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.
Training Data Quality - Mastering Data Reliability in Research
Trusted by — schools, companies and industrial groups
41,181 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.
Data Quality training objectives
- Master advanced profiling techniques to assess data quality in a professional context.
- Develop skills in detecting and correcting anomalies in research datasets.
- Implement automated validation rules tailored to business needs.
- Design certifying data quality pipelines to ensure the reliability of scientific analyses.
- Optimize data governance processes within multidisciplinary teams.
- Evaluate the impact of data quality on the performance of research and business models.
Program
Data Quality curriculum: 2 modules over 2 days
Module 1 : Data Quality: Diagnosis and Profiling (SQL Tools, Python Pandas, Statistical Methods)
Discover essential methods to profile your datasets using advanced SQL and Pandas, analyze completeness, accuracy, and consistency of data via optimized queries and interactive visualizations with Matplotlib, perform practical exercises on real scientific research cases, identify duplicates and outliers with automated scripts, produce a complete diagnostic report as a deliverable, integrate statistical techniques to quantify quality risks, and prepare the ground for Day 2 corrections in an immersive learning environment.
Module 2 : Data Quality: Correction, Validation, and Governance (Business Rules, ETL Pipelines, Monitoring)
Take action by implementing ETL pipelines to correct detected anomalies, configure business validation rules via Great Expectations and custom Python scripts, test on large datasets from research, develop a continuous monitoring system to alert on quality drifts, apply concrete business and scientific cases with pair exercises, generate tracking dashboards with Tableau to visualize improvements, and finalize with an immediately deployable data quality governance plan, thereby strengthening your certifying skills in professional training.
How Data Quality skills are assessed
- Interactive quizzes and multiple-choice questions at the end of each module to validate theoretical knowledge.
- Practical case studies on real datasets with personalized expert feedback.
- Final project on a data quality pipeline evaluated against professional criteria and certifying.
How the Data Quality course is taught
- Experiential learning through practical exercises and hands-on activities for 80% of the time.
- Real case studies from scientific research and Qualiopi-certified companies.
- Pedagogical methods adapted to the intermediate level with individualized support.
- Digital resources post-training for autonomous and sustainable review.
Data Quality training: access and practical arrangements
The Training Data Quality - Mastering Data Reliability in Research 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 - Mastering Data Reliability in Research 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 - Mastering Data Reliability in Research 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.
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.
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.
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.
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
FAQ
Data Quality: frequently asked questions
Which tools are used in Data Quality training?+
Hands-on work runs on SQL Tools, python Pandas, statistical Methods, business Rules, ETL Pipelines and monitoring. Those tools come from the Data Quality program itself, delivered on site over 2 days, so participants practise on the stack they will use at work.
What can participants do after Data Quality training?+
They can master advanced profiling techniques to assess data quality in a professional context, develop skills in detecting and correcting anomalies in research datasets and implement automated validation rules tailored to business needs. Those are the stated objectives of the Data Quality program at Intermediate level, checked by the end-of-session assessment.
What does the Data Quality program cover, day by day?+
Day 1: Data Quality: Diagnosis and Profiling (SQL Tools, Python Pandas, Statistical Methods). Day 2: Data Quality: Correction, Validation, and Governance (Business Rules, ETL Pipelines, Monitoring). The Data Quality program runs over 2 days, delivered on site.
How is Data Quality training assessed?+
Assessment relies on interactive quizzes and multiple-choice questions at the end of each module to validate theoretical knowledge, practical case studies on real datasets with personalized expert feedback and final project on a data quality pipeline evaluated against professional criteria and certifying. 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 $2,310 per participant. For an in-company team, the flat rate starts at $4,190 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?+
2 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?+
Solid knowledge of SQL and databases, experience in handling and analyzing structured datasets, basic knowledge of Python for data processing.
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.
Your professional training, anywhere
Let's build your Data Quality learning path.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.
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