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.
Describe your need, get a tailored program and a pre-filled quote in 3 min. A 100% free call with an advisor.
Very demanding course · Expertise required
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Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.
Program
Dive into the installation and expert configuration of Great Expectations 2026 on cloud environments like AWS S3 or Snowflake, configure multiple datastores with pandas and Spark, launch automated profilers on massive datasets to detect schemas and anomalies, perform practical exercises on a real ETL pipeline, produce your first validation suite with generated documentation, and optimize performance for terabyte-scale volumes in enterprise settings.
Create custom expectations using advanced Python, integrate regex validations for structured formats, implement ML metrics like drift detection via scikit-learn, test on real-world data quality cases in finance and healthcare, develop reusable scripts for data teams, perform interactive runs with Jupyter for rapid iteration, and generate detailed HTML reports proving professional data compliance.
Integrate Great Expectations 2026 into orchestrators like Airflow or Dagster via custom DAGs, configure batch and streaming checkpoints for continuous monitoring, automate tests in GitHub Actions or Jenkins with success badges, apply to an enterprise red thread project with realistic simulated data, debug validation failures live, and deploy scalable runtimes on Kubernetes for high availability in production.
Set up advanced monitoring with Slack/Teams alerts on data drifts, analyze logs and metrics via interactive Data Docs, scale on Spark clusters for petabyte data, audit GDPR compliance with privacy-focused expectations, finalize the red thread project with a custom dashboard, export certified deliverables for data governance committees, and prepare best practices for enterprise rollout with measurable ROI.
The Training Great Expectations - Ensuring Data Quality in Production program is delivered onsite or remote (blended-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 Great Expectations - Ensuring Data Quality in Production program, the following equipment is required:
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.
Skills assessment methods
Assessment of skills acquired during the Training Great Expectations - Ensuring Data Quality in Production program is performed through:
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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
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.
Rigorous trainer selection
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
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.
Content tailored to your context
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
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.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

A school kit donated to a child for every training booked
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.
PythonIndustry-certified
Data analysis & BIIndustry-certified
Data engineeringIndustry-certified
Data governance & qualityIndustry-certified
Data governance & qualityIndustry-certified
Data governance & qualityIndustry-certified
GDPR & digital lawIndustry-certified
GDPR & digital lawIndustry-certified
GDPR & digital lawIndustry-certified
Data scienceIndustry-certified
Data scienceIndustry-certified
Data scienceIndustry-certified
Data analysis & BIIndustry-certified
Data analysis & BIIndustry-certified
Data analysis & BIIndustry-certifiedAvailable on-site and remotely. Pick your city to see the local training center.
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