Data Fusion

 

Azure Cloud Data Engineering Training in Hyderabad – Quality Thoughts

Quality Thoughts offers one of the best Azure Cloud Data Engineering courses in Hyderabad, ideal for graduates, postgraduates, working professionals, or career switchers. The course combines hands-on learning with an internship to make you job-ready in a short time.

Our expert-led training goes beyond theory, with real-time projects guided by certified cloud professionals. Even if you’re from a non-IT background, our structured approach helps you smoothly transition into cloud roles.

The course includes labs, projects, mock interviews, and resume building to enhance placement success.

Why Choose Us?

     1. Live Instructor-Led Training

     2. Real-Time Internship Projects

     3.Resume & Interview Prep

    4 .Placement Assistance

    5.Career Transition Support

Join us to unlock careers in cloud data engineering. Our alumni work at top companies like TCS, Infosys, Deloitte, Accenture, and Capgemini.

Note: Azure Table and Queue Storage support NoSQL and message handling for scalable cloud apps

Data Fusion

Cloud Data Fusion is Google Cloud’s fully managed, no-code/low-code ETL (Extract, Transform, Load) service for building and managing data integration pipelines. It lets you visually design pipelines or use code, and supports both batch and real-time data processing. Built on the open-source CDAP (Cask Data Application Platform), it connects to various data sources and sinks seamlessly.

Key Features:

Drag-and-drop visual pipeline designer.

Pre-built connectors for BigQuery, Cloud Storage, Pub/Sub, relational DBs, SaaS apps, and more.

Built-in transformations for cleansing, joining, aggregating, and enriching data.

Supports on-prem, cloud, and hybrid data integration.

Pipeline lifecycle management: versioning, scheduling, and monitoring.

Scales automatically using underlying Dataflow or Dataproc engines.

Use Cases:

Data migration from legacy systems to cloud.

Building ETL/ELT workflows for analytics.

Real-time ingestion from streaming sources.

Data preparation for AI/ML pipelines.

Best Practices:Use pipeline modularity for reusability, optimize data formats (e.g., Parquet, Avro), and leverage error handling to manage bad records.

Cloud Data Fusion simplifies and accelerates data integration, enabling faster analytics and decision-making without deep coding expertise.

Read More

Cloud Composer (Apache Airflow)

Cloud Dataproc (Apache Spark/Hadoop)

Cloud Dataflow (Apache Beam)


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