Google Cloud & BigQuery for Data Teams
BigQuery modelling, Dataflow concepts, cost-aware querying and data pipelines on Google Cloud.
- ✓ Instructor-led live sessions, online or in Bengaluru
- ✓ Hands-on labs in every module
- ✓ Capstone project with trainer review
- ✓ Curriculum customisable for corporate teams
- ✓ Certificate of completion
Next batch: Sat, 23 Jan 2027 · 32 hours · 4 days
Google Cloud & BigQuery for Data Teams
Duration: 32 hours · 4 days
Next batch: Sat, 23 Jan 2027
Format: Online live · Bengaluru classroom
Modules: 8 · Topics: 38
Level: Intermediate
Fee: ₹14,999
Trusted by leading experts
Upcoming batches
Open batches for individuals; corporate batches on your dates.
| Programme | Starts | Mode | Schedule | Duration | |
|---|---|---|---|---|---|
| Google Cloud & BigQuery for Data Teams | Sat, 23 Jan 2027 | Online live | Weekend (Sat) | 5 Saturdays | Enquire |
| Google Cloud & BigQuery for Data Teams | Mon, 22 Mar 2027 | Bengaluru classroom | Weekday | 4 days | Enquire |
Soaring demand, and where it takes you
BigQuery is a popular serverless warehouse, and teams that use it well, including on cost, are valued.
Become an expert
Roles this programme prepares you for:
Become a GCP Data Engineer
Builds pipelines and warehouses on Google Cloud.
- Model data effectively in BigQuery
- Load and stream data into BigQuery
- Partition and cluster tables for performance and cost
About the course
Data engineering on Google Cloud: BigQuery modelling and performance, loading and streaming data, Dataflow concepts, Cloud Composer orchestration, and cost-aware querying.
BigQuery modelling, Dataflow concepts, cost-aware querying and data pipelines on Google Cloud.
Why should I attend?
Data engineers on GCP
Analysts moving into engineering
ETL developers
Platform teams
Prerequisites
SQL; basic Python; Google Cloud console familiarity helpful
Level
Intermediate
Delivery modes, duration and fee
Online live
Instructor-led virtual classroom; weekday (full-day) or weekend (Saturday) batches
Bengaluru classroom
In-person batches at our Bengaluru training venue
On-site at your office
Private corporate batch anywhere in India, scheduled around your teams
Blended
Live sessions plus guided self-paced labs and mentor check-ins
Duration: 32 hours · 4 days
Course fee (open batch): ₹14,999
Corporate / team batches: per-participant or flat batch pricing on request, based on group size, format and customisation.
What will you learn
- Model data effectively in BigQuery
- Load and stream data into BigQuery
- Partition and cluster tables for performance and cost
- Understand Dataflow pipelines
- Orchestrate with Cloud Composer
- Control query costs and access
Skills you will gain
BigQuery
Pipelines
Governance
Tools and platforms covered
Google BigQuery
Google Cloud Storage
Dataflow
Cloud Composer
Pub/Sub
PythonCourse curriculum
M01 Google Cloud data overview
- Core services
- Projects and IAM
- Reference designs
- Organisation and folders
- Cost visibility
🧪 Hands-on: Set up a project
M02 BigQuery fundamentals
- Datasets and tables
- SQL dialect
- Pricing models
- Nested and repeated fields
- Scripting and procedures
🧪 Hands-on: Run analytical queries
M03 Performance and cost
- Partitioning
- Clustering
- Query optimisation
- Materialised views
- BI Engine
🧪 Hands-on: Cut a query's cost
M04 Loading data
- Batch loads
- Streaming
- External tables
- Storage Write API
- Change data capture
🧪 Hands-on: Load and stream data
M05 Pipelines
- Dataflow concepts
- Pub/Sub
- Cloud Composer
- Dataflow templates
- Pub/Sub subscriptions
🧪 Hands-on: Orchestrate a pipeline
M06 Governance
- IAM
- Column- and row-level security
- Cost controls
- Dataplex overview
- Policy tags
🧪 Hands-on: Secure a dataset
M07 Analytics and ML in BigQuery
- BigQuery ML
- Remote models and GenAI functions
- Looker Studio
- Sharing data
🧪 Hands-on: Train a BigQuery ML model and visualise results
M08 Capstone: BigQuery platform
- Ingest
- Model
- Optimise
- Govern
🧪 Hands-on: Deliver a cost-optimised BigQuery pipeline with governance
Hands-on projects
BigQuery analytics pipeline
Loaded, modelled and cost-optimised BigQuery datasets orchestrated by Composer.
Why train with us
Built around your stack
Labs and examples adapted to the tools, cloud and data your team actually uses.
Practice-first
Every module ends in a lab, and the course ends with a reviewed capstone.
Practitioner-led
Delivered by Karthick Selvam and vetted specialist trainers from our network.
Visible progress
Attendance, lab completion and assessment results shared with your L&D team.
Certificate of completion
Participants who complete the labs and capstone receive a Learning Dots certificate of completion for Google Cloud & BigQuery for Data Teams. [confirm certificate wording / sample image]
Learner reviews
“[Verified learner review for this course]”
“[Verified learner review for this course]”
Meet your trainer
Karthick Selvam
Founder · Data Engineering Corporate Trainer, Bengaluru
[Trainer bio, experience and areas of expertise]
Frequently asked questions
Is prior GCP experience needed?
No; SQL knowledge is enough to start.
Can the curriculum be customised for our team?
Yes. Modules, depth, duration and labs can be tailored to your stack and goals.
What delivery formats are available?
Online live instructor-led sessions, Bengaluru classroom, or on-site at your office.
How do we enquire or book?
Use the enquiry form on this page or the Enquire button next to any batch.
What does it cost?
The open-batch fee is ₹14,999 per participant plus GST. Corporate batches are priced on group size, format and customisation.
How long is the course?
32 hours · 4 days. Corporate batches can be split into half-day sessions.
A closer look
About this course
Data engineering on Google Cloud: BigQuery modelling and performance, loading and streaming data, Dataflow concepts, Cloud Composer orchestration, and cost-aware querying.
What is Google Cloud & BigQuery for Data Teams?
BigQuery modelling, Dataflow concepts, cost-aware querying and data pipelines on Google Cloud.
Who this course is for
Data engineers on GCP, Analysts moving into engineering, ETL developers, Platform teams.
What you will be able to do
Model data effectively in BigQuery. Load and stream data into BigQuery. Partition and cluster tables for performance and cost. Understand Dataflow pipelines. Orchestrate with Cloud Composer. Control query costs and access.
Career paths
Roles this course supports include GCP Data Engineer, BigQuery Developer, Analytics Platform Engineer. BigQuery is a popular serverless warehouse, and teams that use it well, including on cost, are valued.
Cloud guides
AWS vs Azure vs Google Cloud: Which Should Your Team Learn?
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