Google BigQuery – Cloud Data WareHouse Course in Chennai

825 Ratings

Master cloud-based data warehousing and analytics with Edubrights’ Google BigQuery – Cloud Data Warehouse training in Chennai. This course is designed for students, freshers, data analysts, data engineers, BI professionals, cloud practitioners, and working professionals who want to leverage Google Cloud’s powerful analytics platform for large-scale data processing.

Gain hands-on experience with BigQuery architecture, SQL analytics, data warehousing, data modeling, query optimization, reporting, and real-world cloud analytics projects through practical industry use cases.

Key Highlights:

✅ Real-Time Cloud Data Warehouse Projects & Industry Use Cases

✅ Live Instructor-Led Training by Google Cloud & Data Analytics Experts

✅ Hands-On Practice with Google BigQuery & Google Cloud Platform (GCP)

✅ BigQuery Architecture, Storage & Compute Fundamentals

✅ Advanced SQL for Data Analysis & Business Intelligence

✅ Data Loading, Transformation & Data Warehousing Techniques

✅ Query Optimization & Performance Tuning Best Practices

✅ Data Modeling & Scalable Analytics Solutions

✅ Integration with Looker, Data Studio & Google Cloud Services

✅ Data Governance, Security & Access Management Concepts

✅ Building Interactive Reports & Business Intelligence Workflows

✅ Resume Building, Portfolio Development & Mock Interview Preparation

✅ Career Guidance, Placement Assistance & Certification Support

✅ Flexible Online, Classroom & Weekend Training Options

✅ Corporate Training for Cloud, Analytics & Data Teams

Build practical BigQuery expertise, analyze large-scale datasets efficiently, and become industry-ready for careers in Cloud Data Engineering, Business Intelligence, Data Analytics, and Google Cloud Technologies.

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₹30000

₹42000

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Enroll Now View Syllabus

Case Studies and Projects

Hours of Training

20+

Placement Assurance

100%

Expert Support

Yes

Support & Access

Lifetime

Certification

Yes

Skill Level

All

Language

All

Course Objectives

Q1. What will I learn in the Google BigQuery – Cloud Data Warehouse course?

You will learn how to store, manage, query, and analyze large datasets using Google BigQuery. The course covers cloud data warehousing, SQL querying, data loading, reporting, and performance optimization for modern analytics.

Q2. Why should I learn Google BigQuery?

Google BigQuery is a powerful cloud-based analytics platform used by organizations to process massive volumes of data quickly. Learning BigQuery helps you build practical cloud analytics skills that are valuable in data engineering, business intelligence, and cloud computing careers.

Q3. How does this course support my career growth?

This course develops practical knowledge in cloud data warehousing, SQL, data analysis, and query optimization. These skills are beneficial for students, freshers, data analysts, cloud professionals, and IT professionals working with large-scale data.

Q4. Will I gain practical experience during the training?

Yes. The course includes hands-on labs where you will create datasets, import data, write SQL queries, optimize query performance, generate reports, and work with real-world cloud analytics scenarios using Google BigQuery.

Q5. What skills are required to become a Google BigQuery professional?

Develop practical skills in SQL analytics, cloud data warehousing, query optimization, data transformation, reporting, and business intelligence.

Popular Techniques Covered in This Course

BigQuery Fundamentals

SQL Querying

Dataset Management

Data Loading

Table Partitioning

Query Optimization

Data Analysis

Cloud Data Warehousing

BigQuery Security

Reporting & Insights

Get Hands-on Knowledge about Real-Time Projects

Project 1

1. Sales Analytics Dashboard Project

Load business sales data into BigQuery, write optimized SQL queries, and build interactive dashboards to analyze revenue, customer behavior, and business performance.

Project 2

2. Customer Data Warehouse Project

Design a cloud-based data warehouse by integrating customer information from multiple data sources for reporting and advanced analytics.

Project 3

3. Marketing Campaign Analytics Project

Analyze digital marketing campaign data using BigQuery to measure conversions, customer engagement, and return on investment through SQL-based reporting.

Project 4

4. BigQuery ML Prediction Project

Build machine learning models using BigQuery ML to predict customer trends, business outcomes, and future sales based on historical data.

Project 5

5. Enterprise Reporting Project

Develop automated reporting solutions by integrating BigQuery with Looker Studio to create real-time business intelligence dashboards for decision-makers.

Key Features

Edubrights offers GOOGLE BIGQUERY – CLOUD DATA WAREHOUSE Training in virtual mode with expert trainers. Here are the key features,

40 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Curriculum

Module 1: BigQuery Architecture and Fundamentals

Google BigQuery overview: serverless, petabyte-scale data warehouse
BigQuery architecture: Dremel execution engine, Colossus storage, and Jupiter network
BigQuery pricing: on-demand, capacity, and BigQuery Omni
Navigating BigQuery console: datasets, tables, and query editor

Module 2: BigQuery SQL Essentials

Standard SQL in BigQuery: SELECT, FROM, WHERE, GROUP BY, and HAVING
BigQuery-specific functions: DATE, TIMESTAMP, ARRAY, and STRUCT types
Wildcard table queries for querying multiple tables efficiently
BigQuery scripting: variables, loops, and procedural SQL

Module 3: Advanced SQL in BigQuery

Window functions: OVER, PARTITION BY, ORDER BY, and frame clauses
Analytical functions: ROW_NUMBER, RANK, LAG, LEAD, and NTILE
WITH clause and nested CTEs for complex query organisation
PIVOT and UNPIVOT for reshaping analytical datasets

Module 4: BigQuery Data Ingestion and Loading

Batch loading: CSV, JSON, Avro, Parquet, and ORC from GCS
Streaming inserts: real-time data ingestion with BigQuery Storage Write API
BigQuery Data Transfer Service: scheduled imports from SaaS sources
Federated queries: querying Cloud Storage, Bigtable, and Cloud SQL directly

Module 5: BigQuery Performance and Cost Optimisation

Partitioning: ingestion-time, column-based, and integer range partitioning
Clustering: automatic and manual clustering for query acceleration
Materialised views for pre-computed aggregations
Query optimisation: avoiding SELECT *, reducing data scanned, and slot usage

Module 6: BigQuery ML

BigQuery ML overview: training ML models with SQL
Supported model types: linear regression, logistic regression, k-means, and ARIMA
CREATE MODEL, EVALUATE, and PREDICT statements
Importing TensorFlow and XGBoost models into BigQuery ML

Module 7: BigQuery Security and Governance

IAM roles: dataset, table, and row-level access control
Column-level security with policy tags and data masking
VPC Service Controls for data exfiltration prevention
BigQuery audit logs and Data Catalog integration

Module 8: Capstone Project and Assessment

BigQuery data warehouse design and SQL analytics project
Performance optimisation: partitioning and clustering implementation
BigQuery ML model training and prediction exercise
Final assessment and course certification

Receive Training From Our Skilled and Effective Trainers

Experience in the Industry Learn from Google Cloud-certified data engineers and analysts who have built BigQuery data warehouses, analytics pipelines, and ML models for enterprises on Google Cloud Platform processing petabytes of data.

Backgrounds at the Top Our BigQuery trainers have delivered GCP data platform projects at technology companies, media organisations, and retail enterprises where BigQuery is the central analytical data store.

Clear & Effective Teaching BigQuery architecture, Standard SQL, advanced analytics, data ingestion, performance optimisation, BigQuery ML, security, and governance are explained with real-world data warehouse and analytics examples.

Hands-On Learning Focus Students write advanced BigQuery SQL, optimise query performance with partitioning and clustering, build BigQuery ML models, and configure access controls through structured hands-on lab exercises.

Up-to-Date Knowledge Trainers keep content current with the latest BigQuery releases, BigQuery Omni multi-cloud capabilities, Duet AI for BigQuery, and evolving Google Cloud data platform best practices.

Earn an Industry-Recognized Google BigQuery – Cloud Data Warehouse Certification

Successfully completing the Google BigQuery – Cloud Data Warehouse Course in Chennai demonstrates your ability to manage cloud data warehouses, perform SQL-based analytics, optimize queries, create business intelligence reports, and analyze enterprise-scale datasets using Google BigQuery.

Course FAQs

1. Who can join the Google BigQuery – Cloud Data Warehouse course?

This course is suitable for students, freshers, data analysts, database professionals, cloud engineers, software developers, and IT professionals. Anyone interested in cloud analytics and large-scale data processing can enroll.

2. Are there any prerequisites for learning Google BigQuery?

Basic knowledge of SQL and databases is helpful but not mandatory. The course begins with cloud data warehouse fundamentals and gradually introduces BigQuery features, making it accessible for beginners with an interest in data analytics.

3. How long does it take to complete the Google BigQuery training?

The course duration depends on the training schedule and learning format. Most learners complete the program within a few weeks while gaining practical experience through cloud labs, SQL exercises, and data analysis projects.

4. Will I get practical training on Google BigQuery?

Yes. The training emphasizes hands-on learning through practical exercises. You will work on creating datasets, importing data, executing SQL queries, analyzing large datasets, and optimizing query performance using Google BigQuery.

5. What topics are covered in the Google BigQuery course?

The course covers BigQuery architecture, SQL, dataset creation, table management, data loading, partitioning, clustering, query optimization, security, reporting, cloud analytics, and integration with other Google Cloud services.

6. Is Google BigQuery suitable for beginners?

Yes. The course is designed to introduce cloud data warehousing concepts from the basics. Learners gradually progress from SQL fundamentals to advanced BigQuery features through guided practical sessions.

7. What career opportunities are available after learning Google BigQuery?

Google BigQuery skills are useful in cloud consulting companies, IT organizations, analytics firms, startups, financial services, healthcare, retail, and other industries that rely on cloud-based data analytics and reporting.

8. Does the course include real-world projects?

Yes. Learners gain practical experience through projects involving cloud data storage, SQL querying, business reporting, data analysis, and performance optimization. These projects help build confidence in working with enterprise datasets.

9. Why should I learn Google BigQuery for cloud analytics?

BigQuery enables organizations to analyze large volumes of data efficiently without managing traditional database infrastructure. Learning BigQuery helps you understand modern cloud data warehouse technologies and scalable analytics solutions.

10. Is Google BigQuery an in-demand technology?

Yes. As businesses increasingly adopt cloud platforms and data-driven decision-making, professionals with BigQuery and cloud analytics skills are becoming valuable across multiple industries and technology domains.

11. Does BigQuery integrate with other Google Cloud services?

Yes. BigQuery integrates with Cloud Storage, Dataflow, Pub/Sub, Looker Studio, BigQuery ML, and other Google Cloud services for end-to-end analytics.

12. Is Google BigQuery in demand?

Yes. Organizations increasingly use BigQuery for cloud analytics, business intelligence, and large-scale data processing, creating strong career opportunities.

13. Can beginners learn Google BigQuery?

Yes. Beginners with basic SQL and database knowledge can learn BigQuery through structured lessons, practical exercises, and real-world cloud analytics projects.