BigQuery for Data Analytics Training in Chennai-Edubrights

825 Ratings

BigQuery for Data Analytics Course in Chennai

Master cloud-based data analytics with Edubrights' BigQuery for Data Analytics Course in Chennai. Designed for students, freshers, job seekers, data analysts, and working professionals, this training program helps you develop practical skills in data querying, data warehousing, analytics reporting, and large-scale data processing using Google BigQuery through hands-on learning and real-world projects.

Learn how organizations leverage BigQuery to analyze massive datasets, generate business insights, optimize reporting processes, and support data-driven decision-making. Through practical assignments, industry-focused case studies, and project-based training, you will gain the expertise needed to work with modern cloud analytics platforms and enterprise data environments.

Key Highlights:

✅ Real-Time BigQuery Projects and Business Analytics Case Studies

✅ Hands-On Training in SQL Queries and Large-Scale Data Analysis

✅ Data Warehousing, Data Processing, and Cloud Analytics Concepts

✅ Practical Exposure to Query Optimization and Performance Tuning

✅ Reporting, Business Intelligence, and Data Visualization Workflows

✅ Industry-Aligned Curriculum Designed by Experienced Data Professionals

✅ Resume Building, Mock Interviews, and Placement Assistance

✅ Flexible Online, Classroom, and Weekend Training Options

Start your BigQuery analytics journey with Edubrights and gain the practical skills, project experience, and industry knowledge needed to become a job-ready Data Analytics professional in today's cloud-driven business environment.

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₹16000

₹20000

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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

1.What exactly BigQuery for Data Analytics training cover?

BigQuery training covers managing and analyzing large-scale datasets using Google Cloud’s serverless data warehouse. It includes data ingestion, SQL querying, data transformation, performance optimization, and visualization integration.

2. What are the main objectives of the BigQuery for Data Analytics course for your development skills?

The course aims to enhance your skills in handling big data analytics, writing efficient SQL queries, building scalable data transformation pipelines, and creating insightful visual reports using BigQuery and related tools.

3. Build Serverless Predictive AI Models

Leverage BigQuery ML to design, train, and deploy supervised and unsupervised machine learning models using standard SQL syntax.

4. Integrate Unified Enterprise Analytics Ecosystems

Establish secure connections between BigQuery databases and downstream visualization suites like Looker Studio and Power BI, alongside cloud storage data lakes.

Popular Techniques Covered in This Course

1.SQL querying

2.Data ingestion and ETL

3.Data modeling and transformation

4.Performance tuning

5.Data visualization

6.BigQuery ML basics

7.Security and governance

8.Monitoring and troubleshooting

9.Analytics solution design

10.Cost management and optimization

Get Hands-on Knowledge about Real-Time Projects

Project 1

1.E-commerce Sales Analysis:

Analyze sales data with BigQuery SQL, then visualize trends using Looker Studio.

Project 2

2.Customer Segmentation using BigQuery ML:

Use BigQuery ML to create customer clusters for targeted marketing.

Project 3

3. Live Log Tracking & Stream Ingestion Architecture

Design an active tracking subsystem to capture and monitor high-frequency system behavior. You will orchestrate pipelines that stream operational metrics straight into a real-time database table, building dynamic live dashboards to capture system health drops instantly.

Project 4

4. Public Health Geospatial Mapping & GIS Query Engine

Construct a geospatial data analysis module using location coordinates and public map files. You will write specialized spatial queries to isolate clusters of regional health data points, calculating distances and drawing custom boundary shapes for executive territory planning.

Project 5

5. Multi-Tenant Enterprise Data Access & Security Matrix

Architect a strictly compliant data governance framework across an enterprise organization. You will configure Google Cloud IAM security clearings, set up row-level filtering policies, and build column-level masking rules to keep sensitive employee details invisible to unauthorized analytical accounts.

Key Features

Edubrights offers BigQuery for Data Analytics 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: Introduction to BigQuery and Cloud Data Analytics

Overview of BigQuery and Google Cloud Platform
Data analytics fundamentals and business use cases

Module 2: Exploring and Querying Data with SQL

SQL basics and advanced querying techniques
Using functions, joins, and aggregations

Module 3: Data Preparation and Transformation Cleaning and structuring data ETL strategies and Dataform introduction

Module 4: Data Ingestion and Storage Options

Loading data from various sources
External tables and storage optimization

Module 5: Data Visualization Integration

Using Connected Sheets and Looker Studio
Principles of visual storytelling and reporting

Module 6: Advanced Data Analytics Features

Query optimization and performance tuning
Using BigQuery ML for basic machine learning tasks

Module 7: Security and Access Management

Data access controls and auditing
Compliance and best practices

Module 8: Hands-On Labs and Real-World Projects

Practical exercises on querying, transformation, and visualization

Receive Training From Our Skilled and Effective Trainers

Experience in the Industry Gain knowledge from experts with practical BigQuery for Data Analytics project experience in a variety of sectors.

Backgrounds at the Top Prominent corporations such as hcl, tcs , accenture and cognizant employ trainers.

Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.

Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.

Up-to-Date Knowledge Trainers stay current with the latest tools, techniques and best practices.

Succeed Our Resourceful Certification

Our certification validates your expertise in managing and analyzing data using Google BigQuery. It showcases your ability to build scalable data solutions and deliver actionable insights, enhancing your data analytics career opportunities.

Course FAQs

Q1: What is Google BigQuery?

A serverless, scalable data warehouse for analytics on Google Cloud.

Q2: Who should learn BigQuery?

Data analysts, data engineers, BI developers.

Q3: Is SQL required?

Yes, SQL is essential for querying data in BigQuery.

Q4: Can BigQuery handle large datasets?

Yes, it’s designed for petabyte-scale data.

Q5: What visualization tools integrate with BigQuery?

Looker Studio, Connected Sheets, Power BI, Tableau.

Q6: Does BigQuery support machine learning?

Yes, via BigQuery ML for in-database ML capabilities.

Q7: How does BigQuery secure data?

Through role-based access control and data encryption.

Q8: Can I use BigQuery for real-time analytics?

Yes, with streaming data ingestion.

Q9: Is BigQuery cost-effective?

It offers flexible pricing based on storage and query usage.

Q10: What careers benefit from BigQuery skills?

Data Analyst, Data Engineer, BI Developer, Data Scientist.

Q11: What are Nested and Repeated fields, and why are they used?

Nested and repeated fields utilize JSON-like arrays directly inside database columns. This eliminates the need to constantly execute slow, expensive JOIN commands across multiple large tables, optimizing big data processing efficiency.

Q12: Can a traditional business or Excel analyst transition into this role?

Absolutely. This course is specifically built to help traditional analysts upscale their capabilities into modern cloud architecture. We expand your baseline SQL skills into enterprise big data engineering, data warehousing, and cloud analytics.

Q13: Will we learn how to connect BigQuery to visualization dashboards?

Yes. Storing data is only half the battle. You will master connecting your analytical data structures directly to visualization suites like Looker Studio, Power BI, and Tableau to stream interactive reports to corporate stakeholders.