Training Data Quality - Ensuring Data Reliability in the Enterprise

Specialist course · Minimum level required

$4,620

  • 4 days
  • Onsite
  • 10 people max.
Ref: DMF684
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 data quality control, 30% of enterprise datasets contain errors that block strategic analyses, causing estimated annual losses of 15 million € from bad business decisions.

  • Data teams lose 40% of their time on manual corrections, doubling project timelines.

  • In 2024, 68% of AI/ML failures stem from poor data quality, threatening promotions and competitiveness.

  • Every quarter without advanced skills exposes your company to RGPD fines and a critical lag behind data-driven competitors.

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

41,115 programs · 25 countries

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

Every program built with a dedicated engineer

  • OpenAI
  • Anthropic
  • Mistral AI
  • NVIDIA
  • Google
  • Amazon Web Services
  • Microsoft Dynamics 365
  • Salesforce
  • ServiceNow
  • SAP
  • Oracle
  • Cisco
  • Fortinet
  • Palo Alto Networks
  • Aruba
  • VMware
  • Red Hat
  • Databricks
  • Snowflake
  • OVHcloud
  • Notion
  • AMD
  • Apple

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

Data Quality training objectives

  • Master advanced data quality techniques for reliable professional pipelines
  • Develop automated profiling and cleaning strategies in the enterprise
  • Implement scalable, certifiable data quality validation rules
  • Design real-time data quality monitoring systems
  • Optimize data governance to minimize business risks
  • Deploy open-source data quality tools in production environments

Program

Data Quality curriculum: 4 modules over 4 days

Module 1 : Data Quality Profiling: Evaluate and Diagnose Datasets (Great Expectations, Deequ, SQL profilers)

Immediate immersion in in-depth data quality analysis via automated profiling, hands-on with tools like Great Expectations to detect anomalies, duplicates, and inconsistencies on real enterprise datasets, practical exercises on your own imported data, generation of detailed visual reports with comprehensive metrics, development of an actionable initial diagnosis to prioritize corrective actions.

Module 2 : Data Quality Cleaning: Standardize and Enrich Data (Python Pandas, Talend, custom scripts)

Practical application of advanced data quality cleaning techniques using Python with Pandas and specialized libraries like Dedupe, processing large datasets to correct formats, missing values, and outliers, implementation of automated standardization rules on various business cases, iterative tests with cross-validation, production of cleaned datasets ready for analysis, support to integrate these pipelines into your existing workflows.

Module 3 : Data Quality Governance: Implement Rules and Monitoring (Collibra, Soda, data observability)

Design of a robust data quality governance framework with definition of parametric business rules, deployment of real-time monitoring via Soda and automated alerts on degradations, practical workshops to catalog metadata and lineages, simulation of data incidents to test resilience, creation of personalized dashboards tracking quality KPIs, expert advice to align governance with GDPR and ISO 8000 standards in the enterprise.

Module 4 : Data Quality Deployment: Scale in Production (Airflow, Kubernetes, CI/CD data pipelines)

Finalization through advanced orchestration of end-to-end data quality pipelines with Apache Airflow and Kubernetes integration for scalability, automation of quality tests in CI/CD via GitHub Actions, exercises on AWS/GCP cloud deployment of monitoring solutions, performance optimization for large volumes, collaborative code review on the red thread project, delivery of a complete playbook for immediate production rollout with measurable ROI.

How Data Quality skills are assessed

  • Advanced MCQ on data quality metrics and tools
  • Evaluation through practical projects and business cases
  • Presentation of the personalized data quality pipeline

How the Data Quality course is taught

  • Sessions led by operational data quality experts
  • Hands-on exercises on real enterprise datasets
  • Evolving red thread project over 4 days
  • Comprehensive training materials and open-source resources

Data Quality training: access and practical arrangements

The Training Data Quality - Ensuring Data Reliability in the Enterprise 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 Data Quality - Ensuring Data Reliability 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 Data Quality - Ensuring Data Reliability 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

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 Data Quality 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

Data Quality: frequently asked questions

Which tools are used in Data Quality training?+
Hands-on work runs on great Expectations, deequ, SQL profilers, python Pandas, talend and custom scripts. Those tools come from the Data Quality program itself, delivered on site over 4 days, so participants practise on the stack they will use at work.
What can participants do after Data Quality training?+
They can master advanced data quality techniques for reliable professional pipelines, develop automated profiling and cleaning strategies in the enterprise and implement scalable, certifiable data quality validation rules. Those are the stated objectives of the Data Quality program at Advanced level, checked by the end-of-session assessment.
What does the Data Quality program cover, day by day?+
Day 1: Data Quality Profiling: Evaluate and Diagnose Datasets (Great Expectations, Deequ, SQL profilers). Day 2: Data Quality Cleaning: Standardize and Enrich Data (Python Pandas, Talend, custom scripts). Day 3: Data Quality Governance: Implement Rules and Monitoring (Collibra, Soda, data observability). Day 4: Data Quality Deployment: Scale in Production (Airflow, Kubernetes, CI/CD data pipelines). The Data Quality program runs over 4 days, delivered on site.
How is Data Quality training assessed?+
Assessment relies on advanced MCQ on data quality metrics and tools, evaluation through practical projects and business cases and presentation of the personalized data quality pipeline. Learni issues a completion certificate together with the individual assessment report at the end of the Data Quality program, which an L&D team can file as evidence.
How much does Data Quality training cost per participant?+
Data Quality 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 Data Quality 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 Data Quality 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 Data Quality training?+
Advanced mastery of SQL, Python or R for data processing, and basics in data warehousing.
Is a certificate issued after Data Quality 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 Data Quality 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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