Who is in your network?

What Is ETI in AWS Data Engineering
AWS Data Engineering is at the heart of how modern organizations manage and use data in the cloud. With digital transformation driving massive volumes of information, businesses rely on scalable platforms to process, move, and make sense of their data. Amazon Web Services (AWS) offers a full suite of services that data engineers use to build efficient, secure, and automated pipelines. At the center of these workflows is the concept of ETI, which stands for Extract, Transform, and Ingest.
Whether you're building data lakes, preparing datasets for analytics, or enabling real-time reporting, understanding ETI is critical. It is one of the most foundational concepts in cloud-based data engineering. For professionals or students starting their journey, a solid grasp of ETI is essential, especially when enrolling in an AWS Data Analytics Training program that focuses on real-world scenarios.
What is ETI in AWS
ETI stands for Extract, Transform, and Ingest. It refers to the set of processes that move data from its original source to a destination where it can be analyzed or used by applications. These three steps form the core of modern data pipeline architecture.
Extract
This is the process of pulling raw data from various sources. These sources could include on-premises databases, APIs, log files, cloud applications, or even real-time IoT sensors. On AWS, extraction can be performed using services like AWS Glue Crawlers, AWS Database Migration Service (DMS), and simple file uploads to Amazon S3.
Transform
Once the data is extracted, it needs to be cleaned, formatted, and enhanced. This could involve removing duplicates, handling missing values, standardizing formats, or applying business logic. AWS offers services such as AWS Glue Jobs, AWS Lambda, and Amazon EMR to handle transformation at both small and large scales.
Ingest
After transformation, the data is ingested into a storage system or a destination service where it becomes accessible for analytics and reporting. This destination could be a data warehouse like Amazon Redshift, a data lake on Amazon S3, or a streaming platform like Amazon Kinesis. Ingestion ensures that data flows continuously and is ready for real-time or batch use cases.
For those pursuing an AWS Data Engineer online course, ETI is usually introduced early in the curriculum. Understanding how these stages function independently and together allows learners to design more effective data workflows. Courses often include hands-on projects using AWS tools, helping students practice building pipelines that extract, transform, and ingest real datasets.
ETI vs ETL and ELT
Many people are familiar with ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), but ETI is subtly different and more aligned with cloud-native architectures.
ETL is a traditional method used when transformations happen before data is stored. It is common in legacy systems where storage is expensive or limited.
ELT is more modern and used in systems where large volumes of data are loaded first and transformed later within the data warehouse.
ETI separates ingestion as a distinct phase. This distinction matters in real-time applications, where data is not simply loaded once but flows constantly into the system. With ETI, the ingestion step can involve continuous streaming and synchronization, which is increasingly important in today’s fast-moving data environments.
AWS Services Supporting ETI
AWS provides an ecosystem of tools that work together to implement ETI pipelines.
For Extraction
• AWS Glue Crawlers detect and catalog data
• AWS DMS moves data from traditional databases to the cloud
• Amazon S3 supports scalable data uploads
For Transformation
• AWS Glue Jobs allow complex data reshaping
• AWS Lambda performs real-time, lightweight transformations
• Amazon EMR handles large-scale processing using Spark or Hadoop
For Ingestion
• Amazon Kinesis Firehose streams data directly into storage
• Amazon Redshift offers fast access for structured data
• Amazon S3 serves as a scalable and reliable data lake
Each service can operate independently or as part of a larger pipeline, offering flexibility for different data workloads.
Professionals who undertake AWS Data Engineering training often work with these services as part of their capstone projects. Hyderabad, being a tech hub, offers many opportunities to gain real-time experience with AWS tools in industry-relevant environments. From smart city data collection to financial analytics, ETI is implemented in projects that mirror actual business challenges.
Real-World Example of ETI
Imagine a logistics company that tracks delivery trucks using GPS. The company wants to analyze routes in real time to optimize delivery times.
• Extract: GPS data is sent from each vehicle to AWS IoT Core or Amazon Kinesis
• Transform: AWS Lambda functions process this data to calculate speed, delays, and route deviations
• Ingest: The processed data is ingested into Amazon Redshift for dashboards and reports, allowing managers to make real-time decisions
This pipeline demonstrates how ETI enables not just data management but real business outcomes.
Why ETI Matters Today
In today’s data-driven world, timely access to accurate information is a competitive advantage. ETI ensures that data moves efficiently through the stages of collection, preparation, and storage. It also supports use cases like machine learning, fraud detection, real-time alerts, and predictive analytics.
Unlike older systems that rely on batch processing, ETI supports both batch and streaming, making it ideal for modern applications. By learning how to build ETI pipelines using AWS services, data engineers can create solutions that are scalable, reliable, and fast.
Conclusion
ETI is more than just a technical process. It is a strategic approach to managing data in cloud environments. By separating extraction, transformation, and ingestion, organizations gain more control and flexibility in how they handle data. Whether you are just starting out or deepening your skills through an AWS Data Engineer online course, understanding ETI is essential.
As the demand for cloud-native data solutions continues to grow, mastering ETI will place you at the forefront of innovation. If you are considering AWS Data Engineering training in Hyderabad, make sure ETI is a key part of your learning journey.
TRANDING COURSES: AWS AI, CYPRESS, OPENSHIFT.
Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. For More Information about AWS Data Engineering Course Contact Call/WhatsApp: +91-7032290546 Visit: https://www.visualpath.in/onli....ne-aws-data-engineer

Top 10 Cypress Features Every Tester Should Know
Cypress has emerged as a powerful and developer-friendly testing tool that simplifies end-to-end testing for modern web applications. Whether you're a beginner in test automation or an experienced QA engineer, understanding Cypress can significantly enhance your testing productivity. If you're looking to master this tool, Cypress Training is the best place to start your journey.
Below are the top 10 features of Cypress that every tester should know:
1. Time Travel
Cypress offers a powerful "time travel" feature that captures snapshots at each step of your test execution. This allows testers to hover over each command in the Command Log to see what happened at that point in time. It’s an intuitive way to debug and verify test behavior with visual evidence.
2. Real-Time Reloads
One of Cypress’s standout features is its real-time reload capability. As soon as you make changes to your test files, the test runner automatically reloads and re-runs the tests. This drastically reduces feedback time and keeps your workflow seamless.
3. Automatic Waiting
Forget about manually adding waits or sleeps. Cypress intelligently waits for commands and assertions to pass before proceeding. This eliminates flakiness and improves the stability of your test cases.
4. Detailed Dashboard
Cypress provides a dashboard service that offers deeper insights into test runs. With real-time statistics, videos, screenshots, and logs, it becomes easier to pinpoint failures and optimize test performance.
5. Built-in Assertions
Cypress comes with built-in Chai assertions, eliminating the need for additional libraries. This simplifies writing tests and helps maintain cleaner, more readable code. You can validate the presence of elements, values, visibility, and more without any setup.
6. Stubbing and Mocking
Cypress makes it easy to stub and mock network requests using cy.intercept(). This is especially useful when you want to isolate your frontend tests from backend dependencies or simulate various server responses for negative testing.
7. Cross-Browser Testing
While Cypress initially supported only Chrome, it now supports Firefox and Microsoft Edge as well. This allows testers to ensure cross-browser compatibility without switching to other tools.
8. Great Developer Experience
Cypress is built with developers in mind. It’s written in JavaScript and runs in the same execution loop as the application being tested. This unique architecture gives Cypress full control over your app and makes debugging and development incredibly smooth.
9. Test Runner UI
Cypress offers a visual test runner that shows the status of each test case. You can watch the test run in real-time and get immediate feedback, which is invaluable during test development and troubleshooting.
10. CI/CD Integration
Cypress integrates smoothly with popular CI/CD tools like Jenkins, GitHub Actions, CircleCI, and GitLab. This allows you to run your test suite on every code push, ensuring rapid and safe deployments.
By this point, you’re probably wondering how to start using all these features effectively. The good news is, learning Cypress doesn’t require months of effort. With guided training and real-world projects, you can become proficient in just a few weeks. Especially if you’re located in Hyderabad, Cypress Training in Ameerpet offers in-depth courses that combine theory with hands-on practice.
Why Cypress Stands Out
Unlike traditional Selenium-based frameworks, Cypress runs directly in the browser, allowing it to provide native access to every object. This architectural choice results in faster test execution, more reliable test results, and a better developer experience.
Most importantly, Cypress tests are easy to write and maintain, which makes them suitable for Agile teams that follow continuous testing practices.
In India, there's a growing demand for Cypress experts, particularly as more companies shift towards modern front-end frameworks like React and Angular. If you're looking for a flexible and effective way to upskill, Cypress Online Training in India is a perfect choice. These programs cater to both beginners and professionals, offering remote access to top trainers and real-time projects.
Conclusion
Cypress is revolutionizing the way modern web applications are tested. With its developer-centric features, easy setup, and reliable performance, it’s no surprise that Cypress has become a favorite in the test automation community.
To summarize, the top features you should master are:
• Time Travel
• Real-Time Reloads
• Automatic Waiting
• Dashboard Insights
• Built-in Assertions
• Stubbing and Mocking
• Cross-Browser Testing
• Developer Experience
• Visual Test Runner
• CI/CD Integration
These features are not just checkboxes—they’re game changers that can transform your testing approach.
TRENDING COURSES: AWS AI, AWS DATA ENGINEERING, OPENSHIFT.
Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. For More Information about Cypress Training Online Contact Call/WhatsApp: +91-7032290546 Visit: https://www.visualpath.in/onli....ne-cypress-training-

What are OpenShift Operators and Why Use Them?
Introduction
OpenShift has revolutionized container orchestration by providing a platform that simplifies deployment, scaling, and management of containerized applications. One of its most powerful features is OpenShift Operators, which enhance automation and streamline complex tasks. If you are looking to master OpenShift, enrolling in an OpenShift Training Institute can help you gain in-depth knowledge and hands-on experience.
Understanding OpenShift Operators
OpenShift Operators are extensions of Kubernetes Operators, designed to automate the deployment, scaling, and management of applications within OpenShift clusters. They enable the encapsulation of complex operational knowledge into reusable software components, simplifying the management of stateful applications.
How Do OpenShift Operators Work?
Operators work by using Kubernetes Custom Resource Definitions (CRDs) and controllers to manage applications in a declarative manner. Instead of manually configuring resources, Operators allow administrators to define the desired state, and the Operator ensures that the system maintains this state. This automation reduces human intervention and minimizes errors.
Benefits of Using OpenShift Operators
1. Automation – Operators reduce the need for manual configurations, ensuring consistency across deployments.
2. Scalability – They make it easier to scale applications without downtime.
3. Reliability – Automated monitoring and self-healing capabilities enhance stability.
4. Simplified Management – By automating routine tasks, Operators allow DevOps teams to focus on innovation.
Why Use OpenShift Operators?
One of the biggest advantages of OpenShift Operators is their ability to handle complex applications with ease. They enable seamless application lifecycle management, making tasks like updates, backups, and failovers automated and reliable. If you want to deepen your expertise, an OpenShift Course Online can provide the skills required to efficiently use Operators.
Real-World Applications of OpenShift Operators
• Database Management: Automating tasks like backups and scaling for databases like PostgreSQL and MongoDB.
• Monitoring & Logging: Deploying tools like Prometheus and Elasticsearch without manual intervention.
• Security & Compliance: Ensuring consistent security policies across clusters.
How to Implement OpenShift Operators?
1. Identify the right Operator: Choose an Operator from the OpenShift OperatorHub that matches your application’s needs.
2. Install the Operator: Deploy the Operator using the OpenShift web console or CLI.
3. Define Custom Resources: Configure the Operator by specifying the desired application state.
4. Monitor and Scale: Use OpenShift’s monitoring tools to track performance and scale as needed.
Conclusion
OpenShift Operators provide a robust mechanism for automating application lifecycle management, improving scalability, and ensuring operational efficiency. Businesses and developers can leverage Operators to enhance productivity while maintaining high reliability. If you are in Hyderabad and want to advance your OpenShift skills, consider enrolling in OpenShift Training in Hyderabad to gain hands-on expertise and industry-relevant knowledge.
TRENDING COURSES: AWS AI , AWS DATA ENGNEERING , CYPRESS .
Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. For More Information about OpenShift Training
Contact Call/WhatsApp: +91-7032290546 Visit: https://www.visualpath.in/open....shift-online-trainin

What Are the Latest Innovations in AWS AI?
AWS AI: Transforming the Future of Artificial Intelligence
Artificial Intelligence (AI) has rapidly evolved, and AWS AI continues to lead the way with groundbreaking innovations. From machine learning advancements to AI-driven automation, AWS offers powerful tools to enhance business efficiency. For those looking to upskill, AWS AI Online Training is the best way to stay ahead in this fast-paced industry. Let’s explore the latest innovations in AWS AI and how they are shaping the future.
1. Amazon Bedrock: The Future of Generative AI
One of the most exciting advancements in AWS AI is Amazon Bedrock. This service allows businesses to build and scale generative AI applications without extensive expertise. It integrates with large language models (LLMs) from top AI research labs, enabling seamless deployment of AI-driven applications. Whether it’s content generation, chatbots, or personalized recommendations, Bedrock simplifies AI adoption. Those interested in learning more can benefit from an AI With AWS Training Course to understand these advancements better.
2. Amazon SageMaker: Smarter Machine Learning
Amazon SageMaker continues to revolutionize machine learning by making it more accessible. The latest updates include automatic data preprocessing, zero-ETL integration, and enhanced model monitoring. With these features, businesses can reduce AI development time while ensuring high performance. AI With AWS Online Training Institute in Ameerpet provides hands-on experience with SageMaker, helping professionals build and deploy AI models efficiently.
3. AWS CodeWhisperer: AI-Powered Coding Assistance
AWS CodeWhisperer is another groundbreaking innovation designed to help developers write better code with AI assistance. This tool provides real-time code suggestions based on natural language inputs, significantly improving coding speed and accuracy. As AI-driven development becomes mainstream, professionals enrolling in AWS AI Online Training can gain expertise in leveraging these tools for more efficient workflows.
4. Amazon Rekognition: Enhanced Image and Video Analysis
AWS has upgraded Amazon Rekognition with improved facial analysis, object detection, and content moderation. These enhancements make it a must-have tool for industries relying on computer vision, such as security, e-commerce, and healthcare. With deep learning models improving accuracy, businesses can now automate image recognition tasks with greater precision. Understanding these updates through an AI With AWS Training Course can provide a competitive edge in AI-powered image processing.
5. Amazon Transcribe and Translate: AI-Powered Language Services
Communication barriers are rapidly diminishing thanks to AWS AI’s advancements in language processing. Amazon Transcribe offers real-time speech-to-text conversion, while Amazon Translate provides seamless language translation services. These tools are now integrated with machine learning models for better accuracy and efficiency. Mastering these technologies through an AI With AWS Online Training Institute in Ameerpet can help professionals work with multilingual AI applications.
6. AWS HealthScribe: AI in Healthcare
AWS HealthScribe is a revolutionary AI tool designed for the healthcare industry. It automates medical documentation, reducing administrative workload and improving patient care. With AI-powered transcription and summarization, doctors can focus more on treatment rather than paperwork. Professionals in the healthcare sector can enhance their skills through AWS AI Online Training, learning to implement AI-driven healthcare solutions.
7. Amazon Lex: Smarter AI Chatbots
Amazon Lex is a conversational AI service that powers intelligent chatbots and voice assistants. The latest updates include better natural language understanding (NLU) and contextual awareness, making interactions more human-like. Businesses leveraging AI chatbots for customer support can now provide better experiences. By taking an AI With AWS Training Course, professionals can learn to build advanced AI chatbots with Amazon Lex.
8. AWS Inferentia2: High-Performance AI Chips
AWS has introduced Inferentia2, a next-generation AI chip designed to accelerate deep learning workloads. This hardware innovation enhances AI model inference while reducing costs, making large-scale AI deployments more efficient. Companies using AWS for AI workloads can significantly benefit from this upgrade. Enrolling in an AI With AWS Online Training Institute in Ameerpet can help professionals understand how to optimize AI performance using Inferentia2.
9. AWS Kendra: Smarter Enterprise Search
AWS Kendra has been enhanced with better machine learning algorithms, providing faster and more relevant search results within organizations. This AI-powered search engine helps businesses find crucial information quickly, improving productivity. Learning to integrate Kendra through AWS AI Online Training can be a valuable skill for IT professionals working with enterprise AI solutions.
10. Amazon Polly: More Natural AI Voices
Amazon Polly, AWS’s text-to-speech service, now offers improved voice synthesis, making AI-generated speech sound more natural. With enhancements in voice modulation and tone adaptation, Polly is widely used in e-learning, customer service, and accessibility applications. Professionals can explore these updates through an AI With AWS Training Course to develop AI-driven voice applications.
Conclusion
AWS AI continues to push the boundaries of innovation with tools that make AI adoption easier, faster, and more efficient. From generative AI with Amazon Bedrock to AI-powered coding with CodeWhisperer, these advancements are transforming industries. For those looking to build a career in AI, enrolling in an AI With AWS Online Training Institute in Ameerpet can provide hands-on experience with these latest innovations. As AI technology evolves, staying updated with AWS AI will open new opportunities in the ever-growing AI landscape.
TRENDING COURSES: AWS DATA ENGINEERING , CYPRESS , OPENSHIFT.
Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. For More Information about Aws Ai Certification Contact Call/WhatsApp: +91-7032290546 Visit: https://www.visualpath.in/onli....ne-aws-ai-course.htm

What’s the Easiest Way to Learn AWS Data Engineering?
Introduction
AWS Data Engineering is one of the most in-demand skills in today’s tech-driven world. Whether you are a beginner or an experienced professional, learning AWS Data Engineering can open doors to high-paying job opportunities. But where do you start? What is the easiest way to learn AWS Data Engineering? This guide will walk you through the best learning paths, resources, and AWS Data Engineering Training in Chennai to help you become an expert in no time.
1. Understand the Basics of Data Engineering
Before diving into AWS-specific tools, it is essential to grasp the fundamental concepts of Data Engineering. A solid foundation in databases, ETL (Extract, Transform, Load) pipelines, data warehousing, and data processing frameworks is necessary. You can start with a Data Engineering course in Hyderabad to learn these core concepts.
Key topics to focus on:
• SQL and NoSQL databases
• ETL pipelines and data transformation
• Data lakes and warehouses (Amazon Redshift, Snowflake, etc.)
• Cloud computing basics (AWS, Azure, Google Cloud)
2. Get Hands-On Experience with AWS Services
AWS offers multiple cloud-based services tailored for Data Engineering. To learn effectively, you need to get practical experience with these tools. Start by setting up a free AWS account and experiment with the following services:
• Amazon S3 – Storage for raw and processed data
• AWS Glue – Serverless ETL tool
• Amazon Redshift – Data warehousing service
• AWS Lambda – Serverless compute for automation
• Amazon Kinesis – Real-time data streaming
To deepen your understanding, enrolling in an AWS Data Engineering Course with hands-on labs and projects can accelerate your learning.
3. Take a Structured AWS Data Engineering Course
Self-learning is great, but structured training can significantly boost your progress. A well-designed AWS Data Engineering Course will provide a step-by-step approach, expert mentorship, and industry-relevant projects.
Some of the best ways to learn include:
• Online courses (Udemy, Coursera, LinkedIn Learning)
• Instructor-led training (AWS official training partners)
• Bootcamps & workshops (offered in major cities like Hyderabad and Chennai)
For those looking for in-person guidance, a Data Engineering course in Hyderabad or AWS Data Engineering Training in Chennai can provide immersive, real-world learning experiences.
4. Work on Real-World Projects
The best way to solidify your skills is by working on real-world data engineering projects. Here are some beginner-friendly project ideas:
• Building an ETL pipeline using AWS Glue
• Creating a data lake architecture with Amazon S3 and Athena
• Setting up a streaming data pipeline with Amazon Kinesis
• Data warehousing project using Amazon Redshift
By implementing these projects, you’ll gain practical knowledge that makes you job-ready.
5. Get Certified in AWS Data Engineering
AWS certifications validate your skills and increase your chances of getting hired. If you’re serious about a career in data engineering, consider these certifications:
• AWS Certified Data Analytics – Specialty
• AWS Certified Solutions Architect – Associate
• AWS Certified Big Data – Specialty
Many AWS Data Engineering Training in Chennai programs offer certification prep courses to help you pass these exams on your first attempt.
6. Join a Community & Stay Updated
Data Engineering is an evolving field. Join AWS communities, forums, and networking groups to stay updated on industry trends and best practices. Platforms like LinkedIn, GitHub, and Stack Overflow can help you connect with experts and potential employers.
Conclusion
The easiest way to learn AWS Data Engineering is by following a structured approach: understanding the basics, getting hands-on with AWS tools, enrolling in an AWS Data Engineering Course, working on projects, and getting certified. If you prefer in-person learning, consider a Data Engineering course in Hyderabad or AWS Data Engineering Training in Chennai for the best industry exposure.
TRANDING COURSES: AWS AI, CYPRESS, OPENSHIFT.
Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. For More Information about AWS Data Engineering Course Contact Call/WhatsApp: +91-7032290546 Visit: https://www.visualpath.in/onli....ne-aws-data-engineer