Training Great Expectations - Ensuring Data Quality in Production

Very demanding course · Expertise required

$4,620

  • 4 days
  • Onsite
  • 10 people max.
Ref: VCK670
10 people max.
$4,620
In-company rate: from $7,865 for the whole team
On-site and certification exam on quote
4 days
Onsite

Don't let this gap widen

Why this program matters

  • Without Great Expectations 2026, 80% of data projects fail due to lack of quality, costing an average of 1,2 million € per major incident according to Gartner.

  • Undetected data drifts generate 30% of analytical errors, blocking business decisions and exposing you to GDPR fines up to 4% of revenue.

  • Teams without expert skills lose 50% of their time on manual debugging, widening the competitive gap against rivals automating their data governance.

  • In 2026, 65% of data leaders demand this expertise for internal promotions.

  • Act before your pipelines sabotage your strategic goals.

Alicia DIOH, Managing Director · Finance, AI & Management trainer
Alicia DIOH

Managing Director · Finance, AI & Management trainer

73%productivity gap
×3cost of inaction
Flag of the United StatesBuilt for US teams
Payment by wire transferEnhanced confidentialityPerfect for companies with 50 to 500 employeesScheduling to fit any time zone

Trusted by — schools, companies and industrial groups

41,113 programs · 25 countries

  • Aptar
  • ArcelorMittal
  • Equans
  • EDF
  • Ubisoft
  • Microsoft
  • Atos

Every program built with a dedicated engineer

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  • AMD
  • Apple

Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.

Great Expectations training objectives

  • Master Great Expectations 2026 to validate professional data pipelines
  • Develop custom and scalable expectations for enterprise use
  • Implement CI/CD integration with Great Expectations for secure deployments
  • Design advanced checkpoints and real-time monitoring
  • Optimize data quality in hybrid cloud environments
  • Deploy certified automated test suites for data teams
  • Analyze and correct data drifts using expert tools

Program

Great Expectations curriculum: 4 modules over 4 days

Module 1 : Great Expectations 2026: Advanced Configuration and Expert Architecture (Datastores, Profilers)

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.

Module 2 : Great Expectations: Custom Expectations and Complex Validations (Regex, ML Metrics)

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.

Module 3 : Great Expectations: Pipeline Integration and CI/CD (Airflow, GitHub Actions)

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.

Module 4 : Great Expectations: Production Monitoring, Scalability, and Data Governance (Alerts, Audits)

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.

How Great Expectations skills are assessed

  • Expert multiple-choice quiz to assess learning outcomes at the end of the training
  • Continuous evaluation through advanced exercises and debugging
  • Defense of a complete data pipeline with Great Expectations

How the Great Expectations course is taught

  • Courses led by an active expert data engineering trainer
  • Practical exercises on real enterprise pipelines and open data datasets
  • Progressive red thread project with Great Expectations 2026
  • Complete course materials and templates provided to each participant

Great Expectations training: access and practical arrangements

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:

  • 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 Great Expectations - Ensuring Data Quality in Production 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

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.

Our method

How Learni guarantees the quality of your Great Expectations training

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.

A child walking to school with a backpack
Our social commitment

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.

  • Backpack, notebooks and essential supplies
  • Distributed through our partner charities
  • Included, at no extra cost to you
Enroll and offer a kit
FAQ

Great Expectations: frequently asked questions

Which tools are used in Great Expectations training?+
Hands-on work runs on datastores, profilers, regex, ML Metrics, airflow and gitHub Actions. Those tools come from the Great Expectations program itself, delivered on site over 4 days, so participants practise on the stack they will use at work.
What can participants do after Great Expectations training?+
They can master Great Expectations 2026 to validate professional data pipelines, develop custom and scalable expectations for enterprise use and implement CI/CD integration with Great Expectations for secure deployments. Those are the stated objectives of the Great Expectations program at Expert level, checked by the end-of-session assessment.
What does the Great Expectations program cover, day by day?+
Day 1: Great Expectations 2026: Advanced Configuration and Expert Architecture (Datastores, Profilers). Day 2: Great Expectations: Custom Expectations and Complex Validations (Regex, ML Metrics). Day 3: Great Expectations: Pipeline Integration and CI/CD (Airflow, GitHub Actions). Day 4: Great Expectations: Production Monitoring, Scalability, and Data Governance (Alerts, Audits). The Great Expectations program runs over 4 days, delivered on site.
How is Great Expectations training assessed?+
Assessment relies on expert multiple-choice quiz to assess learning outcomes at the end of the training, continuous evaluation through advanced exercises and debugging and defense of a complete data pipeline with Great Expectations. Learni issues a completion certificate together with the individual assessment report at the end of the Great Expectations program, which an L&D team can file as evidence.
How much does Great Expectations training cost per participant?+
Great Expectations training costs $4,620 per participant. For an in-company team, the flat rate starts at $7,865 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.
How long does Great Expectations training take?+
4 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for Great Expectations training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before Great Expectations training?+
Advanced mastery of Python, SQL, ETL pipelines (Airflow, Spark), and datastore management.
Is a certificate issued after Great Expectations training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
Does Learni provide the equipment for Great Expectations training?+
No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.
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