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Empower Data. Simplify Integration. Accelerate Insights.
The Data Engineering with Snowflake Program at JVSIT & TGS Training Institute is a job-oriented course designed to help you master the modern cloud data platform Snowflake. Learn how to design, build, and optimize scalable data pipelines, integrate diverse data sources, and deliver high-performance analytics solutions on the cloud.
This program takes you from data fundamentals to advanced Snowflake engineering concepts, preparing you for global opportunities as a Data Engineer, Cloud Data Developer, or Snowflake Specialist.
8th October
07:00 AM TO 08:00 AM
80-100 Days
Training
At JVSIT & TGS Training Institute, our Data Engineering with Snowflake Program blends data integration, transformation, and automation into a single, hands-on learning experience. You’ll gain real-world exposure to building ETL pipelines, query optimization, and data architecture design using Snowflake, SQL, and cloud platforms like Azure and GCP.
Whether you’re a beginner or an experienced data professional, this course will make you job-ready with hands-on projects, live mentorship, and placement support.
Day 1
Types of applications
Roles in software industry
Responsibilities of each role
Introduction to What WG
Day 2
Software development life cycles
Types of SDLC
Day 3
Water Fall Model
V Model
Circler Model
Day 4
Agile Model
Domain choosing
Project choosing
Modules and functionalities finding
Day – 5
Introduction to UI-UX
Introducing FIGMA tool
Day – 6
Optimal design principles of database, business logic
Time and Space complexity
Day 7
GitHub with sample HTML page
Creating Repos
Creating LinkedIn account
Day 8
Difference between platform and domain
Requirement gathering for 2 real time scenarios using Agile
Day 9
Deployment methods on hostings
Knowledge about servers and load balancers
Day 10
Power of AI and prompting (webinar)
Using Copilot tool
Using ChatGPT
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Form tags and Attributes
MultiMedia tags
Assignment – Naasongs.
Assignment – Sample login, register, forgot password pages
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Hibernate and Spring
Day – 1
1.Introduction to Spring Boot
2.Setting Up Spring Boot and Creating a Basic Program
If you need the sample Spring Boot application code as text:
java
}
Day – 2
text
// Sample application.properties
spring.datasource.url=jdbc:h2:mem:testdb
spring.jpa.hibernate.ddl-auto=update
Day – 3
text
// Sample Actuator Configuration
management.endpoints.web.exposure.include=health
Day – 4
java
// Sample JPA Entity
@Entity
public class User {
@Id
@GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
private String name;
// getters and setters
}
Day – 5
java
// Sample Security Configuration
@Configuration
@EnableWebSecurity
public class SecurityConfig extends WebSecurityConfigurerAdapter {
@Override
protected void configure(HttpSecurity http) throws Exception {
http
.csrf().disable()
.authorizeRequests()
.antMatchers(“/public/**”).permitAll()
.anyRequest().authenticated();
}
}
Day – 6
java
// Sample REST Controller
@RestController
@RequestMapping(“/api/users”)
public class UserController {
@GetMapping
public List getAllUsers() {
// return list of users
}
@PostMapping
public User createUser(@RequestBody User user) {
// create and return user
}
}
Day – 7
text
# Sample Dockerfile
FROM openjdk:11-jre-slim
COPY target/demo-0.0.1-SNAPSHOT.jar app.jar
ENTRYPOINT [“java”, “-jar”, “/app.jar”]
Day – 8
java
// Sample Eureka Server Configuration
@SpringBootApplication
@EnableEurekaServer
public class EurekaServerApplication {
public static void main(String[] args) {
Day – 9
java
// Sample Microservice Configuration
@SpringBootApplication
@EnableDiscoveryClient
public class MicroserviceApplication {
public static void main(String[] args) {
SpringApplication.run(MicroserviceApplication.class, args);
}
}
SpringApplication.run(EurekaServerApplication.class, args);
}
}
Day – 10
java
// Sample Asynchronous Method
@Service
public class MyService {
@Async
public CompletableFuture AsyncMethod() {
return CompletableFuture.completedFuture(“Async Result”);
}
}
Day – 11
text
# Sample Kubernetes Deployment YAML
apiVersion: apps/v1
kind: Deployment
metadata:
name: spring-boot-app
spec:
replicas: 2
selector:
matchLabels:
app: spring-boot-app
template:
metadata:
labels:
app: spring-boot-app
spec:
containers:
– name: spring-boot-app
image: spring-boot-app:latest
ports:
– containerPort: 8080
It’s a professional training program that teaches you how to design, manage, and optimize data pipelines and warehouses using Snowflake.
Students, data analysts, developers, and IT professionals aiming to build a career in cloud data engineering.
Basic knowledge of SQL and databases is helpful but not mandatory beginners can learn with guided support.
Snowflake fundamentals, SQL, ETL processes, cloud integrations, and performance optimization.
You’ll work with Snowflake, SQL, Python, Azure Data Factory, Databricks, and cloud platforms like AWS & GCP.
Empowering careers with tech and hands-on learning. 15,000+ trained, 10,000+ placed, 20+ global partners.
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