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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.

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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.

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.

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What's inside

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.
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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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops deep expertise in Amazon Redshift, equipping learners to build a data warehouse on AWS, including the latest Serverless service
Provides real-world insights and best practices from industry experts
Focuses on practical application and hands-on exercises
Introduces latest cloud-based data warehousing solutions and techniques
Suitable for learners seeking to advance their careers in data engineering, cloud computing, or data analytics
Requires basic knowledge of RDBMS, SQL, and AWS, but provides support for learners with no prior experience

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Build a Data Warehouse in AWS with these activities:
Follow a tutorial on creating a data warehouse in Amazon Redshift
Gain practical experience by following a step-by-step tutorial on building a data warehouse in Amazon Redshift.
Browse courses on Redshift
Show steps
  • Find a reputable tutorial on creating a data warehouse in Amazon Redshift
  • Follow the tutorial step-by-step, taking notes and asking questions as needed
  • Experiment with the data warehouse you created, loading data and running queries
Practice writing SQL queries to extract data from a data warehouse
Solidify your understanding of SQL and data warehousing by practicing writing queries to extract data from a data warehouse.
Browse courses on SQL Queries
Show steps
  • Find a dataset to use for practicing SQL queries
  • Write SQL queries to extract data from the dataset, focusing on different types of queries (e.g., SELECT, JOIN, GROUP BY)
  • Test your queries and analyze the results
Create a data visualization dashboard based on data from a data warehouse
Apply your skills in data warehousing and data visualization by creating a dashboard that presents insights from a data warehouse.
Browse courses on Data Visualization
Show steps
  • Choose a dataset from a data warehouse that you have access to
  • Design a data visualization dashboard that will present insights from the dataset
  • Use a data visualization tool to create the dashboard
  • Present your dashboard to others and discuss the insights that you have gained
Show all three activities

Career center

Learners who complete Build a Data Warehouse in AWS will develop knowledge and skills that may be useful to these careers:
Data Warehouse Engineer
Data Warehouse Engineers are responsible for building and maintaining data warehouses. The Build a Data Warehouse in AWS course would be highly relevant to this role, as it provides hands-on experience in setting up and managing a data warehouse in Amazon Redshift. The course also covers the ETL (Extract, Transform, and Load) process in Amazon Redshift, which would be essential knowledge for a Data Warehouse Engineer.
Data Architect
Data Architects design and manage data systems. The Build a Data Warehouse in AWS course would be helpful for Data Architects, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which would be valuable knowledge for a Data Architect.
Database Administrator
Database Administrators (DBAs) are responsible for managing and maintaining databases. The Build a Data Warehouse in AWS course would be helpful for DBAs, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which would be valuable knowledge for a DBA.
Business Intelligence Analyst
Business Intelligence Analysts use data to make informed decisions. The Build a Data Warehouse in AWS course would be helpful for Business Intelligence Analysts, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which would be valuable knowledge for a Business Intelligence Analyst.
Data Scientist
Data Scientists use data to build predictive models. The Build a Data Warehouse in AWS course may be helpful for Data Scientists, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be valuable knowledge for a Data Scientist.
Cloud Architect
Cloud Architects design and manage cloud computing solutions. The Build a Data Warehouse in AWS course would be helpful for Cloud Architects, as it provides a deep understanding of the concepts and principles of data warehousing in AWS. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Cloud Architect.
Software Engineer
Software Engineers design and develop software applications. The Build a Data Warehouse in AWS course may be helpful for Software Engineers, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Software Engineer.
Project Manager
Project Managers plan and manage projects. The Build a Data Warehouse in AWS course may be helpful for Project Managers, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Project Manager.
Data Analyst
Data Analysts use data to solve business problems. The Build a Data Warehouse in AWS course may be helpful for Data Analysts, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Data Analyst.
Database Developer
Database Developers design and develop databases. The Build a Data Warehouse in AWS course may be helpful for Database Developers, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Database Developer.
Systems Analyst
Systems Analysts analyze and design business systems. The Build a Data Warehouse in AWS course may be helpful for Systems Analysts, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Systems Analyst.
IT Consultant
IT Consultants provide advice and guidance on IT-related matters. The Build a Data Warehouse in AWS course may be helpful for IT Consultants, as it provides a deep understanding of the concepts and principles of data warehousing in AWS. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for an IT Consultant.
Data Engineer
Data Engineers design and build data pipelines. The Build a Data Warehouse in AWS course may be helpful for Data Engineers, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Data Engineer.
Business Analyst
Business Analysts analyze and solve business problems. The Build a Data Warehouse in AWS course may be helpful for Business Analysts, as it provides a deep understanding of the concepts and principles of data warehousing. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Business Analyst.
Cloud Engineer
Cloud Engineers design and manage cloud computing solutions. The Build a Data Warehouse in AWS course may be helpful for Cloud Engineers, as it provides a deep understanding of the concepts and principles of data warehousing in AWS. The course also covers the different types of data warehousing solutions available in AWS, which may be helpful knowledge for a Cloud Engineer.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Build a Data Warehouse in AWS.
Classic guide to dimensional modeling, a data modeling technique that is commonly used in data warehouses. It valuable resource for anyone looking to learn about dimensional modeling.
Provides a comprehensive overview of data warehousing concepts and best practices. It covers the entire data warehousing lifecycle, from data integration and modeling to data access and analysis.
Provides a practical guide to ETL (Extract, Transform, and Load) processes in data warehousing. It covers all aspects of ETL, from data extraction to data loading.
Provides a collection of articles on data warehousing from Ralph Kimball. It covers a wide range of topics, from data modeling to data governance.

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