Model Power BI Data with Security

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Model Power BI Data with Security

Coursera · Intermediate ·📊 Data Analytics & Business Intelligence ·3mo ago

Key Takeaways

Models and secures financial data in Power BI using real-world business scenarios

Original Description

In this intermediate-level course, you’ll learn how to model and secure financial data in Power BI using real-world business scenarios. You’ll start by importing General Ledger, Cost Center, and Budget data, then design a star-schema model that supports accurate, high-performing analytics. Through guided demos and hands-on practice, you’ll define relationships, create DAX measures for Gross Margin, and validate your model structure for reliable reporting. Next, you’ll apply Row-Level Security (RLS) and Role-Based Access Control (RBAC) to ensure sensitive data stays protected as you publish to Power BI Service. Along the way, you’ll explore how modeling and security intersect—where table structure influences filter logic and access rules affect collaboration. By the end of the course, you’ll have the confidence to build, test, and deploy Power BI dashboards that are both powerful and secure, ready for real enterprise environments.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Tracking Macroeconomic Indicators with the Finance Toolkit
Learn to track macroeconomic indicators using the Finance Toolkit and understand its importance in global economic trends
Dev.to · Jeroen Bouma
📰
Pydantic for Data Engineering: Schema Validation in ETL & Pipeline Contracts
Use Pydantic for schema validation in ETL pipelines to ensure data consistency and quality
Dev.to · Gowtham Potureddi
📰
Half of Data Engineering Jobs on LinkedIn Aren't Real
Understand the discrepancy between reported data engineering job growth and actual job availability on LinkedIn
Dev.to · DataDriven
📰
Evolutionary Data Through Schemaboi: Achieving Forward, Backwards, and Sideways Compatibility
Learn how Schemaboi achieves forward, backwards, and sideways compatibility for evolutionary data through self-contained schemas in file headers
InfoQ AI/ML
Up next
6-Phase SQL Roadmap 2026 | Data Analytics & Engineering | #shorts
SCALER
Watch →