Course : Big Data, methods and practical solutions for data analysis
Practical course - 3d
- 21h00 - Ref. IBD
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 | Understand the main concepts of Big Data, as well as the technological ecosystem of a Big Data project. |
| Knowing how to analyze the difficulties inherent in a big data project |
| Determine the nature of the data handled |
| Understanding safety, ethics and legal issues |
| Exploiting big data architectures |
| Setting up complete technical foundations for big data projects |
Intended audience
Project managers, architects, developers, data scientists or anyone who wants to know how to design a big data architecture.
Prerequisites
Avoir une bonne culture générale des systèmes d'information et, plus particulièrement, avoir des connaissances de base des modèles relationnels, des statistiques et des langages de programmation.
Practical details
Set up a Hadoop platform and its basic components, use an ETL to manage data, create analysis models and dashboards.
Course schedule
1 Understanding the concepts and challenges of big data
- Origins and definition of big data.
- Key market figures worldwide and in France.
- The challenges of big data: ROI, organization, data confidentiality.
- An example of big data architecture.
- Ethical and legal aspects of data management.
- Data security.
2 Big data technologies
- Description of the architecture and components of the Hadoop platform.
- Storage modes (NoSQL, HDFS).
- Operating principles of MapReduce, Spark, Storm, etc.
- Market-leading distributions (Hortonworks, Cloudera, MapR, Elastic Map Reduce, Biginsights).
- Install a Hadoop platform.
- Data scientist technologies.
- Overview of specific Big Data technologies (Tableau, Talend, QlikView, etc.).
Exercise
Installation of a Hadoop big data platform (via Cloudera QuickStart or other).
3 Managing structured and unstructured data
- Hadoop Distributed File System (HDFS) operating principles.
- Import external data into HDFS.
- Perform SQL queries with HIVE.
- Use PIG to process the data.
- The ETL principle (Talend, etc.).
- Massive data streaming management (NIFI, Kafka, Spark, Storm, etc.)
Exercise
Implementation of massive data flows.
Customer reviews
3,8 / 5
Customer reviews are based on end-of-course evaluations. The score is calculated from all evaluations within the past year. Only reviews with a textual comment are displayed.
SAID RACHID N.
17/12/25
2 / 5
The content did not correspond at all to my expectations or to the announced training plan. The trainer didn't use his camera, there were very long silences, spelling mistakes and some foreign language words in the slides.the concepts and principles were covered very superficially and too quickly.the other two trainees didn't meet the prerequisites you announced for the course, which disrupted the progress.
ROS SEBASTIEN D.
15/10/25
5 / 5
Frankly top
KARL N.
25/06/25
4 / 5
The content is far too dense for three days, forcing the trainer to speed up the course without leaving any room for discussion. What's more, there's not much on Spark. I'm a bit disappointed by the end of the course.
PARTICIPANTS
Project managers, architects, developers, data scientists or anyone who wants to know how to design a big data architecture.
PREREQUISITES
Avoir une bonne culture générale des systèmes d'information et, plus particulièrement, avoir des connaissances de base des modèles relationnels, des statistiques et des langages de programmation.
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
Project managers, architects, developers, data scientists or anyone who wants to know how to design a big data architecture.
PREREQUISITES
Avoir une bonne culture générale des systèmes d'information et, plus particulièrement, avoir des connaissances de base des modèles relationnels, des statistiques et des langages de programmation.
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TEACHING AIDS AND TECHNICAL RESOURCES
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
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