Build a Data Warehouse in AWS (Coursera)

Build a Data Warehouse in AWS (Coursera)
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Prior working experience with RDBMS, SQL, and AWS is recommended but optional for this course.
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Build a Data Warehouse in AWS (Coursera)
Embark on a transformative journey with our "Build a Data Warehouse in AWS" course, immersing yourself in the landscape of Amazon Redshift. This comprehensive course equips you with the essential skills not only to navigate but also to harness the full potential of this robust cloud-based data warehousing solution.

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

During this course, you will explore the applications of AWS data warehousing solutions and delve into its fundamentals. By the end of this course, you will be able to:

- Explore and understand the concepts of AWS Services used for Data Warehousing in AWS.

- Gain proficiency in creating and managing IAM users and groups, understanding IAM policies and roles, and applying this knowledge in practical, hands-on scenarios.

- Differentiate between traditional and cloud storage, operate Simple Storage Service, and understand various storage classes and versioning in AWS S3.

- Gain a solid understanding of Amazon Redshift and effectively utilize it for data warehousing needs.

- Effectively set up and managed a data warehouse using Amazon Redshift.

- Develop a thorough understanding and practical expertise in implementing ETL (Extract, Transform, Load) processes in Amazon Redshift.

- Acquire knowledge on monitoring and optimizing the performance of Amazon Redshift environments.

This course is designed for Data Engineers, Cloud Solution Architects, Data Analysts, Database Administrators (DBAs), Software Developers, and Engineers seeking to explore the AWS Data Warehouse and its applications.

Prior working experience with RDBMS, SQL, and AWS is recommended but optional for this course.

Begin an educational journey to learn about the Data Warehouse in AWS and its concepts for handling and analyzing large volumes of data.


What you'll learn

Working with AWS services, SQL, Data warehousing, Amazon Redshift, Amazon Redshift Serverless, Redshift Spectrum, and ETL in Amazon Redshift.


Syllabus


Introduction to AWS Services

Welcome to this module highlighting AWS essentials, encompassing the AWS Free Tier account, AWS Identity and Access Management (IAM), compute services, and storage services. Explore foundational aspects for account security, delve into IAM for access control, and discover compute and storage services for robust cloud solutions.


Empowering Data Warehousing using SQL and AWS

Welcome to this module, which focuses on AWS networking, databases, SQL overview, and data warehousing introduction. Explore AWS networking concepts, master database solutions on AWS, and grasp SQL fundamentals. Gain insights into data warehousing for efficient data management. Acquire skills to optimize AWS resources, ensuring robust data storage, protection, and sharing strategies.


Fundamentals of Amazon Redshift

Welcome to "Getting Started with Amazon Redshift", a comprehensive module designed for anyone interested in mastering Amazon Redshift, a powerful data warehousing solution. This module is structured in three main sections, each diving deep into various aspects of Amazon Redshift. In the first section, "Introduction to Amazon Redshift", we begin by exploring the foundational elements of Amazon Redshift, including its features, architecture, data processing flow, and the benefits it offers over other data warehousing solutions. Through a blend of theoretical knowledge and practical insights, this section provides a solid understanding of why organizations prefer Amazon Redshift for their data warehousing needs. Moving on to the second section, "Classification of Amazon Redshift", we will delve into the specifics of Amazon Redshift Serverless and provisioned clusters. Here, you'll learn about the architecture of both serverless and provisioned clusters, and understand their comparative advantages. This section includes real-world case studies, highlighting how different organizations effectively use Amazon Redshift Serverless and Provisioned Clusters in diverse scenarios. The final section, "Key Elements in Amazon Redshift", focuses on the technical components like clusters, nodes, serverless workgroups, and columnar storage. Special emphasis is placed on security aspects and managing users and groups within Amazon Redshift. We also discuss the advantages of columnar storage over traditional row-based storage, particularly in terms of query performance and data compression. This module is ideal for Data Professionals, Project Managers, Database Administrators, and Business Analysts looking to deepen their understanding of data warehousing with Amazon Redshift. Whether you are a fresher or have some experience with AWS services, this module will enhance your skills and knowledge, preparing you for practical application in real-world scenarios. By the end of this module, you will have a fundamental understanding of Amazon Redshift and its key elements. The journey culminates in a comprehensive assessment to consolidate your learning and proficiency in the subject. Embark on this educational journey to gain a thorough understanding of Amazon Redshift, equipping yourself with the skills to leverage this powerful tool in your data warehousing and analytics projects.


Build a Data Warehouse in Amazon Redshift

Welcome to the "Build a Data Warehouse in Amazon Redshift" module. This comprehensive program is meticulously crafted to guide you through the nuances of setting up and managing a data warehouse in Amazon Redshift. Throughout this journey, you will acquire hands-on skills in configuring AWS Secrets Manager, creating a Key Management Service (KMS) for Redshift Serverless, and understanding the intricacies of IAM Roles for Redshift Query Editor v2. The module is segmented into detailed parts, starting with creating a Data Warehouse in Amazon Redshift, followed by uploading and managing sample data in S3. You will delve into creating and loading tables in Query Editor v2 and learn to run and visualize sample queries. A significant portion of this module is dedicated to discussing the importance of KMS in the context of Redshift Serverless, focusing on its role in data encryption and security in a serverless environment. As you progress, you will explore Redshift Spectrum, understanding its dataset and pricing model, and develop strategies for optimizing query performance. This module also covers the ETL (Extract, Transform, and Load) process in Amazon Redshift, with a special emphasis on Zero-ETL integrations and their benefits. Monitoring in Amazon Redshift is another critical area you will master. This includes viewing cluster performance data, query history, database performance, and understanding the impact of workload concurrency. You will learn how monitoring individual queries and loads can significantly contribute to performance tuning and optimization. This module is ideal for individuals aspiring to specialize in data warehousing, such as Data Professionals, Project Managers, Database Administrators, and Business Analysts. It is particularly beneficial for those with a foundational understanding of AWS services, although prior experience is not mandatory. By the end of this module, you will have a deep understanding of building and managing a data warehouse in Amazon Redshift, equipped with practical knowledge and skills to optimize data storage, retrieval, and security effectively. The journey culminates in a comprehensive assessment to consolidate your learning and proficiency in the subject.



MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Course Auditing
44.00 EUR
Prior working experience with RDBMS, SQL, and AWS is recommended but optional for this course.

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.