# Building Data Lakes on AWS Review (2026): 7.6/10 · Coursera · Paid > Independent review of Building Data Lakes on AWS on Coursera. Rated 7.6/10 by our editorial team. Pros, cons, price, and top alternatives. Certificate availa… Building Data Lakes on AWS ![Building Data Lakes on AWS](/api/media/file/hero/building-data-lakes-on-aws-course.webp?v=2?width=800) # Building Data Lakes on AWS Course — Review (7.6/10) Building Data Lakes on AWS offers a solid foundational understanding of AWS-based data lake design, ideal for those new to cloud data architectures. The course effectively combines theory with a pract... Explore This Course 🎟️ Coursera Discount Offer Explore This Course Building Data Lakes on AWS is a 6 weeks online beginner-level course on Coursera by Amazon Web Services that covers cloud computing. Building Data Lakes on AWS offers a solid foundational understanding of AWS-based data lake design, ideal for those new to cloud data architectures. The course effectively combines theory with a practical lab using AWS Lake Formation, though it assumes some prior familiarity with AWS services. While concise and well-structured, learners seeking deeper technical dives may need supplementary resources. Overall, it's a valuable starting point for aspiring cloud data professionals. We rate it 7.6/10. ## Prerequisites No prior experience required. This course is designed for complete beginners in cloud computing. ## Pros - Clear, structured introduction to AWS data lake concepts for beginners - Hands-on lab with AWS Lake Formation provides practical experience - Official AWS content ensures alignment with current best practices - Covers key services like Athena, Glue, and Lake Formation comprehensively ## Cons - Limited depth in advanced data governance and security configurations - Assumes basic AWS knowledge; may challenge absolute beginners - Few real-world troubleshooting scenarios or performance optimization tips ## Building Data Lakes on AWS Course Review Platform: Coursera Instructor: Amazon Web Services Updated May 4, 2026·Editorial Standards·How We Rate ## What will you learn in Building Data Lakes on AWS course - Understand the fundamental architecture and components of a data lake on AWS - Learn how to ingest and catalog data from various sources into a centralized repository - Prepare and transform raw data for analytics using AWS Glue and other tools - Query structured and unstructured data using Amazon Athena - Build and secure a production-ready data lake using AWS Lake Formation ### Program Overview ### Module 1: Introduction to Data Lakes 1 week - What is a data lake? - Benefits of data lakes vs. traditional data warehouses - Core AWS services involved in data lake architecture ### Module 2: Data Ingestion and Cataloging 2 weeks - Using AWS Glue for ETL workflows - Setting up data crawlers and data catalogs - Connecting data sources like S3, RDS, and on-premises databases ### Module 3: Data Preparation and Transformation 2 weeks - Cleaning and structuring raw data - Partitioning and compressing data for performance - Applying schema to semi-structured data ### Module 4: Querying and Securing the Data Lake 2 weeks - Using Amazon Athena for SQL-based querying - Implementing access controls with AWS Lake Formation - Hands-on lab: building an end-to-end data lake ### Get certificate #### Job Outlook - High demand for cloud data engineers and AWS specialists in enterprise environments - Skills applicable to roles in data architecture, cloud infrastructure, and analytics engineering - Certification strengthens credibility for cloud-focused data projects ## Editorial Take Building Data Lakes on AWS, offered through Coursera by Amazon Web Services, serves as a practical entry point for learners aiming to understand cloud-native data storage architectures. This course targets individuals with foundational knowledge of data systems but little exposure to AWS-specific implementations. It delivers a streamlined path from concept to hands-on implementation, focusing on real-world tools used in enterprise environments. ### Standout Strengths - Official AWS Curriculum: Developed by Amazon Web Services, the content reflects industry standards and real-world use cases. This ensures learners gain skills directly applicable to production environments. - Hands-On Lab Experience: The capstone lab using AWS Lake Formation allows learners to build a functional data lake. This practical component reinforces theoretical concepts and boosts confidence in using AWS tools. - Clear Module Progression: The course follows a logical flow from data ingestion to querying, making complex topics digestible. Each module builds on the last, supporting gradual skill development. - Focus on Core AWS Services: Learners gain proficiency in key services like Amazon Athena, AWS Glue, and S3. These are foundational for cloud data engineering roles and widely used across industries. - Integration with AWS Ecosystem: The course emphasizes how services work together, such as Glue crawlers populating the data catalog used by Athena. This systems-thinking approach is crucial for real-world deployments. - Beginner-Friendly Pacing: Designed for foundational learners, the course avoids overwhelming jargon and provides clear explanations. This makes it accessible to those transitioning into cloud data roles from other IT domains. ### Honest Limitations - Limited Depth in Security: While access controls are introduced, the course doesn’t deeply explore fine-grained permissions or data encryption strategies. Advanced learners may find this insufficient for enterprise compliance needs. - Assumes Prior AWS Knowledge: The course presumes familiarity with core AWS services and the console interface. Absolute beginners may struggle without supplementary AWS fundamentals training. - Few Real-World Edge Cases: Scenarios like handling schema drift, large-scale partitioning issues, or cost overruns are not covered. These omissions limit preparedness for production challenges. - Short on Performance Optimization: There’s minimal discussion on query optimization, partitioning strategies, or cost-efficient storage tiers. These are critical for scalable data lake implementations. ### How to Get the Most Out of It - Study cadence: Dedicate 3–4 hours per week consistently to absorb concepts and complete labs. Spacing out sessions helps retain complex service interactions and workflows. - Parallel project: Apply concepts by building a personal data lake with public datasets. This reinforces learning and creates a tangible portfolio piece for job applications. - Note-taking: Document each step of the Lake Formation lab, including error messages and fixes. These notes become valuable references for future cloud projects. - Community: Join AWS forums and Coursera discussion boards to troubleshoot issues. Engaging with peers exposes you to diverse problem-solving approaches and real-world tips. - Practice: Re-run labs with different data sources or file formats. Experimenting with JSON, CSV, and Parquet deepens understanding of data type handling and performance. - Consistency: Complete modules in sequence without long breaks. The course builds on prior knowledge, so continuity ensures better comprehension of integrated workflows. ### Supplementary Resources - Book: 'AWS Certified Data Analytics – Specialty Study Guide' expands on course topics with deeper technical insights and exam-focused practice. - Tool: Use AWS Free Tier to experiment beyond lab constraints. This allows safe exploration of service limits, costs, and configurations. - Follow-up: Enroll in AWS's 'Data Engineering on AWS' course for advanced ETL, streaming, and automation techniques. - Reference: AWS Documentation for Glue, Athena, and Lake Formation provides up-to-date API details and best practices not covered in the course. ### Common Pitfalls - Pitfall: Skipping the lab setup steps can lead to permission errors. Ensuring correct IAM roles and bucket policies is essential for lab success. - Pitfall: Misunderstanding partitioning can degrade query performance. Learners should practice organizing data by date or category to optimize Athena scans. - Pitfall: Overlooking data format choices may increase storage costs. Converting raw CSV to columnar Parquet reduces costs and improves query speed. ### Time & Money ROI - Time: At 6 weeks with 3–5 hours weekly, the time investment is reasonable for foundational cloud data skills. Completion fits well within a month. - Cost-to-value: As a paid course, it offers moderate value. The hands-on lab justifies the cost, though free AWS tutorials cover some overlapping content. - Certificate: The Coursera certificate adds credibility, especially when paired with AWS certifications. It signals practical engagement with AWS tools. - Alternative: Free AWS Digital Training offers similar content but lacks structured labs. This course is worth the price for learners wanting guided practice. ### Editorial Verdict Building Data Lakes on AWS is a well-structured, beginner-friendly course that delivers on its promise to introduce core data lake concepts within the AWS ecosystem. The integration of Amazon Athena, AWS Glue, and Lake Formation provides learners with a realistic workflow used in modern data engineering. While it doesn’t dive into advanced topics like machine learning integration or real-time streaming, it lays a solid foundation for further specialization. The hands-on lab is a standout feature, offering practical experience that many theoretical courses lack. However, the course’s brevity means some critical areas—like security, cost management, and performance tuning—are only touched upon. Learners aiming for production-level expertise will need to supplement with official AWS documentation or advanced training. That said, for its target audience—those new to AWS data services—it strikes a good balance between accessibility and technical relevance. If you're planning a career in cloud data engineering or need to understand AWS data lake architecture for your role, this course is a worthwhile investment. Pair it with hands-on practice and follow-up learning to maximize long-term value. ## How Building Data Lakes on AWS Compares | Course | Platform | Rating | Level | Duration | | --- | --- | --- | --- | --- | | Building Data Lakes on AWS | Coursera | 7.6/10 | Beginner | 6 weeks | | Google Cloud Generative AI Leader - Mock Exams [Apr'26] Course | Udemy | 9.8/10 | N/A | N/A | | Microsoft Azure Fundamentals AZ-900 Practice [Exams 2026] Course | Udemy | 9.8/10 | N/A | N/A | | Practice Exams \| AWS Certified Developer Associate 2024 Course | Udemy | 9.8/10 | N/A | N/A | ## Who Should Take Building Data Lakes on AWS? This course is best suited for learners with no prior experience in cloud computing. It is designed for career changers, fresh graduates, and self-taught learners looking for a structured introduction. The course is offered by Amazon Web Services on Coursera, combining institutional credibility with the flexibility of online learning. Upon completion, you will receive a course certificate that you can add to your LinkedIn profile and resume, signaling your verified skills to potential employers. If you are exploring adjacent fields, you might also consider courses in Agile & Scrum Courses, AI Courses, Arts and Humanities Courses, which complement the skills covered in this course. ### Career Outcomes - Apply cloud computing skills to real-world projects and job responsibilities - Qualify for entry-level positions in cloud computing and related fields - Build a portfolio of skills to present to potential employers - Add a course certificate credential to your LinkedIn and resume - Continue learning with advanced courses and specializations in the field ## More Cloud Computing Courses on Coursera Explore other highly rated courses in cloud computing available on Coursera to expand your learning path: - Preparing for Google Cloud Certification: Cloud Security Engineer Professional Certificate Course 9.8/10 - Preparing for Google Cloud Certification: Cloud DevOps Engineer Professional Certificate Course 9.8/10 - AWS Cloud Solutions Architect Professional Certificate Course 9.8/10 - AWS Cloud Technology Consultant Professional Certificate Course 9.8/10 - Architecting with Google Kubernetes Engine en Español Specialization Course 9.8/10 - IBM DevOps and Software Engineering Professional Certificate Course 9.7/10 - AWS Fundamentals Specialization Course 9.7/10 - Preparing for Google Cloud Certification: Cloud Developer Professional Certificate Course 9.7/10 - AWS Cloud Support Associate Professional Certificate Course 9.7/10 - Digital Transformation Using AI/ML with Google Cloud Specialization Course 9.7/10 ## Top Alternatives on Other Platforms Looking for a different teaching style or approach? These top-rated cloud computing courses from other platforms cover similar ground: - Google Cloud Generative AI Leader - Mock Exams [Apr'26] Course 9.8/10 Udemy - Microsoft Azure Fundamentals AZ-900 Practice [Exams 2026] Course 9.8/10 Udemy - Practice Exams | AWS Certified Developer Associate 2024 Course 9.8/10 Udemy - DP-900 Azure Data Fundamentals Exam Prep In One Day Course 9.7/10 Udemy - GIT and Visual Studio with Azure DevOps Repos for Developers Course 9.7/10 Udemy - Microsoft Azure: From Zero to Hero – The Complete Guide Course 9.7/10 Udemy - Practice Exams | AWS Certified Solutions Architect Associate Course 9.7/10 Udemy - Introduction to AWS – Understand AWS basics in 3 hours! Course 9.7/10 Udemy - Azure Fundamentals: AZ-900 Certification +Practice Questions Course 9.7/10 Udemy - AI-900 Microsoft Azure AI Fundamentals Certification Course 9.7/10 Udemy ## More Courses from Amazon Web Services Amazon Web Services offers a range of courses across multiple disciplines. If you enjoy their teaching approach, consider these additional offerings: - AWS Cloud Technology Consultant Professional Certificate Course 9.8/10 - AWS Cloud Solutions Architect Professional Certificate Course 9.8/10 - DeepLearning.AI Data Engineering Professional Certificate Course 9.8/10 - AWS Cloud Technical Essentials Course 9.7/10 - AWS Cloud Support Associate Professional Certificate Course 9.7/10 - AWS Cloud Practitioner Essentials Course 9.7/10 - Amazon Junior Software Developer Professional Certificate Course 9.7/10 - AWS Fundamentals Specialization Course 9.7/10 View all courses from Amazon Web Services → ## Related Articles & Guides Deepen your understanding with these articles from our editorial team, covering career advice, industry trends, and learning strategies: - Build AI skills with the Google AI Professional Certificate - Python Tutorial: Best Courses to Learn Python in 2026 - CISSP vs CompTIA Security+: Which Cert Should You Pursue? - Coursera Data Analytics Professional Certificate: Worth It in 2026? - Best edX Courses in 2026: Top Picks by Enrollment and Career Value - Best Online Coursera Courses in 2026: What's Actually Worth Your Time - Udemy Online: What the Platform Actually Delivers in 2026 - OKR for Leaders: 7 Best Training Courses Compared (2026) - Generative AI for Marketing with Microsoft 365 Copilot: Professional Certificate Review - The Best React Courses in 2026, Ranked and Reviewed ## Explore All Course Categories Not sure what to learn next? 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Be the first to share your experience! ## FAQs What are the prerequisites for Building Data Lakes on AWS? No prior experience is required. Building Data Lakes on AWS is designed for complete beginners who want to build a solid foundation in Cloud Computing. It starts from the fundamentals and gradually introduces more advanced concepts, making it accessible for career changers, students, and self-taught learners. Does Building Data Lakes on AWS offer a certificate upon completion? Yes, upon successful completion you receive a course certificate from Amazon Web Services. This credential can be added to your LinkedIn profile and resume, demonstrating verified skills to employers. In competitive job markets, having a recognized certificate in Cloud Computing can help differentiate your application and signal your commitment to professional development. How long does it take to complete Building Data Lakes on AWS? The course takes approximately 6 weeks to complete. It is offered as a paid course on Coursera, which means you can learn at your own pace and fit it around your schedule. The content is delivered in English and includes a mix of instructional material, practical exercises, and assessments to reinforce your understanding. Most learners find that dedicating a few hours per week allows them to complete the course comfortably. What are the main strengths and limitations of Building Data Lakes on AWS? Building Data Lakes on AWS is rated 7.6/10 on our platform. Key strengths include: clear, structured introduction to aws data lake concepts for beginners; hands-on lab with aws lake formation provides practical experience; official aws content ensures alignment with current best practices. Some limitations to consider: limited depth in advanced data governance and security configurations; assumes basic aws knowledge; may challenge absolute beginners. Overall, it provides a strong learning experience for anyone looking to build skills in Cloud Computing. How will Building Data Lakes on AWS help my career? Completing Building Data Lakes on AWS equips you with practical Cloud Computing skills that employers actively seek. The course is developed by Amazon Web Services, whose name carries weight in the industry. The skills covered are applicable to roles across multiple industries, from technology companies to consulting firms and startups. Whether you are looking to transition into a new role, earn a promotion in your current position, or simply broaden your professional skillset, the knowledge gained from this course provides a tangible competitive advantage in the job market. Where can I take Building Data Lakes on AWS and how do I access it? Building Data Lakes on AWS is available on Coursera, one of the leading online learning platforms. You can access the course material from any device with an internet connection — desktop, tablet, or mobile. The course is paid, giving you the flexibility to learn at a pace that suits your schedule. All you need is to create an account on Coursera and enroll in the course to get started. How does Building Data Lakes on AWS compare to other Cloud Computing courses? Building Data Lakes on AWS is rated 7.6/10 on our platform, placing it as a solid choice among cloud computing courses. Its standout strengths — clear, structured introduction to aws data lake concepts for beginners — set it apart from alternatives. What differentiates each course is its teaching approach, depth of coverage, and the credentials of the instructor or institution behind it. We recommend comparing the syllabus, student reviews, and certificate value before deciding. What language is Building Data Lakes on AWS taught in? Building Data Lakes on AWS is taught in English. Many online courses on Coursera also offer auto-generated subtitles or community-contributed translations in other languages, making the content accessible to non-native speakers. The course material is designed to be clear and accessible regardless of your language background, with visual aids and practical demonstrations supplementing the spoken instruction. Is Building Data Lakes on AWS kept up to date? Online courses on Coursera are periodically updated by their instructors to reflect industry changes and new best practices. Amazon Web Services has a track record of maintaining their course content to stay relevant. We recommend checking the "last updated" date on the enrollment page. Our own review was last verified recently, and we re-evaluate courses when significant updates are made to ensure our rating remains accurate. Can I take Building Data Lakes on AWS as part of a team or organization? Yes, Coursera offers team and enterprise plans that allow organizations to enroll multiple employees in courses like Building Data Lakes on AWS. Team plans often include progress tracking, dedicated support, and volume discounts. This makes it an effective option for corporate training programs, upskilling initiatives, or academic cohorts looking to build cloud computing capabilities across a group. What will I be able to do after completing Building Data Lakes on AWS? After completing Building Data Lakes on AWS, you will have practical skills in cloud computing that you can apply to real projects and job responsibilities. You will be prepared to pursue more advanced courses or specializations in the field. 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