Copyright 2022
Designed by Ermin Systems.


Copyright 2022 ©
Designed by Ermin Systems.

Data Engineering on the Cloud

6 Weeks

Data Engineering on the Cloud

This six-week course is tailored for data professionals looking to specialize in cloud-based data engineering. Participants will explore how to leverage major cloud platforms such as AWS, Azure, and Google Cloud for data engineering tasks. The course covers the essentials of building and managing cloud data warehouses, utilizing cloud-native tools for data processing, and best practices for cloud data architecture.


Detailed Syllabus:


Week 1: Introduction to Cloud Data Engineering

  • Overview of cloud computing and its impact on data engineering.
  • Comparing key cloud platforms: AWS, Azure, and Google Cloud.
  • Setting up a cloud environment for data engineering tasks.


Week 2: Cloud Data Storage and Warehousing

  • Exploring cloud storage solutions: AWS S3, Azure Blob Storage, Google Cloud Storage.
  • Building and managing cloud data warehouses with Amazon Redshift, Google BigQuery, and Azure SQL Data Warehouse.
  • Best practices for data loading and extraction.


Week 3: Data Integration and ETL on the Cloud

  • Tools and services for data integration in the cloud: AWS Glue, Azure Data Factory, Google Dataflow.
  • Designing and implementing ETL pipelines in a cloud environment.
  • Managing data quality and consistency across distributed environments.


Week 4: Cloud-Native Data Processing

  • Leveraging serverless computing for data processing: AWS Lambda, Azure Functions, and Google Cloud Functions.
  • Batch and stream processing in the cloud with AWS EMR, Azure HDInsight, and Google Dataproc.
  • Introduction to orchestration with Apache Airflow in cloud environments.


Week 5: Advanced Analytics and Machine Learning on the Cloud

  • Integrating machine learning and advanced analytics into cloud data platforms.
  • Using AWS SageMaker, Azure ML Studio, and Google AI Platform for building and deploying ML models.
  • Real-world applications and case studies of cloud-based analytics.


Week 6: Security, Governance, and Compliance in Cloud Data Engineering

  • Understanding security best practices and compliance in the cloud.
  • Implementing data governance frameworks on cloud platforms.
  • Capstone Project: Designing a comprehensive cloud data solution addressing real-world business needs.


Learning Outcomes:

  • Master the fundamentals and advanced techniques of cloud data engineering across multiple platforms.
  • Develop skills in building, managing, and optimizing cloud data warehouses and data lakes.
  • Learn to integrate advanced analytics and machine learning into cloud-based data engineering workflows.


This course includes interactive lectures, hands-on lab sessions, and a comprehensive capstone project that challenges participants to design and implement a full-scale data solution on the cloud, emphasizing practical skills and real-world applications.

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