Business Professionals
Power BI | Power Pivot | Power Query | DAX
Cloud Flows | RPA | AI Builder | Copilot
60+ Formulas | Data Stories | Advanced Reporting & Modeling
VB Programming | Report Automation |
MS-Office Automation
Techno-Business Professionals
Power BI | Power Query | Advanced DAX | SQL - Query &
Programming
Microsoft Fabric | Power BI | Power Query | Advanced DAX |
SQL - Query & Programming
Power BI | Power Apps | Power Automate | Copilot Studio | Power Pages | Dataverse
Microsoft Power Apps | Microsoft Power Automate
Power BI | Adv. DAX | SQL (Query & Programming) |
VBA | Python | Web Scrapping | API Integration
Power BI | Power Apps | Power Automate |
SQL (Query & Programming)
Power BI | Adv. DAX | Power Apps | Power Automate |
SQL (Query & Programming) | VBA | Python | Web Scrapping | API Integration
Power Apps | Power Automate | SQL | VBA | Python |
Web Scraping | RPA | API Integration
Technology Professionals
Power BI | DAX | SQL | ETL with SSIS | SSAS | VBA | Python
Power BI | SQL | Azure Data Lake | Synapse Analytics |
Data Factory | Databricks | Power Apps | Power Automate |
Azure Analysis Services
Microsoft Fabric | Power BI | SQL | Lakehouse |
Data Factory (Pipelines) | Dataflows Gen2 | KQL | Delta Tables | Power Apps | Power Automate
Power BI | Power Apps | Power Automate | SQL | VBA | Python | API Integration
Power BI | Advanced DAX | Databricks | SQL | Lakehouse Architecture
Business Professionals
Power BI | Power Pivot | Power Query | DAX
Cloud Flows | RPA | AI Builder | Copilot
60+ Formulas | Data Stories | Advanced Reporting & Modeling
VB Programming | Report Automation |
MS-Office Automation
Techno-Business Professionals
Power BI | Power Query | Advanced DAX | SQL - Query &
Programming
Microsoft Fabric | Power BI | Power Query | Advanced DAX |
SQL - Query & Programming
Power BI | Power Apps | Power Automate | Copilot Studio | Power Pages | Dataverse
Microsoft Power Apps | Microsoft Power Automate
Power BI | Adv. DAX | SQL (Query & Programming) |
VBA | Web Scrapping | API Integration
Power BI | Power Apps | Power Automate |
SQL (Query & Programming)
Power BI | Adv. DAX | Power Apps | Power Automate |
SQL (Query & Programming) | VBA | Web Scrapping | API Integration
Power Apps | Power Automate | SQL | VBA |
Web Scraping | RPA | API Integration
Technology Professionals
Power BI | DAX | SQL | ETL with SSIS | SSAS | VBA
Power BI | SQL | Azure Data Lake | Synapse Analytics |
Data Factory | Azure Analysis Services
Microsoft Fabric | Power BI | SQL | Lakehouse |
Data Factory (Pipelines) | Dataflows Gen2 | KQL | Delta Tables
Power BI | Power Apps | Power Automate | SQL | VBA | API Integration
Power BI | Advanced DAX | Databricks | SQL | Lakehouse Architecture
LEARN THIS HANDS ON
Power Apps & Power Automate
Most teams discover Power Automate privacy issues the hard way: an audit, a DPIA, or a security review that suddenly reveals flows pushing HR data into a personal OneDrive or forwarding customer tickets to someone's Gmail. You get a vague "Power Automate GDPR" question from the privacy officer, and realise you don't actually know where all those flows send personal data.
This article walks through a realistic scenario and shows how to design privacy‑friendly flows under the Dutch AVG / European GDPR, how to spot risky patterns (personal OneDrive, Gmail, random SaaS connectors), and how to fix them without killing automation.
Imagine an HR team using Microsoft 365 and Power Automate:
Data involved:
The privacy officer asks a simple question: “Which flows copy personal data outside our tenant, and under what legal basis?”
You realise:
Let’s clean this up systematically.
Before you fix anything, you need to know which flows touch personal data and where they send it.
Walk through the HR scenario and identify:
Under AVG/GDPR, the risk is mainly in:
As of late 2026, the practical ways to see where data flows in Power Automate are:
Power Automate portal (per environment)
Solutions (Dataverse environments)
You’re looking specifically for:
Document each flow:
This gives you a concrete list of flows that need privacy hardening.
Power Automate itself doesn’t “know” about AVG. It just executes connectors with whatever data you pass. The risk comes from how you design flows and which connections you use.
For the HR scenario, the main patterns to watch:
Risky patterns:
Privacy‑friendly alternatives:
Any connector that sends data to a third‑party service is a potential data transfer:
For AVG/GDPR:
Each connector action runs under a connection created by a user or service principal.
Risks:
Better:
Now we redesign the HR flow to keep personal data inside the tenant and under control.
Current risky step:
Safer design:
Example structure:
HR-Requests.SensitiveRequests with restricted permissions.Flow change (conceptual):
HR-Requests SharePoint list with metadata.SensitiveRequests library for attachments.No code is needed here, but the key is:
Current risky step:
Safer alternatives:
hr@company.nl).hr-team@company.nl).Design:
Example email body (conceptual):
New HR request: @{triggerOutputs()?['body/employeeName']}A new HR request has been submitted. View details: <SharePoint item link>This keeps personal data within Exchange Online and SharePoint, which are already under your organisation’s control and policies.
If HR really needs to push data into a third‑party helpdesk:
Flow pattern:
This satisfies the operational need while reducing the volume of personal data leaving your environment.
Designing one flow correctly is not enough. You need guardrails so future flows don’t reintroduce the same AVG/GDPR issues.
Use Power Platform environments to separate sensitive flows:
Benefits:
In the Power Platform admin center, define DLP policies that classify connectors:
For the HR environment:
Effect:
This is one of the most effective technical controls for Power Automate privacy.
In solutions:
Benefits:
Even inside your tenant, AVG/GDPR expects data minimisation.
For the HR flow:
Common anti‑pattern:
Better:
Example pattern:
If some HR requests are more sensitive (e.g. health‑related):
SensitiveRequests library, notify only senior HR.This keeps sensitive data away from broader channels while using the same core flow.
AVG/GDPR also cares about not keeping data forever.
Pattern:
Design points:
This keeps retention under control without manual clean‑up.
Technical controls work best when the HR team understands them.
For the HR scenario:
This turns privacy from a one‑off project into a normal part of how you design automation.
Next time someone mentions "Power Automate privacy" or "Power Automate GDPR", don’t start with theory. Start by listing flows that touch personal data, check where they send it, and lock down personal and external destinations with environments and DLP. If you can keep HR‑style flows inside shared Microsoft 365 resources, minimise what leaves the tenant, and centralise connections, you’ve already eliminated most of the silent AVG/GDPR risks in your automation.
This article reflects how teams using Power Automate for HR and other sensitive workflows are tightening connector choices, environments, and data minimisation to keep personal data inside organisational boundaries under AVG/GDPR.
Professionals who want to apply these patterns to their own data can explore Excelgoodies' Power Apps & Power Automate programme - taught live by instructors, with certification awarded once a real project is running at work.
Insights compiled through ongoing industry research and discussions within the Excelgoodies Analytics Community.
Power Automate
New
Next Batches Now Live
Power BI
SQL
Power Apps
Power Automate
Microsoft Fabrics
Azure Data Engineering