Power BI Services
Program Information
- 🎓 Delivery Method:
- On-site (available now, on demand)
- Remote (live, on demand)
- Online (self-paced, coming soon)
- ⏳ Duration:
- 3 days, 4 hours per day
- Custom options available for internal teams
- 🧩 Format:
- Interactive workshops
- Hands-on exercises
- 👨🎓 Maximum Participants:
- 12 per session (to ensure personalized interaction)
- 📋 Course Requirements:
- No prior technical background required.
- 📅 Scheduling:
- Flexible scheduling available on demand
- 📞 Contact to Schedule:
- 📧 training@vizacta.com
Course Description
This course is designed for data analysts, BI developers, data engineers, and administrators who need to understand not just how to build reports, but how to operate and govern Power BI in the real world. You’ll learn how to structure environments using Dev/Test/Prod workspaces, publish and manage Power BI Apps, secure data with Row-Level Security, create shared and certified datasets, and manage user access via Azure AD groups.
We’ll also cover key enterprise topics such as deployment pipelines, monitoring refreshes and usage, automating tasks via PowerShell and REST APIs, and hybrid connectivity using the on-premises data gateway.
The course includes hands-on labs, templates, checklists, and a capstone project that simulates a full enterprise rollout from development to production.
What You Will Learn
- How to structure Power BI Workspaces for Dev, Test, and Production environments
- Best practices for managing apps, sharing content, and distributing reports
- How to share datasets across workspaces and promote certified datasets
- Implementing Row-Level Security (RLS) using Azure AD groups
- Managing access and permissions across large user groups
- Installing and configuring the on-premises data gateway
- Using the Power BI Admin Portal for tenant-wide governance
- Monitoring usage, auditing activity, and managing refresh schedules
- Automating tasks using PowerShell and the Power BI REST API
- Deploying a complete enterprise BI project using real-world scenarios
Course Content
- Introduction to the Power BI ecosystem
- Differences between Power BI Desktop and Power BI Service
- Roles: Developer, Business User, Administrator
- Power BI Licensing: Free, Pro, PPU, Premium
- Overview of Power BI Architecture
- Importance of multi-environment architecture
- Setting up Dev → Test → Prod workspace structure
- Using Deployment Pipelines: step-by-step
- Managing content promotion and versioning
- Governance and approval roles across environments
- Lab: Create and manage a deployment pipeline
- Workspace types and use cases (team vs department)
- Managing workspace roles and permissions
- Creating and sharing Power BI Apps
- Best practices for navigation and version updates
- Lab: Build and share a departmental app
- Certified and Promoted datasets: definition and use
- Creating and managing Linked Datasets
- Centralized data model strategy for organizations
- Dataset ownership and permission management
- Lab: Publish a certified dataset for reuse
- Managing access with Azure AD security groups
- Assigning workspace/report/app permissions
- Applying RLS with Azure AD groups
- Controlling access with roles vs user mapping
- Lab: Implement RLS with group-based security
- Overview of on-premises data gateway architecture
- Differences: Personal vs Enterprise gateway
- Installation and configuration walkthrough
- Managing gateway clusters and data sources
- Troubleshooting gateway connection issues
- Lab: Connect to on-prem SQL Server using a gateway
- Power BI Admin portal overview
- Tenant settings: export, sharing, publish-to-web controls
- Monitoring capacity and performance settings
- Using audit logs and activity reports
- Lab: Configure tenant policies and review usage data
- Using PowerShell and REST API for automation
- Automating workspace creation and dataset updates
- Monitoring scheduled refreshes and failures
- Integrating Power BI with Azure services (Log Analytics, etc.)
- Lab: Automate dataset refresh and monitor logs via API
- End-to-end BI solution deployment: Dev → Test → Prod
- Share centralized dataset across teams
- Implement security and access with AD + RLS
- Connect via gateway to hybrid data source
- Monitor and document refresh history and performance
- Deliverable: Architecture diagram and deployment workbook