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Training Pseudonymisation - Securing Data Pipelines in the Enterprise

Ref: EXY752
10 people max.
5500€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master advanced pseudonymisation algorithms for professional ETL pipelines
  • Develop skills in Spark integration to pseudonymize massive datasets in enterprises
  • Design secure and scalable pseudonymized Kafka streams
  • Optimize Airflow to orchestrate certified pseudonymisation in production
  • Implement re-identification resistant strategies in data engineering contexts
  • Deploy GDPR-compliant pseudonymisation solutions for Qualiopi-certified teams

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Pseudonymisation: Advanced Fundamentals and GDPR Compliance (Algorithms, Spark)

Dive into expert pseudonymisation techniques such as k-anonymity and differential privacy tailored to data engineering pipelines, using Apache Spark to process terabytes of sensitive data. Apply practical exercises on secure hashing and tokenization, analyze real enterprise GDPR cases, produce a first pseudonymized ETL with testable deliverables, and assess re-identification risks for immediate professional compliance.

Module 2Pseudonymisation: Spark Implementation for Massive Datasets (Advanced ETL)

Build optimized Spark jobs to pseudonymize continuous streams, integrate shuffling and salting against linkage attacks, through hands-on workshops on distributed clusters. Process real e-commerce datasets, measure performance with Spark SQL and DataFrames, generate compliance reports, and debug potential leaks, all aligned with enterprise standards for certified expertise in secure data engineering.

Module 3Pseudonymisation: Secure ETL Pipelines with Kafka (Pseudonymized Streams)

Deploy end-to-end Kafka pipelines for real-time pseudonymisation, configure producers/consumers with advanced encryption and format-preserving encryption. Simulate sensitive IoT streams, integrate pseudonymized Avro schemas, test resilience to attacks via practical exercises, produce monitoring dashboards, and validate scalability for enterprise production environments, enhancing certified professional skills.

Module 4Pseudonymisation: Airflow Orchestration and Tool Hybridization (Secure DAGs)

Orchestrate complex pseudonymisation workflows via Airflow, integrate Spark-Kafka DAGs for expert automations, manage secrets with Vault and key rotations. Develop custom tasks on real banking cases, optimize scheduling for data peaks, monitor privacy anomalies, generate automated audits, and deploy in simulated production, for certified mastery in enterprise data engineering pipelines.

Module 5Pseudonymisation: Optimization, Advanced Security, and Real Cases (Production Deployment)

Optimize pseudonymized pipelines for high availability, integrate ML for re-identification detection, via challenges on healthcare datasets. Audit hybrid Spark-Kafka-Airflow architectures, measure privacy ROI, produce deployable blueprints, and prepare internal certifications, concluding with a capstone project deliverable to boost professional skills in secure data engineering.

Evaluation method

  • Advanced quizzes on algorithms and Spark-Kafka tools
  • Final project: Complete pseudonymized ETL pipeline
  • GDPR case study with audit and optimization

Learning method

  • Practical projects on real Spark clusters
  • Hands-on workshops on Kafka and Airflow in simulated production
  • Enterprise cases for expert contextualization
  • Continuous feedback and personalized corrections

Methods, materials and delivery

The Training Pseudonymisation - Securing Data Pipelines in the Enterprise program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Pseudonymisation - Securing Data Pipelines in the Enterprise program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Pseudonymisation - Securing Data Pipelines in the Enterprise program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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