Microsoft Power Platform — Technical Architecture, Components and Enterprise Use Cases
1. Introduction
Microsoft Power Platform is Microsoft’s low-code platform for building business applications, automating processes, analyzing data, creating external business websites, and developing AI-powered agents.
From an architectural perspective, Power Platform should not be understood as a single application.
It is an ecosystem of technologies that can be used independently or combined to create end-to-end enterprise solutions.
Microsoft currently identifies five primary product areas:
| Product | Primary responsibility |
|---|---|
| Power Apps | Business applications |
| Power Automate | Process automation |
| Power BI | Analytics and business intelligence |
| Power Pages | External-facing business websites |
| Copilot Studio | Agents and agent flows |
Microsoft Dataverse provides a common enterprise data platform that can support these technologies, although using Power Platform does not automatically mean every solution must use Dataverse.
Microsoft describes Power Platform as a low-code platform for rapidly creating end-to-end business solutions, with the individual product areas capable of working separately or together.
A useful first mental model is:
Business Problem
↓
Microsoft Power Platform
↓
Power Apps → Applications
Power Automate → Automation
Power BI → Analytics
Power Pages → External Websites
Copilot Studio → Agents
↓
Dataverse / SharePoint / SQL / APIs / Microsoft 365 / External Systems
This distinction is fundamental.
Power Platform is not simply a collection of visual development tools.
It is an enterprise application and integration platform.
2. Power Platform from an Architectural Perspective
A real Power Platform solution frequently crosses several layers.
Consider an employee training system.
The organization could use:
Power Apps
to provide an application where employees request training.
Dataverse
to store structured training requests.
Power Automate
to execute the approval process.
Outlook or Teams
to notify managers.
Power BI
to analyze training costs and certification completion.
Power Pages
to expose selected training information to external partners.
And eventually:
Copilot Studio
to allow employees to interact with the system through natural language.
The architecture might therefore look like:
Employee
↓
Power Apps
↓
Dataverse
↓
Power Automate
↓
Manager Approval
↓
Dataverse
↓
Power BI
And independently:
Employee
↓
Copilot Studio Agent
↓
Knowledge / Tools
↓
Dataverse / SharePoint / Power Automate
The important architectural principle is:
Each component should have a clear responsibility.
3. Power Apps
3.1 What Power Apps Is
Power Apps is the application-development component of Power Platform.
Microsoft defines Power Apps as a suite of apps, services, connectors and data capabilities that provides a rapid development environment for creating custom business applications.
Power Apps applications can connect to Microsoft Dataverse as well as other data sources such as SharePoint, Microsoft 365, Dynamics 365 and SQL Server.
The fundamental architecture is:
User
↓
Power App
↓
Business Logic
↓
Connector
↓
Data Source
The data source might be:
SharePoint
Dataverse
SQL Server
Excel
Microsoft 365
Dynamics 365
REST API through a Custom Connector
or another supported service.
4. The Two Major Power Apps Models
Power Apps primarily provides two important application models:
| Type | Architecture | Best suited for |
|---|---|---|
| Canvas App | UI-first | Highly customized user experiences |
| Model-driven App | Data-model-first | Dataverse-centric enterprise applications |
Understanding this distinction is extremely important.
5. Canvas Apps
Canvas Apps provide substantial control over the application’s user interface.
The maker designs screens, controls, navigation and interaction.
Conceptually:
Canvas
↓
Screens
↓
Controls
↓
Power Fx
↓
Connectors
↓
Data
For example, imagine a SharePoint list:
TrainingRequests
with columns:
Title
Employee
Course
Provider
Cost
Manager
Status
We could build a Canvas App providing:
My Requests
New Request
Request Details
Manager Approval
Search
Filters
The architecture could remain very simple:
Employee
↓
Canvas App
↓
SharePoint Connector
↓
SharePoint List
This is an important example because Dataverse is not automatically necessary.
If the application is relatively simple and SharePoint already provides an adequate data model, permissions and lifecycle, introducing Dataverse might add unnecessary complexity.
6. Power Fx
Canvas Apps use Power Fx extensively.
Power Fx is the formula language used across parts of Power Platform.
Its syntax is intentionally similar to spreadsheet formulas.
Conceptually:
Control
↓
Power Fx expression
↓
Business behavior
For example:
Filter(TrainingRequests, Status.Value = "Pending")
could conceptually retrieve pending requests.
Or:
SubmitForm(frmTrainingRequest)
could submit a form.
For a developer familiar with TypeScript or C#, an important mental shift is that Power Fx is primarily a declarative formula language, rather than a conventional imperative programming language.
7. Model-Driven Apps
Model-driven Apps approach application development from the opposite direction.
Instead of beginning with:
What should the screen look like?
we begin primarily with:
What is the business data model?
The architecture is strongly associated with Dataverse:
Dataverse
↓
Tables
↓
Columns
↓
Relationships
↓
Forms
↓
Views
↓
Business Processes
↓
Model-driven App
Suppose we have:
Customer
↓
Training Contract
↓
Training Request
↓
Course
↓
Instructor
↓
Certification
A model-driven application can use this relational business model to automatically provide structured forms, views, navigation and enterprise data experiences.
This is especially valuable for CRM-like and process-centric applications.
8. Canvas vs Model-Driven
| Requirement | Canvas | Model-driven |
|---|---|---|
| Highly customized UI | Excellent | More constrained |
| Dataverse required | No | Yes |
| SharePoint as primary source | Common | No |
| Relational enterprise data | Possible | Excellent |
| Rapid CRUD application | Good | Excellent |
| Pixel-level UI control | Excellent | Limited |
| Complex data relationships | Possible | Excellent |
| Business-process-oriented application | Good | Excellent |
| Mobile business app | Excellent | Good |
Neither is inherently superior.
They solve different problems.
9. Microsoft Dataverse
9.1 What Dataverse Is
Dataverse is Microsoft’s cloud-based business data platform used extensively throughout Power Platform and Dynamics 365.
Microsoft describes Dataverse as a platform for securely storing and managing data used by business applications. Data is organized into tables containing rows and columns.
A simplified model is:
Dataverse
↓
Tables
↓
Rows
↓
Columns
But that description is incomplete.
Dataverse also provides:
Relationships
Metadata
Security
Business rules
Validation
APIs
Auditing
Solutions
Integration capabilities
Enterprise application services
This makes Dataverse considerably more than a simple cloud database.
10. Dataverse Data Model
Imagine:
Employee
Department
TrainingRequest
Course
Provider
Relationships could include:
Department
1
↓
N
Employee
Employee
1
↓
N
TrainingRequest
Course
1
↓
N
TrainingRequest
Provider
1
↓
N
Course
This is a genuine relational business model.
Dataverse also provides standard tables for common enterprise concepts, while allowing organizations to create custom tables. Microsoft also provides role-based security and metadata capabilities directly within the platform.
11. Dataverse vs SharePoint
This is one of the most important architectural decisions for Microsoft 365 developers.
| Requirement | SharePoint | Dataverse |
|---|---|---|
| Document management | Excellent | Limited |
| Lists / lightweight data | Excellent | Excellent |
| Simple departmental applications | Excellent | Excellent |
| Complex relational model | Limited | Excellent |
| Enterprise row-level security | Limited architecture | Excellent |
| Model-driven Apps | No | Native |
| Dynamics 365 | No | Foundation |
| Business rules | Limited | Rich |
| Document libraries | Native | Not primary purpose |
| Power Platform enterprise data | Good | Native |
| Existing M365 content | Excellent | Requires architecture/migration |
| Complex enterprise business application | Possible | Usually stronger |
The architectural rule should never be:
“It is Power Platform, therefore use Dataverse.”
The correct question is:
“What data platform best satisfies this business requirement?”
For a corporate document library:
SharePoint is normally the natural solution.
For a sophisticated relational business application with strong security and lifecycle requirements:
Dataverse may be more appropriate.
12. Power Automate
Power Automate is the process automation component of Power Platform.
Its responsibility is fundamentally different from Power Apps.
Power Apps answers:
How does the user interact with the business application?
Power Automate answers:
What process should execute when something happens?
Conceptually:
Trigger
↓
Workflow
↓
Conditions
↓
Actions
↓
Result
Power Automate supports cloud automation and broader automation scenarios including RPA capabilities. Microsoft positions it as the automation layer for repetitive and business-process tasks integrated with Microsoft 365 and Power Platform.
13. Example — SharePoint Approval
Suppose a user creates:
Training Request #145
with:
Course = Copilot Studio Training
Cost = $1,200
Manager = John Smith
Status = Pending
The architecture could be:
SharePoint
↓
Item Created
↓
Power Automate
↓
Get Manager
↓
Start Approval
↓
Approved?
↙ ↘
Yes No
↓ ↓
Update Update
Approved Rejected
↓
Notify Employee
No AI is required.
This is an important architectural lesson.
A deterministic business process should normally remain deterministic.
14. Power Automate Trigger and Action Model
A Flow generally begins with a Trigger.
Examples:
When a SharePoint item is created
When an email arrives
When a Dataverse row is modified
When a Forms response is submitted
Recurrence
Manual trigger
HTTP request
The Flow then executes Actions.
For example:
Trigger
When an item is created
↓
Action
Get item
↓
Condition
↓
Action
Start and wait for an approval
↓
Action
Update item
↓
Action
Send an email
This Trigger → Action model is fundamental to Power Automate.
15. Power Automate vs Agent
This distinction will become extremely important when we later return to Copilot Studio.
Power Automate:
IF
Status = Approved
THEN
Send Email
This is deterministic automation.
An Agent might instead need to:
Read an unstructured request
↓
Understand intent
↓
Retrieve relevant policy
↓
Interpret context
↓
Determine which Tool is appropriate
↓
Call an operation
The first problem is workflow automation.
The second potentially benefits from AI reasoning.
We should not replace predictable business rules with LLM decisions simply because AI is available.
16. Connectors
Connectors are one of the architectural foundations of Power Platform.
A Connector provides an integration abstraction between Power Platform and another service.
Conceptually:
Power App / Flow / Agent
↓
Connector
↓
Service API
Examples include:
SharePoint
Outlook
Teams
SQL Server
Salesforce
Dataverse
OneDrive
Azure services
and many others.
Microsoft currently distinguishes two broad connector types:
Prebuilt Connectors
and
Custom Connectors.
17. Prebuilt Connector
Suppose Power Automate needs to create a SharePoint item.
Instead of manually implementing:
OAuth
HTTP
REST endpoint
JSON serialization
Error parsing
token management
the Flow can use the SharePoint Connector:
Power Automate
↓
SharePoint Connector
↓
Create item
↓
SharePoint Online
The Connector abstracts much of the underlying integration complexity.
18. Custom Connector
Suppose the company owns an internal API:
api.contoso.com/training
but no standard connector exists.
We can create a Custom Connector exposing operations such as:
GetCourses
GetCourse
CreateTrainingRequest
GetTrainingStatus
Conceptually:
Power Apps
or
Power Automate
or
Copilot Studio
↓
Custom Connector
↓
REST API
↓
Corporate System
This creates a reusable integration contract inside the Power Platform ecosystem.
Microsoft’s connector architecture currently makes connectors available across Power Apps, Power Automate, Copilot Studio and Azure Logic Apps, depending on connector support and scenario.
19. Power Pages
Power Pages addresses another problem entirely:
external-facing business websites.
Microsoft describes Power Pages as a secure, enterprise-grade low-code SaaS platform for building, hosting and administering external-facing business websites. It integrates particularly closely with Dataverse.
Conceptually:
Internet User
↓
Power Pages
↓
Authentication / Authorization
↓
Dataverse
↓
Business Data
This differs significantly from Power Apps.
20. Example — Supplier Portal
Suppose Contoso wants suppliers to manage registrations.
External Supplier
↓
Power Pages
↓
Login
↓
Supplier Profile
↓
Dataverse
↓
Supplier Registration
↓
Power Automate
↓
Internal Approval
↓
Notification
The external supplier does not need access to an internal Canvas App.
Power Pages provides the external web experience.
21. Power Apps vs Power Pages
| Scenario | Power Apps | Power Pages |
|---|---|---|
| Internal employees | Excellent | Possible but generally not primary purpose |
| External customers | Limited scenario | Primary scenario |
| Anonymous website | No | Yes, where configured appropriately |
| Dataverse integration | Excellent | Core architecture |
| Custom business application | Yes | Web portal |
| Public/extranet portal | Not primary use | Yes |
A common architectural simplification is:
Power Apps → business applications
Power Pages → external business websites
22. Power BI
Power BI is the analytics and business-intelligence component of the ecosystem.
Microsoft describes Power BI as its business analytics platform for transforming data into actionable insights. Power BI now also operates as a major component of Microsoft Fabric.
Its responsibility is not primarily transactional.
Power Apps:
enter/change data
Power Automate:
process data
Power BI:
analyze data
Conceptually:
Multiple Data Sources
↓
Power Query
↓
Data Transformation
↓
Semantic Model
↓
DAX
↓
Reports
↓
Dashboards
↓
Business Decisions
23. Example — Training Analytics
Our training system may contain:
5,000 requests
20 departments
120 courses
40 providers
$2 million annual spending
Power BI could produce:
Training Cost by Department
Certification Completion
Approval Time
Most Requested Courses
Training Spend by Provider
Budget vs Actual
Architecture:
SharePoint / Dataverse / SQL
↓
Power BI
↓
Data Model
↓
DAX Measures
↓
Reports
↓
Managers
Power BI Desktop is primarily used for data modeling and report development, while the Power BI service provides cloud publication, sharing and collaboration.
24. AI Builder
AI Builder introduces AI capabilities into Power Platform without requiring the organization to develop every AI model from scratch.
Microsoft describes AI Builder as a Power Platform capability for creating and using AI models in business processes, integrated particularly with Power Apps and Power Automate.
AI Builder supports scenarios such as:
document processing
invoice processing
text recognition
sentiment analysis
entity extraction
ID reading
category classification
language detection
and other AI capabilities.
25. Example — Invoice Processing
Consider:
Supplier
↓
Invoice PDF
↓
SharePoint
↓
Power Automate
↓
AI Builder
↓
Invoice Processing
↓
Extract:
Invoice Number
Supplier
Date
Amount
Tax
↓
Dataverse
↓
Approval
↓
Power BI
This is a powerful example because each component has a distinct responsibility.
SharePoint:
Document storage
Power Automate:
Orchestration
AI Builder:
Information extraction
Dataverse:
Structured business data
Power BI:
Analytics
No component needs to pretend to be all the others.
26. AI Builder vs Copilot Studio
These technologies both involve AI, but their responsibilities differ.
AI Builder typically solves problems such as:
“Extract the invoice number from this document.”
Copilot Studio solves more agent-oriented problems such as:
“Understand what the user wants, retrieve appropriate knowledge and decide which available capability should be used.”
We will explore this distinction much more deeply when we move to Copilot Studio.
27. Environments
Power Platform introduces another fundamental concept:
Environment
An Environment is a logical container used to store and manage business applications, data, flows and other Power Platform resources.
Microsoft specifically describes environments as containers that can separate applications based on roles, security requirements or target audiences.
Conceptually:
Microsoft 365 Tenant
↓
Power Platform
↓
DEV Environment
↓
TEST Environment
↓
PROD Environment
This provides separation between development and production workloads.
28. Environment Architecture
A mature enterprise architecture might use:
DEV
↓
Solution Development
↓
TEST
↓
Integration Testing
↓
UAT
↓
User Acceptance
↓
PROD
↓
Production
Each Environment can have its own:
Dataverse
Apps
Flows
Connections
Security
Environment Variables
Solutions
Agents
configuration.
Microsoft currently specifies that each environment can contain one Dataverse database.
29. Solutions
Solutions are one of the foundations of Power Platform Application Lifecycle Management.
Instead of manually recreating components in another Environment, related components can be organized within a Solution.
For example:
TrainingManagementSolution
could contain:
Canvas App
Model-driven App
Dataverse Tables
Power Automate Flows
Environment Variables
Connection References
Copilot Studio components
Other solution-aware components
Conceptually:
DEV
↓
Solution
↓
Export / Pipeline
↓
TEST
↓
Solution
↓
PROD
This is much closer to professional software engineering than simply creating random applications inside the Default Environment.
30. ALM — Application Lifecycle Management
Microsoft explicitly applies ALM concepts to Power Apps, Power Automate, Power Pages, Copilot Studio and Dataverse.
A mature lifecycle is:
Plan
↓
Develop
↓
Build
↓
Test
↓
Deploy
↓
Operate
↓
Monitor
↓
Improve
Power Platform ALM can involve:
Environments
Solutions
Source Control
Environment Variables
Connection References
Pipelines
Azure DevOps
GitHub
Power Platform CLI
automated deployments.
This is the point where Power Platform stops looking like merely a citizen-development tool and begins looking like an enterprise application platform.
31. Power Platform Admin Center
Enterprise Power Platform requires administration.
The Power Platform admin center provides centralized management capabilities for areas including environments, security, Copilot, monitoring, deployments, licensing and support.
An administrator therefore operates at another architectural layer:
Tenant
↓
Power Platform Admin Center
↓
Environments
↓
Security
↓
Governance
↓
Capacity
↓
Applications / Flows / Agents
↓
Monitoring
This administrative layer should be designed from the beginning in enterprise implementations.
32. Data Policies and Governance
Suppose an organization allows:
SharePoint
Dataverse
SQL Server
but wants to prevent corporate information from being accidentally transferred into inappropriate consumer services.
Power Platform governance can use Data Policies to control how connectors participate in data movement.
Microsoft explicitly describes data policies as mechanisms controlling which connectors data can be shared with, helping prevent business information from being accidentally published through inappropriate connectors.
Conceptually:
Business Data
↓
Power Platform
↓
Data Policy
↓
Allowed Connector
or
↓
Blocked combination
This becomes essential in enterprise Power Platform governance.
33. Low-Code Does Not Mean No Architecture
This is perhaps the most important architectural principle in this article.
Power Platform allows solutions to be created rapidly.
That does not remove the need for:
Architecture
Security
Data modeling
Integration design
Error handling
Testing
ALM
Governance
Monitoring
Capacity planning
Licensing analysis
A badly designed Power Platform application is still a badly designed application.
Low-code reduces implementation friction.
It does not eliminate software-engineering principles.
34. The Role of Professional Developers
Power Platform is sometimes incorrectly described as a platform only for citizen developers.
Microsoft explicitly supports professional developer extensibility. Power Apps, for example, allows developers to interact programmatically with data and metadata, implement business logic, create custom connectors and integrate external data.
A professional developer can participate through:
REST APIs
Custom Connectors
PCF — Power Apps Component Framework
JavaScript
TypeScript
C#
Dataverse Web API
Power Platform CLI
Azure DevOps
GitHub
Azure Functions
Microsoft Graph
Azure services
custom APIs.
Therefore, the real architecture is often:
Low-Code
Pro-Code
rather than:
Low-Code
versus
Pro-Code.
35. Power Platform and SharePoint
For a Microsoft 365 architecture, SharePoint remains extremely important.
SharePoint can provide:
Documents
Lists
Pages
Sites
Permissions
Collaboration
Intranet
Enterprise Content
while Power Platform can extend those capabilities.
For example:
SharePoint List
↓
Power Apps
Custom UI
↓
Power Automate
Business Process
↓
Power BI
Analytics
And later:
SharePoint Documents
↓
Copilot Studio
Knowledge / Grounding
This is why SharePoint should not automatically be replaced by Dataverse merely because Power Platform is being introduced.
36. A Complete Enterprise Example
Consider an organization implementing an:
Employee Training Management Platform
User Interface
Power Apps
↓
Employee submits training request
Data
Dataverse
↓
TrainingRequest
Employee
Course
Provider
Certification
Documents
SharePoint
↓
Course Material
Certificates
Training Policies
Invoices
Process
Power Automate
↓
Manager Approval
↓
Finance Approval
↓
Notifications
AI Processing
AI Builder
↓
Extract information from certificates/invoices
Analytics
Power BI
↓
Training Spending
Certification Status
Department Performance
External Access
Power Pages
↓
External training provider portal
Agent
Copilot Studio
↓
Employee:
“What training am I eligible for?”
or:
“Create a Copilot Studio training request.”
Now we have a true Power Platform architecture.
37. Responsibility Matrix
| Technology | Primary question |
|---|---|
| Power Apps | What application should the user interact with? |
| Power Automate | What process should execute? |
| Dataverse | Where should structured enterprise business data live? |
| Power Pages | How should external users interact with the business system? |
| Power BI | What does the data tell us? |
| AI Builder | Can AI extract/classify/predict information in this process? |
| Connectors | How does Power Platform communicate with another system? |
| Solutions | How do components move through their lifecycle? |
| Environments | Where are workloads isolated and managed? |
| Power Platform Admin Center | How is the platform governed and administered? |
| Copilot Studio | How can Agents reason, converse, retrieve Knowledge and use Tools? |
38. Choosing the Correct Tool
A mature architect should begin with the requirement rather than the technology.
| Requirement | Likely starting point |
|---|---|
| Custom employee application | Power Apps |
| Automated approval | Power Automate |
| Enterprise relational business data | Dataverse |
| Existing M365 documents | SharePoint |
| External customer/supplier portal | Power Pages |
| Analytics/dashboard | Power BI |
| Document AI extraction | AI Builder |
| Integration with SaaS | Connector |
| Integration with unsupported REST API | Custom Connector / API |
| Conversational AI Agent | Copilot Studio |
| Simple deterministic form | Power Apps / SharePoint |
| Simple deterministic workflow | Power Automate |
| Complex custom M365 UX | Possibly SPFx |
| Advanced unsupported integration | API / Azure / custom development |
The most important line in this table is effectively the one that is not written:
Sometimes the correct answer is not AI.
39. The Complete Power Platform Mental Model
A useful final architecture is:
Users
↓
┌──────────────────────────────────────────┐
│ EXPERIENCE LAYER │
│ │
│ Power Apps │ Power Pages │ Copilot Studio│
└──────────────────────────────────────────┘
↓
┌──────────────────────────────────────────┐
│ PROCESS LAYER │
│ │
│ Power Automate │ Agent Flows │
└──────────────────────────────────────────┘
↓
┌──────────────────────────────────────────┐
│ AI LAYER │
│ │
│ AI Builder │ Copilot / Agents │
└──────────────────────────────────────────┘
↓
┌──────────────────────────────────────────┐
│ INTEGRATION LAYER │
│ │
│ Connectors │ Custom Connectors │ APIs │
└──────────────────────────────────────────┘
↓
┌──────────────────────────────────────────┐
│ DATA LAYER │
│ │
│ Dataverse │ SharePoint │ SQL │ APIs │
└──────────────────────────────────────────┘
↓
┌──────────────────────────────────────────┐
│ ANALYTICS LAYER │
│ │
│ Power BI │
└──────────────────────────────────────────┘
And surrounding everything:
Environments
Solutions
Security
Governance
ALM
Monitoring
Licensing
This is a much better mental model than seeing Power Platform as five unrelated products.
40. Final Technical Summary
| Component | Category | Main responsibility | Typical example |
|---|---|---|---|
| Power Apps | Application | Build business applications | Training request app |
| Canvas App | Application | Custom UX | Mobile inspection app |
| Model-driven App | Application | Data/process-centric application | CRM application |
| Power Automate | Automation | Workflow/process automation | Approval process |
| Dataverse | Data | Enterprise business data | Customers/orders/requests |
| Power Pages | Web | External business portal | Supplier portal |
| Power BI | Analytics | BI and reporting | Executive dashboard |
| AI Builder | AI | AI inside apps/processes | Invoice extraction |
| Connector | Integration | Connect services | SharePoint Connector |
| Custom Connector | Integration | Expose custom API | Internal ERP API |
| Environment | Platform | Workload isolation | DEV / TEST / PROD |
| Solution | ALM | Package application components | Training Solution |
| Power Platform Admin Center | Administration | Governance and operations | Environment management |
| Copilot Studio | Agent platform | Build and orchestrate Agents | Corporate Policy Agent |
41. Conclusion
Microsoft Power Platform is best understood as an integrated enterprise solution platform rather than a collection of independent low-code products.
Its technologies solve different architectural problems.
Power Apps builds applications.
Power Automate executes processes.
Dataverse manages structured enterprise business data.
Power Pages exposes business capabilities externally.
Power BI analyzes information.
AI Builder introduces specialized AI capabilities into applications and workflows.
Connectors integrate systems.
Environments and Solutions provide isolation and lifecycle management.
Power Platform Admin Center provides administration and governance.
And finally:
Copilot Studio introduces the Agent layer.
The critical architectural principle is therefore not:
“How can I use every Power Platform technology in this solution?”
It is:
“Which Power Platform capabilities are actually necessary to solve this business problem securely, predictably and economically?”
Only after answering that question should technologies be selected.
That distinction becomes even more important when Copilot Studio and generative AI enter the architecture, because an Agent should not replace deterministic applications, workflows or business rules when those technologies already solve the requirement more safely and efficiently.
Our next conceptual layer can therefore focus specifically on:
Microsoft Copilot Studio inside Power Platform
and answer:
What changes when we add an Agent to this architecture?
Official Microsoft References
Microsoft Learn — Power Platform for developers
Introduction to Microsoft Power Platform for developers
Microsoft Learn — Power Apps
What is Power Apps?
Microsoft Learn — Dataverse
What is Microsoft Dataverse?
Microsoft Learn — Power Pages
What is Power Pages?
Microsoft Learn — Power BI
What is Power BI?
Microsoft Learn — AI Builder
AI Builder overview
Microsoft Learn — Connectors
Connectors overview
Microsoft Learn — Power Platform Environments
Power Platform environments overview
Microsoft Learn — Application Lifecycle Management
ALM with Microsoft Power Platform
Microsoft Learn — Power Platform Admin Center
Power Platform admin center overview
