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 Google BigQuery - Scaling Serverless Data Warehouse training are: Advanced SQL proficiency, Google Cloud Platform experience, management of large-volume ETL pipelines. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Google BigQuery - Scaling Serverless Data Warehouse training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Google BigQuery - Scaling Serverless Da... | 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 Google BigQuery - Scaling Serverless Data Warehouse 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 Google BigQuery - Scaling Serverless Data Warehouse 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 Google BigQuery - Scaling Serverless Data Warehouse 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 BigQuery optimizations for real-time analysis of petabytes

Develop advanced SQL queries and integrated ML in a professional enterprise setting

Design scalable, certifiable serverless data warehouse architectures

Implement data governance and security at scale in BigQuery

Optimize costs and performance for expert data engineering skills

Integrate BigQuery with the GCP ecosystem for certifiable projects

Training program

Module 1BigQuery Architecture: Serverless Modeling at Scale (partitions, clusters, slots)

Dive into BigQuery's serverless architecture to model massive datasets, configure partitions and clusters to accelerate queries by 10x, manage reserved and on-demand slots to optimize enterprise budgets, perform hands-on exercises on real petabyte datasets, create scalable schemas with Materialized Views, and test live performance to validate immediate professional skills.

Module 2Advanced BigQuery Queries: Expert SQL and Window Functions (optimizations, massive joins)

Master advanced BigQuery SQL with window functions for complex analyses on billions of rows, integrate UDFs and scripting for powerful automations, optimize joins and aggregations on unstructured data, apply real-world e-commerce and IoT cases, develop integrated ML queries via BigQuery ML for real-time predictions, and generate performant reports with trainer code review to refine certifiable skills.

Module 3BigQuery Integrations: GCP Pipelines and Serverless ETL (Dataflow, Pub/Sub, Looker)

Build serverless ETL pipelines by connecting BigQuery to Dataflow for real-time streaming, integrate Pub/Sub and Cloud Storage for massive ingestions, orchestrate workflows with Composer for enterprise automations, explore BI via Looker Studio on BigQuery datasets, implement end-to-end ongoing project flows on real data, and validate scalability and resilience for immediate production deployments.

Module 4BigQuery Governance: Security, Costs, and Large-Scale Monitoring (IAM, slots, BI Engine)

Implement advanced BigQuery governance with granular IAM and column-level security for GDPR compliance, optimize costs via BI Engine and query caching for 50% savings, monitor with Cloud Monitoring and Logging for proactive alerts, analyze slot usage and budgets for maximum ROI, finalize ongoing project with full audit, and prepare for certification to boost expert data warehouse career.