Build a Data Warehouse in AWS (Coursera)

Offered by Edureka,
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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.

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

Related Courses

Building Scalable Java Microservices with Spring Boot and Spring Cloud (Coursera) Coursera
Google Cloud

Building Scalable Java Microservices with Spring Boot and Spring Cloud (Coursera)

"Microservices" describes a software design pattern in which an application is a collection of loosely coupled services. These services are fine-grained, and can be individually maintained and scaled. The microservices architecture is ideal for the public cloud, with its focus on elastic scaling with on-demand resources. In this course, you will learn how to build Java applications using Spring Boot and Spring Cloud on Google Cloud Platform.

Jun 9th 2026
2 Weeks
Oracle SQL Basics (Coursera) Coursera
LearnQuest

Oracle SQL Basics (Coursera)

This course, Oracle SQL Basics is the third course in the Oracle specialization. It is designed to help you learn the key elements of the Structured Query Language specific to Oracle. We recommend that you have completed the first two courses (Oracle Database Foundations and Oracle Database Platform) prior to beginning this one.

Jun 8th 2026
2 Weeks
Data Manipulation at Scale: Systems and Algorithms (Coursera) Coursera
University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Jun 8th 2026
4 Weeks
Extract, Transform, and Load Data (Coursera) Coursera
CertNexus

Extract, Transform, and Load Data (Coursera)

This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL. Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination

Jun 8th 2026
4 Weeks
SQL for Data Science with R (Coursera) Coursera
IBM

SQL for Data Science with R (Coursera)

Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL and R languages. It is also intended to get you started with performing SQL access in a data science environment.

Jun 8th 2026
5-12 Weeks
Relational database systems (Coursera) Coursera
Universidad Nacional Autónoma de México

Relational database systems (Coursera)

Welcome to the specialization course Relational Database Systems. This course will be completed on six weeks, it will be supported with videos and various documents that will allow you to learn in a very simple way how several types of information systems and databases are available to solve different problems and needs of the companies.

Jun 8th 2026
5-12 Weeks
Databases and SQL for Data Science with Python(Coursera) Coursera
IBM

Databases and SQL for Data Science with Python(Coursera)

Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.

Jun 8th 2026
4 Weeks
Data Warehouse Concepts, Design, and Data Integration (Coursera) Coursera
University of Colorado System

Data Warehouse Concepts, Design, and Data Integration (Coursera)

This is the second course in the Data Warehousing for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will learn exciting concepts and skills for designing data warehouses and creating data integration workflows. These are fundamental skills for data warehouse developers and administrators. You will have hands-on experience for data warehouse design and use open source products for manipulating pivot tables and creating data integration workflows.

Jun 8th 2026
5-12 Weeks
Introduction to Structured Query Language (SQL) (Coursera) Coursera
University of Michigan

Introduction to Structured Query Language (SQL) (Coursera)

In this course, you'll walk through installation steps for installing a text editor, installing MAMP or XAMPP (or equivalent) and creating a MySql Database. You'll learn about single table queries and the basic syntax of the SQL language, as well as database design with multiple tables, foreign keys, and the JOIN operation. Lastly, you'll learn to model many-to-many relationships like those needed to represent users, roles, and courses.

Jun 8th 2026
4 Weeks
Python Project for Data Engineering (Coursera) Coursera
IBM

Python Project for Data Engineering (Coursera)

This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for analysis. Continue with the course and test your knowledge by implementing webscraping and extracting data with APIs all with the help of multiple hands-on labs. After completing this course you will have acquired the confidence to begin collecting large datasets from multiple sources and transform them into one primary source, or begin web scraping to gain valuable business insights all with the use of Python.

Jun 8th 2026
1 Week