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.
Learning objectives
- Master the fundamentals of Apache Arrow for professional analyses
- Develop performant and scalable data pipelines
- Implement reading and writing of massive datasets with Arrow
- Integrate Apache Arrow with Python, Pandas, and Spark in a business context
- Optimize memory and CPU performance for certifiable skills
- Design efficient and secure columnar data flows
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.
Program
Module 1Apache Arrow Fundamentals: Installation and Columnar Concepts (PyArrow Tools, Environments)
Immersive discovery of Apache Arrow's columnar principles, quick installation of PyArrow and creation of a first zero-copy dataset, exploration of data schemas through practical exercises on massive CSV files, manipulation of Arrow arrays to understand memory gains, production of an initial report on performance compared to classic Pandas, with personalized code review to anchor professional skills from the first day.
Module 2Apache Arrow Manipulation: Reading, Writing, and Conversion (IPC, Parquet Formats)
Practical dive into basic operations with Apache Arrow, smooth reading of Parquet and IPC files on real enterprise datasets, transparent conversion between formats via PyArrow and exercises on 1 GB of data, optimized writing of Arrow tables for big data storage, resolution of concrete cases like importing application logs, delivery of a reusable script tested under load conditions to boost your immediate data productivity.
Module 3Apache Arrow Integration: Python, Pandas, and Ecosystem (Bindings, Compute API)
Concrete integration of Apache Arrow with Pandas to accelerate DataFrames, use of Python bindings on ongoing sales analysis projects, exploration of the Compute API for vectorized aggregations without memory overhead, collaborative exercises on zero-copy joins between massive tables, development of a simplified ETL pipeline connected to SQL sources, obtaining a functional deliverable ready for the company with measured performance metrics.
Module 4Advanced Apache Arrow: Spark and Scalability (Spark DataFrames, Plasma)
Powerful connection of Apache Arrow to Apache Spark for distributed clusters, configuration of Arrow-optimized DataFrames on simulated multi-node environments, practical exercises on efficient shuffling and SQL queries on virtual terabytes, discovery of Plasma for shared in-memory storage, enterprise use cases like real-time IoT logs analysis, production of a deployable Spark job with 5x speed gains validated by personal benchmarks.
Module 5Apache Arrow Optimization: Production and Best Practices (Tuning, Monitoring)
Final mastery of Apache Arrow optimizations for production environments, tuning of Compute kernels for specific CPU/GPU via exercises on critical datasets, implementation of memory leak monitoring and profiling with Flight RPC, security review on shared data streams, finalization of the ongoing project with Dockerized deployment, delivery of a complete kit of certifiable resources for immediate implementation in the company.
Evaluation method
- Multiple-choice quiz to validate learning outcomes at the end of the training
- Continuous evaluation through practical exercises on real datasets
- Defense of the ongoing Apache Arrow project in front of the trainer
Learning method
- Courses led by an active data engineering expert trainer
- Practical exercises on concrete enterprise big data cases
- Progressive ongoing project throughout the training
- Complete course materials provided to each participant
Methods, materials and delivery
The Training Apache Arrow - Processing Massive Data in Real Time 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 Apache Arrow - Processing Massive Data in Real Time 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 Apache Arrow - Processing Massive Data in Real Time 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
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
★★★★★
« cool, j'ai appris des trucs »
★★★★★
« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »
★★★★★
« la formation dev etait intense mais grave bien. merci Anthony Khelil »
★★★★★
« 😊👍 »
★★★★★
« bien 👍 »
★★★★★
« Allan Busi t'es au top, continue comme ça. formation géniale »
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.
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.
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