We are giving best offers for new students 25% discount this month
Cloud technology is reshaping the way businesses manage data, and Data Engineers are at the forefront of this transformation. This course will equip you with the skills to design, build, and manage data pipelines across AWS, GCP, and Azure. You’ll learn how to choose the right cloud service, implement scalable data architectures, and ensure data quality & governance in multi-cloud environments.
✅ Software Developers looking to specialize in data engineering
✅ Data Analysts wanting to transition into big data roles
✅ Cloud Engineers who want to expand their data expertise
✅ IT Professionals & Graduates interested in high-paying data careers
📌 AWS Data Engineering – Glue, Redshift, S3
📌 Google Cloud Data Engineering – BigQuery, Dataflow, Cloud Storage
📌 Azure Data Engineering – Synapse Analytics, Databricks, Data Factory
📌 Data Warehousing & Architecture – Modern cloud-based storage solutions
📌 ETL/ELT Pipelines – Automating data extraction, transformation & loading
📌 Data Governance & Security – Ensuring compliance, security, and quality
→ Role of a Data Engineer in cloud environments
→ Comparing AWS, GCP, and Azure for data engineering
→ AWS S3 & Redshift for scalable storage & analytics
→ Google Cloud Storage & BigQuery for big data processing
→ Azure Synapse Analytics & Data Lake for enterprise data solutions
→ Automating ETL/ELT processes with AWS Glue
→ Streaming data pipelines using GCP Dataflow & Pub/Sub
→ Data orchestration with Azure Data Factory
→ Apache Spark on Databricks for big data analytics
→ Using SQL & Python for data transformation
→ Implementing machine learning pipelines in the cloud
→ Building multi-cloud data pipelines
→ Optimizing performance & cost-efficiency
→ Ensuring data security & governance compliance