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 BigQuery - Efficiently Analyze Massive Data training are: Basic knowledge of SQL and familiarity with structured data concepts. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training BigQuery - Efficiently Analyze Massive Data training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training BigQuery - Efficiently Analyze Massive ... | 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.

Configure your training

Response within 24hNo commitment100% free

9 spots remaining for the next session

FormatParticipantsDateDetails

Which format do you prefer?

Methods, approaches, and teaching resources

The Training BigQuery - Efficiently Analyze 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 BigQuery - Efficiently Analyze 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 BigQuery - Efficiently Analyze 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 access terms and deadlines

Training objectives

Master the fundamentals of BigQuery for professional, certifiable analyses

Develop optimized SQL queries on large volumes of data

Configure datasets and tables in the BigQuery environment

Implement analysis pipelines for business needs

Analyze and export data using integrated tools

Acquire scalable skills for production data projects

Training program

Module 1BigQuery Fundamentals: Configuration and First Datasets (GCP Console, Standard SQL)

Discovery of the Google Cloud Platform console and creation of your first BigQuery project, hands-on with datasets and tables to import real business data, interactive schema exploration with basic SQL queries, practical exercises on massive samples to understand serverless storage, creation of a simple first dashboard and export of results, with personalized feedback from the trainer to consolidate your skills from the start.

Module 2BigQuery Queries: Advanced SQL and Analytic Functions (JOIN, WINDOW, Aggregations)

Dive into complex queries with multiple JOINs on billions of rows without latency, mastery of analytic functions like ROW_NUMBER and LAG for precise business insights, performance optimization via partitioning and clustering on real business cases, practical workshops to transform raw data into actionable reports, testing real scenarios like log analysis or e-commerce sales, production of materialized views to accelerate future analyses.

Module 3BigQuery Management: Pipelines and Automation (Dataflow, Scheduled Queries)

Configuration of ingestion pipelines with Cloud Storage and Pub/Sub for continuous streams, setting up scheduled queries for automated daily reports, integration with BigQuery ML for simple predictions without external code, exercises on cost and quota management in an enterprise environment, simulation of scalable workloads with monitoring via Cloud Monitoring, creation of a basic deliverable ETL ready for production, enhancing your professional autonomy.

Module 4BigQuery Projects: Optimization and Visualization (Looker Studio, Advanced Exports)

Development of a complete ongoing project on a real business dataset, query cost optimization with slots and materialized views, connection to Looker Studio for interactive visualizations and shared dashboards, advanced exercises on IAM security and federated queries, performance tests under massive load, finalization with export to Sheets or Drive, collective review of deliverables to validate your certified skills and prepare for production deployment.