Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training Data Lake - Storing and Exploiting Massive Data training are: Basic knowledge of SQL and relational databases. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Data Lake - Storing and Exploiting Massive Data training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Data Lake - Storing and Exploiting Mass... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Training Data Lake - Storing and Exploiting Massive Data training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Training Data Lake - Storing and Exploiting Massive Data training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training Data Lake - Storing and Exploiting Massive Data training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training objectives

Master the fundamentals of Data Lake for professional projects

Design scalable Data Lake architecture in a business context

Implement ingestion of heterogeneous data using open-source tools

Exploit data via queries and basic certifying analyses

Optimize governance and quality in a Data Lake

Develop skills to integrate a Data Lake into production

Training program

Module 1Data Lake Fundamentals: Principles and Initial Architecture (Hadoop, S3, Storage Zones)

Discovery of key Data Lake concepts, differentiation from data warehouse, hands-on with tools like AWS S3 or Hadoop to create raw, curated, and refined zones, practical exercises on ingesting various CSV and JSON files, simple scalable architecture modeling, production of an initial schema with diagrams and documentation for enterprise projects.

Module 2Data Lake Ingestion: Tools and ETL Pipelines (Apache NiFi, Kafka, Spark)

Configuration of ingestion tools like Apache NiFi for batch and streaming flows, implementation of basic ETL pipelines with Spark, processing of structured and unstructured data, real-world cases on application logs and IoT sensors, performance testing, creation of reusable scripts, generation of reports on ingested volume to validate robustness in professional contexts.

Module 3Data Lake Exploitation: Queries, Governance, and Deployment (Athena, Databricks Governance)

SQL queries on Data Lake via Amazon Athena or Presto, implementation of metadata with Apache Atlas, workshops on data quality and access security, partitioning optimization for fast queries, pilot deployment on cloud, final exercises with ongoing project analysis, delivery of complete governance plan and skills ready for certifying production.