals who want to move from tool-level thinking to architecture-level thinking.
In many organizations, people learn individual tools such as Power BI, Microsoft Fabric, SQL, Tableau, cloud platforms, or AI tools. But when they enter enterprise projects, the real challenge is different. They need to understand how data platforms are designed, how BI layers connect to business users, how governance and security fit into the architecture, and how modern AI depends on trusted data foundations.
This course focuses on the foundations of enterprise data architecture. You will learn the mindset of an enterprise architect and understand the core layers of a modern data platform, including ingestion, storage, transformation, governance, semantic layer, BI consumption, and AI readiness.
We will also clarify important architecture concepts such as lakehouse, warehouse, data mart, and semantic layer. Instead of treating these as isolated technologies, you will learn where each layer fits and how they work together in real enterprise scenarios.
The course is not designed as a deep coding course or product demo course. It is designed to help you think like an architect. You will learn how to connect business needs, technical layers, platform choices, governance, scalability, security, and user adoption into one practical architecture view.
By the end of this course, you will have a strong foundation to understand enterprise data platforms, BI architecture, semantic architecture, and AI-ready data design. This course is especially useful if you are a BI developer, data analyst, Power BI professional, Fabric learner, data engineer, solution architect, or anyone preparing for enterprise-level architecture discussions.
Who this course is for
Data analysts, BI developers, Power BI developers, and reporting professionals who want to grow into architecture roles.
Data engineers and cloud data professionals who want to understand enterprise architecture from a business and BI angle.
Solution architects, technical leads, and analytics managers who design or review data and BI platforms.
Students and professionals who want to understand how modern enterprise data platforms are structured.
Homepage

https://www.udemy.com/course/enterprise-data-architecture-bi-ai-cloud-foundations

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