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Training Google Dataflow - Processing Real-Time Data at Scale

Ref: VNE992
10 people max.
From $5,765 HT / per person
In-company rate: $20,990 (team of 8)Volume pricing: ≈ $2,624/person for 8 · ≈ $5,248/person for 4
On-site on request · +$540 with certification exam
5 days
Onsite

Don't let this gap widen

Why this program matters

  • Without Google Dataflow mastery, stream pipelines produce 50% more latency, causing 20% losses in real-time business opportunities.

  • Companies pay 3x more in cloud costs for obsolete batch processing, with 65% of data loss incidents due to faulty scaling.

  • In 2026, 82% of Dataflow-certified data engineers reach senior roles at +30% salary.

  • Each quarter without stream skills widens a fatal competitive gap in live predictive analytics.

Allan BUSI, Learni trainer · AI expert
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

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Equans
EDF
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Microsoft
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ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
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ArcelorMittal
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Ubisoft
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ArcelorMittal
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Learning objectives

  • Master Google Dataflow for professional real-time data pipelines
  • Develop scalable and resilient enterprise stream processing
  • Optimize Dataflow performance with certifiable skills
  • Implement advanced GCP integrations for real-time analytics
  • Design fault-tolerant and cost-efficient Dataflow architectures
  • Deploy and monitor production Dataflow jobs with certification
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Our social commitment

A school kit donated to a child for every training booked

To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.

  • Backpack, notebooks and essential supplies
  • Distributed through our partner charities
  • Included, at no extra cost to you
Enroll and offer a kit

The Learni story

Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.

Don't let this gap widen

Why this program matters

  • Without Google Dataflow mastery, stream pipelines produce 50% more latency, causing 20% losses in real-time business opportunities.

  • Companies pay 3x more in cloud costs for obsolete batch processing, with 65% of data loss incidents due to faulty scaling.

  • In 2026, 82% of Dataflow-certified data engineers reach senior roles at +30% salary.

  • Each quarter without stream skills widens a fatal competitive gap in live predictive analytics.

Allan BUSI, Learni trainer · AI expert
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

Program

Module 1Google Dataflow: Advanced Stream Pipelines and Apache Beam (SDK, transformations)

Dive into the Beam SDKs for Google Dataflow, configure stream pipelines with Pub/Sub as the source, implement custom ParDo transformations and advanced windowing, test locally with DirectRunner then deploy to Dataflow, complete a practical exercise on a real-time IoT stream, produce a first scalable job with latency metrics.

Module 2Google Dataflow: Stateful Processing and Streaming Joins (stateful processing, CoGroupByKey)

Explore the stateful APIs of Google Dataflow for real-time aggregations, integrate stream joins with CoGroupByKey on multiple streams, handle late data with timers and watermarks, apply to an e-commerce fraud detection case, optimize memory with Beam's state backend, deliver a resilient join pipeline tested under load.

Module 3Google Dataflow: Optimization and Scaling (autoscaling, step fusion, custom IO)

Analyze Google Dataflow job profiles with Stackdriver, apply dynamic autoscaling and step fusion to reduce costs by 40%, develop custom IO for proprietary sources, test under traffic peaks with Synthetic Data, measure throughput and latency, produce a quantified optimization report on your end-to-end project.

Module 4Google Dataflow: Advanced GCP Integrations (BigQuery, Datastore, ML inference)

Connect Google Dataflow to BigQuery for real-time sinks, integrate Datastore for enriched lookups, deploy Vertex AI ML models in stream pipelines, process complex events with side inputs, simulate a live analytics dashboard, verify end-to-end latency under 1 second, document schemas and configurations for production.

Module 5Google Dataflow: Monitoring, Resilience, and 2026 Best Practices (SLO, templates)

Set up Cloud Monitoring alerts for Google Dataflow, implement resilience with dead-letter queues and retries, deploy parameterized templates for CI/CD, review fault-tolerant architectures for 2026, evaluate your end-to-end project in a presentation, receive a certification plan and enterprise skills roadmap.

Evaluation method

  • Expert quiz on Dataflow pipelines and Beam
  • Practical evaluation of optimized stream jobs
  • Presentation of the real-time end-to-end project

Learning method

  • Training by an active GCP-certified trainer
  • Practical exercises on real data stream cases
  • Scalable 5-day end-to-end project
  • Course materials and Dataflow templates provided

Methods, materials and delivery

The Training Google Dataflow - Processing Real-Time Data at Scale program is delivered onsite or remote (blended-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 Google Dataflow - Processing Real-Time Data at Scale 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 Google Dataflow - Processing Real-Time Data at Scale 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

Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.

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.

Step 1

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.
Step 2

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.
Step 3

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.
Step 4

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.

FAQ

Frequently asked questions

Which tools are used in Google Dataflow training?+
Hands-on work runs on SDK, transformations, stateful processing, coGroupByKey, autoscaling and step fusion. Those tools come from the Google Dataflow program itself, delivered on site over 5 days, so participants practise on the stack they will use at work.
What can participants do after Google Dataflow training?+
They can master Google Dataflow for professional real-time data pipelines, develop scalable and resilient enterprise stream processing and optimize Dataflow performance with certifiable skills. Those are the stated objectives of the Google Dataflow program at Expert level, checked by the end-of-session assessment.
What does the Google Dataflow program cover, day by day?+
Day 1: Google Dataflow: Advanced Stream Pipelines and Apache Beam (SDK, transformations). Day 2: Google Dataflow: Stateful Processing and Streaming Joins (stateful processing, CoGroupByKey). Day 3: Google Dataflow: Optimization and Scaling (autoscaling, step fusion, custom IO). Day 4: Google Dataflow: Advanced GCP Integrations (BigQuery, Datastore, ML inference). Day 5: Google Dataflow: Monitoring, Resilience, and 2026 Best Practices (SLO, templates). The Google Dataflow program runs over 5 days, delivered on site.
How is Google Dataflow training assessed?+
Assessment relies on expert quiz on Dataflow pipelines and Beam, practical evaluation of optimized stream jobs and presentation of the real-time end-to-end project. Learni issues a completion certificate together with the individual assessment report at the end of the Google Dataflow program, which an L&D team can file as evidence.
How much does Google Dataflow training cost per participant?+
$5,765 (USD) per participant. A detailed quote is sent within one business day, and team pricing applies from the second participant.
How long does Google Dataflow training take?+
5 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for Google Dataflow training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before Google Dataflow training?+
Mastery of Apache Beam, advanced Python or Java, GCP (Pub/Sub, BigQuery, Dataflow basics).
Is a certificate issued after Google Dataflow training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
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