POWERBI EMBEDDED ANALYTICS

Power BI Embedded Analytics

Course Overview:

In this course, you will learn how to programmatically embed Power BI content by using

the Power BI REST API and the Power BI client APIs, enforce row-level security (RLS) for

embedded content, automate common Power BI setup tasks, configure a development

environment, and determine appropriate licensing. Microsoft Power BI is a leading data

analytics service. Today, many people are familiar with Power BI because they interact

with reports in the Power BI service or Power BI mobile apps. The great news for

developers is that any type of Power BI content can be programmatically embedded in

their apps.

Course Objectives:

In this module, you will:

• Select the appropriate embedding scenario.
• Select the appropriate Power BI embedded analytics product.
• Manage resource and scale requirements.
• Set up a development environment.

Course Outline:

Introduction

• What is Power BI embedded analytics?
•  Power BI Embedded features
•  What is the Power BI Embedded analytics playground?
•  Power BI Embedded Setup
•  Create an Azure Active Directory tenant
•  Power BI app registration tool
•  Configure credentials
•  Edit your app permissions
•  Auto-install apps
•  Performance best practices
•  Monitor Power BI Embedded apps

Embed content

•  Embed using a service principal
•  Embed using service principal and a certificate Embed content for customers
•  Embed content for your organization
•  Embed content for national clouds
•  Embed a report in an app for your customers Embed a report in an app for your

organization

•  Embed a paginated report
•  Embed in Salesforce
•  Embedding Q&A
•  Secure embed

Integrate content with Power BI client APIs

Introduction

•  Go from insights to quick action
•  Personalize top insights
•  Customize report theme
•  Capture report views
•  Create personalized visuals

Tokens

•  Embedded analytics access tokens
•  Generating an embed token
•  Connect a report using dynamic binding

Export to file

•  Export report to file
•  Export paginated report to file

Capacities and SKUs

•  Move an embedded app to production
•  Capacity and SKUs in Power BI embedded analytics Capacity planning
•  Create a capacity in Azure
•  Create a capacity using Multi-Geo in Azure
•  Assess the capacity load
•  Scale a capacity in Azure
•  Pause and start a capacity in Azure
• Workspace separation and multitenancy
•  Service principal profiles for multitenancy apps
•  Power BI SDK and service principal profiles
•  Migrate to the service principal profiles model

Security

•  Embedding security features
•  Embed with cloud-based RLS
•  RLS in embedded paginated reports
•  Embed with on-premises SQL Server Analysis Services (SSAS)
•  Embed with Azure Analysis Services (AAS)
•  Embed with object-level security (OLS)
•  Support
•  Troubleshoot your embedded application
•  Troubleshoot REST APIs
•  Reference APIs
•  Azure Resource Management REST APIs
•  Power BI REST APIs
•  Push datasets limitations
•  Datasets permissions
•  Monitor Power BI Embedded data reference
•  Power BI libraries
•  Azure CLI
•  Power BI glossary

Resources

•  Power BI Dev Camp
•  Developer center
•  Embedding setup tool
•  Embedded analytics playground
•  Power BI embedded analytics Client APIs
•  Developer samples and scripts
•  Power BI community
•  Stack Overflow
• Enforce data permissions for Power BI embedded analytics
•  Introduction
•  Set up row-level security
•  Determine the type of Power BI dataset
•  Set effective identity
•  Apply good development practices
• Automate Power BI solution management
•  Introduction
•  Automate workspace separation3 min

Prerequisites:

• You should be an experienced app developer. It's an advantage if you have

development experience with .NET, Visual C#, HTML, and JavaScript. Familiarity

with Power BI is beneficial, but not essential.

• Basic understanding of Power BI embedded analytics and the types of Power BI

content that can be embedded in apps.

Who Can attend:

• Developers
• AI Engineer
• App Maker
• Business User
• Data Analyst
• Data Engineer
• Data Scientist