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⇱ Orchestrating Data Pipelines and Advanced Data Strategies | Coursera

Orchestrating Data Pipelines and Advanced Data Strategies

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Orchestrating Data Pipelines and Advanced Data Strategies

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Design and automate data workflows using AWS Step Functions and Glue.

  • Visualize complex datasets interactively with Amazon QuickSight dashboards.

  • Migrate structured and unstructured data using AWS DMS, DataSync, and Snow Family.

  • Enhance analytics workflows with serverless services like Lambda, S3, and DynamoDB.

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Assessments

6 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Data Engineering on AWS - The Complete Training Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

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.

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.

What's included

3 videos2 readings1 assignment

3 videos•Total 38 minutes
  • Data Visualization•7 minutes
  • Getting Started•19 minutes
  • Integration with Amazon Athena•12 minutes
2 readings•Total 20 minutes
  • Introduction to the Course 'Orchestrating Data Pipelines and Advanced Data Strategies'•10 minutes
  • Full Specialization Resource•10 minutes
1 assignment•Total 15 minutes
  • Visualize Your Data Using Amazon QuickSight - Assessment•15 minutes

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.

What's included

7 videos1 assignment

7 videos•Total 49 minutes
  • Orchestrating Your Data Pipeline•9 minutes
  • Which One to Choose?•6 minutes
  • Amazon AppFlow•8 minutes
  • AWS Data Exchange•7 minutes
  • AWS Step Functions: Part 1•6 minutes
  • AWS Step Functions: Part 2•8 minutes
  • AWS Step Functions: Part 3•6 minutes
1 assignment•Total 15 minutes
  • Orchestrating Your Data Pipeline - Assessment•15 minutes

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.

What's included

11 videos1 assignment

11 videos•Total 143 minutes
  • A Note Before You Proceed•2 minutes
  • Migrating Your Databases to AWS•18 minutes
  • AWS DMS: Part 1•11 minutes
  • AWS DMS: Part 2•23 minutes
  • AWS DMS: Part 3•7 minutes
  • Migrating Your Data to AWS•4 minutes
  • AWS DataSync: Part 1•8 minutes
  • AWS DataSync: Part 2•24 minutes
  • AWS Transfer Family: Part 1•10 minutes
  • AWS Transfer Family: Part 2•17 minutes
  • AWS Snow Family•18 minutes
1 assignment•Total 15 minutes
  • Data Migration Services in AWS - Assessment•15 minutes

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.

What's included

18 videos1 assignment

18 videos•Total 114 minutes
  • A Note Before You Proceed•2 minutes
  • AWS Lambda: Important Features•5 minutes
  • AWS Lambda: Concurrency•7 minutes
  • AWS Lambda: Layers•6 minutes
  • AWS Lambda: VPC Connectivity•5 minutes
  • AWS Lambda: Permissions•5 minutes
  • Amazon S3: Encryption•5 minutes
  • Amazon S3: Glacier Storage Tiers•3 minutes
  • Amazon S3: Events Notification•4 minutes
  • Amazon S3: Lifecycle Policies•9 minutes
  • Amazon S3: Intelligent Tier•27 minutes
  • Amazon S3: Select•5 minutes
  • Amazon S3: Object Lambda•9 minutes
  • Amazon EC2: EBS Volumes•6 minutes
  • Amazon RDS: Performance Insights•3 minutes
  • Amazon DynamoDB: Streams•5 minutes
  • Amazon DynamoDB: Global Tables•4 minutes
  • Amazon DynamoDB: Auto Scaling•3 minutes
1 assignment•Total 15 minutes
  • Going Beyond AWS Analytics Services - Assessment•15 minutes

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.

What's included

1 video1 reading2 assignments

1 video•Total 1 minute
  • Final Note•1 minute
1 reading•Total 10 minutes
  • Conclusion to the Course 'Orchestrating Data Pipelines and Advanced Data Strategies'•10 minutes
2 assignments•Total 75 minutes
  • Full Course Assessment•60 minutes
  • Full Course Practice Assessment•15 minutes

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Frequently asked questions

“Orchestrating Data Pipelines and Advanced Data Strategies” is a comprehensive course designed to help learners understand how to build, automate, and optimize modern data workflows using AWS services. It’s relevant for data professionals looking to manage data efficiently, streamline analytics operations, and implement secure, scalable, and cost-effective data strategies in the cloud.

This course explores how to design and orchestrate data pipelines using a suite of AWS tools such as Step Functions, Glue Workflows, and AppFlow. It also delves into data visualization with Amazon QuickSight, data migration using AWS DMS, DataSync, and Snow Family, and advanced analytics through AWS Lambda, S3, EC2, RDS, and DynamoDB. By the end, learners gain practical experience in creating, automating, and optimizing data pipelines across diverse AWS environments.

After completing the course, you will be able to visualize data using Amazon QuickSight, automate end-to-end data pipelines with orchestration tools, migrate and manage large-scale datasets using AWS migration services, and leverage advanced AWS analytics tools to enhance performance, scalability, and security. You’ll also be capable of integrating multiple AWS services to support dynamic and data-driven business operations.

Basic knowledge of cloud computing concepts, databases, and data analytics is recommended before enrolling. Familiarity with AWS fundamentals such as S3, EC2, or Lambda will enhance your understanding, but the course content is structured to guide learners progressively through the technical topics.

This course is ideal for data engineers, cloud practitioners, and IT professionals who want to strengthen their AWS data management and orchestration skills. It is also suitable for analysts, developers, and architects interested in building scalable, automated data workflows in the AWS ecosystem.

The course consists of approximately 6 hours of video content. Depending on your learning pace and level of hands-on experimentation, it can typically be completed within a week.

Yes. Throughout the course, learners engage in practical demonstrations and guided exercises involving tools like QuickSight, AWS Step Functions, AWS DMS, and DataSync, enabling them to apply the concepts directly in simulated or real AWS environments.

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,