Best Software Training Institute in Hyderabad – Version IT

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GCP Data Engineer Training in Hyderabad

Google Cloud Platform (GCP) is a comprehensive cloud computing platform that offers a wide range of cloud-based services and solutions. It provides organizations with the tools and infrastructure needed to build, deploy, and scale applications efficiently. GCP enables businesses to leverage the power of Google’s infrastructure and technologies for enhanced performance and flexibility.

Why Learn GCP Data Engineer in Hyderabad?

In today’s data-driven world, organizations are increasingly relying on cloud-based solutions to manage and analyze their data effectively. GCP offers a robust ecosystem of data tools and services that empower businesses to store, process, and analyze large-scale datasets efficiently. By learning GCP data engineering, you gain the skills and knowledge to design, develop, and manage data pipelines, implement data processing systems, and build data solutions on the cloud. This expertise is in high demand, making GCP data engineering a rewarding career path.

Why Version IT for GCP Training?

Version IT is a leading GCP Data Engineer Training Institute in Hyderabad known for its comprehensive and industry-focused training programs. When it comes to GCP data engineer training, Version IT stands out for several reasons:

Experienced Trainers: Our trainers are industry experts with extensive experience in GCP data engineering. They provide practical insights and real-world examples to ensure a well-rounded learning experience.
Hands-on Approach: We believe in learning by doing. Our GCP data engineer training program offers hands-on exercises, projects, and case studies to help you apply the concepts you learn in a practical setting.
Comprehensive Curriculum: Our training curriculum is designed to cover all the essential concepts and skills required to become a proficient GCP data engineer. From data ingestion and storage to data processing and analysis, our program covers the entire data engineering lifecycle.

Learning Objectives in GCP Data Engineer Training

During our GCP data engineer training program, you will acquire a range of skills and knowledge, including:

  • Understanding the core concepts of GCP and its data-related services
  • Designing and implementing data storage solutions on GCP
  • Building and managing data pipelines using GCP tools like Dataflow and Dataproc
  • Applying data processing techniques with technologies like BigQuery and Cloud Pub/Sub
  • Integrating machine learning models and analytics solutions in GCP
  • Implementing security and compliance measures for data on GCP
  • Monitoring, troubleshooting, and optimizing data workflows on GCP

Who is Eligible to Learn GCP Data Engineer Training?

GCP data engineer training is suitable for professionals who are interested in working with data and want to leverage the power of the Google Cloud Platform. The following individuals can benefit from this training:

  • Data engineers and ETL developers looking to expand their skills to the cloud
  • Database administrators and data architects interested in cloud-based data solutions
  • Data analysts and scientists who want to learn data engineering on GCP
  • Software engineers and developers transitioning into the data engineering domain
  • IT professionals aiming to enhance their career prospects in the cloud computing industry
 

To make the most of our GCP data engineer training program, participants should have a basic understanding of data concepts, SQL, and programming languages like Python. Familiarity with cloud computing concepts and prior experience with any cloud platform would be beneficial but not mandatory.

Join Version IT’s Best GCP Training in Hyderabad to gain in-demand skills and accelerate your career in the exciting field of cloud-based data engineering.

Join Version IT’s Best GCP Training in Hyderabad to gain in-demand skills and accelerate your career in the exciting field of cloud-based data engineering.

Topics You will Learn

Introduction to Google Cloud Platform

● Google Cloud Platform (GCP) Infrastructure
● Using GCP
● Lab: Console and Cloud Shell
● Demo: Projects
● Lab: Infrastructure Preview

Virtual Machines

● Compute Engine
● Lab: Creating Virtual Machines
● Compute options (vCPU and Memory)
● Images
● Common Compute Engine actions
● Lab: Working with Virtual Machines

Autoscaling

● Autoscaling, Policies, Configuration
● Lab: Autoscaling

Load Balancing

● Managed Instance Groups
● HTTPS load balancing
● Cross-region and content-based load balancing
● SSL proxy/TCP proxy load balancing
● Network load balancing
● Lab: VM Automation and Load Balancing

Virtual Networks

● Virtual Private Cloud (VPC),
● Projects, Networks
● Subnetworks
● IP addresses
● Routes
● Firewall rules
● Subnetworks for resource management instead of physical network topology
● Lab: Virtual Networking
● Lab: Bastion Host

Interconnecting Networks

● Cloud Virtual Private Network (VPN)
● Lab: Virtual Private Networks (VPN)
● Cloud Router, Cloud Interconnect, External Peering, Cloud DNS

Cloud IAM

● Organizations
● Roles
● Members
● Service Accounts
● Cloud IAM best practices
● Lab: Cloud IAM

Data Storage Services

● Cloud Storage
● Lab: Cloud Storage
● Cloud SQL
● Lab: Cloud SQL
● Cloud Spanner, Cloud Datastore
● Cloud Bigtable

Resource Management

● Cloud Resource Manager
● Quotas
● Labels
● Names
● Billing
● Demo: Billing Administration
● Lab: Examining Billing Data with BigQuery

Resource Monitoring

● Stackdriver
● Monitoring
● Lab: Resource Monitoring (Stackdriver)
● Logging
● Error Reporting
● Tracing, Debugging
● Lab: Error Reporting and Debugging (Stackdriver)

Infrastructure Automation with Google Cloud Platform APIs

● Infrastructure automation
● Images
● Metadata
● Scripts
● Google Cloud API
● Lab: Google Cloud Platform API Infrastructure Automation

Infrastructure Automation with Deployment Manager

● Deployment Manager
● Configuration
● Cloud Launcher
● Lab: Deployment Manager

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FAQ's

A GCP Data Engineer is in charge of developing, constructing, and managing data processing systems on the Google Cloud Platform. Data storage, transformation, and analysis are examples of such jobs.

BigQuery (data warehouse), Cloud Storage (object storage), Dataflow (stream and batch processing), Dataprep (data preparation), and other data engineering services are available through GCP.

BigQuery is a serverless data warehouse that allows for quick SQL searches on massive datasets. BigQuery is used by Data Engineers for analytics, reporting, and ad-hoc querying.

Cloud Storage is Google Cloud Platform's object storage service. Cloud Storage is used by data engineers for scalable and long-term storage of raw and processed data, frequently as a data lake.

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