Key Features Of GCP Data Engineer Training In Hyderabad
Why Choose Us
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Ingesting Data from various sources (databases, APIs)
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Transforming and Cleaning Data
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Weekly Test + Weekend Doubt clearing class
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Comprehensive Curriculum
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Hands-On Training
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Expert Gen AI Coaches
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Free Demo Class
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100% Guaranteed Placement Assistance
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Free Interview preparation Sessions
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Flexible Learning Modes
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Project-Based Learning
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Affordable Fees
Course Content Of GCP Data Engineer Training In Hyderabad
Course Content
Designing Data Processing Systems
Security & Compliance: Implementing IAM, encryption, data loss prevention, and compliance measures.
Reliability & Fidelity: Data preparation, monitoring, disaster recovery, and ACID compliance.
Flexibility & Portability: Designing for multi-cloud, data governance, and migration strategies.
Data Migrations: Planning and executing migrations to Google Cloud using tools like BigQuery Data Transfer Service and Datastream.
Ingesting and Processing Data
Pipeline Planning: Defining data sources, transformation logic, and networking considerations.
Pipeline Building: Utilizing tools like Dataflow, Dataproc, Cloud Data Fusion, and BigQuery for data ingestion and transformation.
Deployment & Operationalization: Managing pipeline performance, cost, and scalability.
Storing the Data
Storage Systems: Choosing between BigQuery, Cloud SQL, Cloud Storage, Bigtable, and Firestore based on use cases.
Data Modeling: Designing data models, normalization, and data access patterns.
Data Lakes & Mesh: Implementing data lakes with tools like Dataplex and managing distributed data systems.
Preparing and Using Data for Analysis
Data Preparation: Optimizing data for analysis using BigQuery, including partitioning and clustering.
Data Visualization: Integrating with tools like Looker and Data Studio for data visualization.
SQL Proficiency: Writing complex queries for data analysis and reporting.
Maintaining and Automating Data Workloads
Monitoring & Troubleshooting: Using tools like Cloud Monitoring and Logging to oversee data systems.
Automation: Implementing automation for data workflows and pipeline management.
Failure Management: Designing systems for fault tolerance and data recovery.
Preparation Resources
Google Cloud SkillsBoost: Offers a structured learning path with hands-on labs.
Coursera: Provides a Professional Certificate in Data Engineering.
ProjectPro: Offers a course with practical projects on GCP data engineering.
Aakash.ai: Provides study materials and notes for the certification exam.
GCP Data Engineering
GCP Data Engineer Training in Hyderabad
Whether you're a student, a working professional, or a career switcher, our training programs are tailored to your needs. Join us and master data science with one of Hyderabad's top-rated institutes.
Typical GCP Data Engineering Workflow
Data engineering is the discipline of designing and building systems for collecting, storing, and analyzing data at scale. The goal is to create data pipelines that clean, transform, and organize raw data into usable formats for analytics and machine learning.
graph TD
A[Data Sources] –> B[Ingest with Pub/Sub or Storage]
B –> C[Process with Dataflow or Dataproc]
C –> D[Store in BigQuery or GCS]
D –> E[Analyze with SQL, Looker Studio]
E –> F[Serve to users / ML models]
Features List
Where is Used GCP Data Engineering ?
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Real-Time Analytics Spotify: Utilizes BigQuery and Dataflow to process user interactions and streaming metrics, enabling personalized recommendations and improved user engagement.
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Supply Chain Optimization The Home Depot: Implemented Cloud Pub/Sub and BigQuery for real-time inventory management, reducing stockouts and overstock situations
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IoT Data Processing Energy Sector: An energy company monitors thousands of IoT sensors in real-time to track equipment health and predict failures using Pub/Sub, Dataflow, and BigQuery
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Data Preparation and Transformation Data Engineering Teams: Leverage Dataform to automate ETL workflows, transforming raw data into structured formats for analysis in BigQuery.
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Healthcare Data Analysis NHANES-GCP: A framework built on GCP that automates data engineering tasks for the National Health and Nutrition Examination Survey, enabling reproducible machine learning analyses
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Common Use Cases ETL/ELT Pipelines: Automating the extraction, transformation, and loading of data from various sources into data warehouses.
Skills Required for GCP Data Engineers
Proficiency in SQL, Python, and Spark
Understanding of cloud architecture and data modeling
Experience with ETL, streaming, and data pipeline orchestration
Familiarity with DevOps tools (CI/CD, Terraform, CloudFormation)
Our Services
Provoke Trainings is a leading training provider in Hyderabad, offering a comprehensive range of online, offline, and corporate training solutions. We specialize in IT and business technologies, delivering industry-relevant courses designed to enhance practical skills and career readiness.
Online
- Basic to advanced level
- Daily recorded videos
- Live project included
- Course Material Dumps
- 100% Placement assistance
Offline
- Basic to advanced level
- Daily recorded videos
- Live project included
- Course Material Dumps
- 100% Placement assistance
Corporate
- Whatsapp Group Access
- Doubt Clearing Sessions
- Live project included
- Course Material Dumps
- 100% Placement assistance
"Transitioning from a Zonal Manager to a Data Scientist was a bold move, but Provoke Trainings made it seamless. The curriculum was comprehensive, and the hands-on projects were invaluable. I now apply advanced analytics daily to solve complex business problems.
Mahesgh Goud