Training course · Make · Compliance & Data Protection

Make for Compliance and Data Protection Teams

Automation with Make (formerly Integromat) and AI modules: build scenarios, routers and AI steps while keeping data protection in check.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Make for Compliance and Data Protection Teams” is designed for roles such as Compliance officers and managers, Data protection officers and privacy coordinators and Information security officers and shows step by step how to use Make productively, safely and transparently in Compliance & Data Protection – from the fundamentals to advanced workflows.

Make, formerly known as Integromat, is a visual automation platform that lets you connect applications and automate recurring processes without writing code. Over two days you will learn to build scenarios systematically, from triggers and modules through routers and filters to iterators, aggregators and data stores. You will understand how data flows through a scenario, how to reshape it with functions and how to keep an eye on operations consumption.

The second focus is AI. You connect language models through Make’s AI modules and provider integrations to classify text, extract information from emails and documents, draft replies or enrich content. You learn to catch errors with error handlers, test scenarios and document them clearly. Finally, you address data protection topics such as hosting region, data processing agreements and data minimisation, so that your automations can be run safely within your organisation.

Compliance and data protection teams must keep track of a growing body of rules, from the GDPR and whistleblower protection to supply chain due diligence and the EU AI Act. Generative AI can structure and accelerate this work: AI assistants summarise new regulations, produce gap analyses against existing policies, support records of processing activities and data protection impact assessments and draft clear training content. Automation helps with data subject requests, contract reviews and vendor risk assessments. At the same time, compliance teams are expected to steer AI use across the organisation: AI policies, risk classification under the AI Act and staff AI literacy obligations. Teams that use AI confidently themselves can advise the business better and design effective governance.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Compliance officers and managers
  • Data protection officers and privacy coordinators
  • Information security officers
  • Governance, risk and compliance staff
  • AI governance leads

Typical challenges we address

  • Tracking numerous new regulations and translating them into internal requirements
  • Keeping records of processing and impact assessments up to date
  • Advising business units quickly and soundly when they introduce new tools
  • Steering organisation-wide AI use in a compliant way

What you will be able to do

  • You can build Make scenarios independently using triggers, routers, filters and data transformations.
  • You can process lists and records with iterators, aggregators and data stores.
  • You can integrate AI modules for classification, extraction and text generation into your processes.
  • You can safeguard scenarios with error handlers, validation and human approval.
  • Use AI for regulatory analysis, data protection documentation and contract reviews.
  • Build AI governance with a policy, a tool inventory and risk classification.
  • Advise business units soundly on GDPR and AI Act requirements for AI use.

Course outline

Day 1

Module 1 Fundamentals: scenarios, modules and data flow
  • Interface layout, scenario editor and execution history
  • Triggers, actions and searches: module types and their role in a scenario
  • Understanding bundles, mapping and data types and using them deliberately
  • Choosing between schedules, webhooks and instant triggers
Module 2 Logic: routers, filters, iterators and aggregators
  • Using routers and filters for branching and conditional flows
  • Splitting lists with iterators and combining them with aggregators
  • Applying text, date and maths functions to transform data
  • Using data stores and variables for interim values and duplicate checks
Module 3 AI building blocks in Make
  • Connecting language models via AI modules and provider integrations
  • Automating classification, structured data extraction and text generation
  • Building prompts from scenario variables and processing output as JSON
  • Combining AI agents in Make with tools and scenarios as actions
Module 4 Integrations, error handling and testing
  • Connecting common business applications and any API via the HTTP module
  • Applying error handlers such as Resume, Ignore, Break and Rollback
  • Validating AI output and routing unusable results to a person
  • Testing scenarios, optimising operations and documenting them for the team

Day 2

Module 5 Data protection, governance and operations
  • Assessing hosting region, data processing agreements and data flows to AI providers
  • Applying data minimisation and pseudonymisation within scenarios
  • Managing connections, teams and permissions across the organisation
  • Defining approval steps, monitoring and ownership for live operation
Module 6 Practice lab: Compliance & Data Protection
  • Regulatory gap analysis
  • Records of processing and DPIAs
  • Reviewing data processing agreements
  • Data subject requests
  • Building AI governance
  • Training and awareness
Module 7 Data protection, quality & transfer to daily work
  • Compliance and privacy records often contain sensitive information, such as whistleblower reports that must be kept strictly confidential under whistleblower protection laws and must not be entered into unvetted AI tools. At the same time, Article 4 of the EU AI Act requires organisations to ensure sufficient AI literacy among their staff.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Regulatory gap analysis

An AI assistant summarises new regulations, compares requirements with existing policies and processes and produces a structured list of gaps and actions for expert assessment.

Records of processing and DPIAs

Process descriptions and interviews are turned into draft entries for the record of processing activities and risk analyses for data protection impact assessments, reviewed by the DPO.

Reviewing data processing agreements

AI checks vendors' data processing agreements and privacy documentation for the mandatory content under Article 28 GDPR, third-country transfers and technical measures and flags deviations from the internal standard.

Data subject requests

Automations log access and erasure requests, monitor deadlines and draft responses, while data searches and final approval remain with the responsible staff.

Building AI governance

AI helps draft AI policies, build an inventory of AI systems in use and classify them according to the EU AI Act risk categories as a basis for governance board decisions.

Training and awareness

Policies are turned into clear learning modules, case studies and quizzes on data protection, anti-money laundering, anti-corruption or AI literacy, tailored to target groups across the organisation.

Prerequisites

You should be comfortable with common office and cloud applications and have some experience with AI assistants. No programming skills are required. You work in compliance, data protection or information security and are familiar with the basics of the GDPR.

Technical requirements

You will need a laptop with an up-to-date browser and a Make account; the free plan covers most exercises. API access for a language model is set up together during the course.

Data protection & compliance

Compliance and privacy records often contain sensitive information, such as whistleblower reports that must be kept strictly confidential under whistleblower protection laws and must not be entered into unvetted AI tools. At the same time, Article 4 of the EU AI Act requires organisations to ensure sufficient AI literacy among their staff.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Bremen Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Salzburg Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Online Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Kaiserslautern Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Online Request

Frequently asked questions

Is Make the same as Integromat?

Yes. Integromat was renamed Make and substantially developed along the way. The core principle of visual scenarios made of connected modules remains, while a redesigned interface, many new integrations and AI building blocks have been added. If you used Integromat in the past, you will quickly feel at home and discover the new capabilities on the course.

How do I keep operation costs under control?

Every module that runs consumes operations or credits, and AI calls also use quota with the respective model provider. On the course you learn to design scenarios so that filters apply early, unnecessary runs are avoided and data is processed in batches. This keeps your automations economical and predictable as volumes grow.

Can Make be used in a GDPR-compliant way?

In principle yes, provided you set up the framework deliberately. This includes choosing the hosting region, signing a data processing agreement, reviewing connected AI services and applying data minimisation. On the course you work through these points with a checklist and learn to filter or pseudonymise sensitive data within scenarios.

What does the EU AI Act actually require of companies?

Since early 2025, certain AI practices have been prohibited and organisations must ensure AI literacy among staff. Further obligations cover transparency and providers and deployers of high-risk systems. In the course we classify typical use cases and work out which governance components your organisation needs.

Can data protection officers use AI themselves?

Yes, for example for contract reviews, draft documentation or training content, provided no unnecessary personal data is processed. The legal assessment remains with you. Hands-on experience with AI also improves your advice to the business, because you can judge opportunities and risks more realistically.

How much does “Make for Compliance and Data Protection Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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