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Coursera

Orchestrating Data Pipelines and Advanced Data Strategies

Packt via Coursera

Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Dive deep into modern data engineering with this comprehensive course that equips learners with practical skills in orchestrating complex data workflows and implementing advanced data strategies on AWS. You’ll gain hands-on experience with tools like AWS Step Functions, DMS, DataSync, and QuickSight to visualize, migrate, and manage data efficiently. The journey begins with mastering data visualization through Amazon QuickSight, where you’ll connect data sources and build dashboards. You'll then explore the core of the course—automating and orchestrating data pipelines using AWS tools like Glue Workflows and Step Functions, complete with real-world integrations and advanced capabilities. Next, you'll tackle large-scale data migrations, learning how to move data across platforms using AWS DMS, DataSync, and Transfer Family services. Finally, you'll go beyond standard analytics with services like Lambda, S3, RDS, EC2, and DynamoDB, enhancing your understanding of scalable cloud data architectures. This course is ideal for cloud engineers, data engineers, and IT professionals aiming to sharpen their AWS data skills. A basic understanding of AWS and data concepts is recommended. The difficulty level is Intermediate. By the end of the course, you will be able to orchestrate complex data workflows, migrate data across systems, implement cost-efficient storage strategies, and leverage serverless and cloud-native services to optimize data pipelines.

Syllabus

  • Visualize Your Data Using Amazon QuickSight
    • In this module, we will explore the core features of Amazon QuickSight, focusing on the fundamentals of data visualization. You will learn how to connect data sources, create dynamic dashboards, and integrate QuickSight with Amazon Athena for enhanced data insights. This section will lay the foundation for presenting your data effectively to drive decisions.
  • Orchestrating Your Data Pipeline
    • In this module, we will dive into the essentials of orchestrating your data pipeline with AWS tools. You’ll explore how to automate complex workflows using services like AWS Step Functions and AppFlow. Additionally, you will compare different orchestration tools to ensure the right choice for your data processing needs.
  • Data Migration Services in AWS
    • In this module, we will guide you through the various options for migrating your data to AWS. You will learn how to use AWS Database Migration Service (DMS), AWS DataSync, and other tools to seamlessly transfer both databases and large datasets. Additionally, we’ll cover key troubleshooting and validation practices to ensure your migration is efficient and error-free.
  • Going Beyond AWS Analytics Services
    • In this module, we will extend your analytics capabilities by exploring advanced AWS services. You’ll learn how to integrate AWS Lambda, Amazon S3, and DynamoDB into your analytics pipeline to enable serverless computing, cost-efficient data storage, and real-time data processing. This section empowers you to optimize your architecture and improve data scalability.
  • Final Note
    • In this module, we will wrap up the course with final thoughts and practical guidance on advancing your data engineering skills. You will review key takeaways and get advice on further learning paths, enabling you to continue developing your expertise in AWS data engineering.

Taught by

Packt - Course Instructors

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