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Sean Murdock,
Matt Swaffer,
Ben Goldberg,
Amanda Moran,
and
Valerie Scarlata
Take Udacity's Introduction to Data Warehousing course and learn to create cloud-based data warehouses using Amazon Web Services (AWS).
Prerequisite details
Read more
Take Udacity's Introduction to Data Warehousing course and learn to create cloud-based data warehouses using Amazon Web Services (AWS).
Prerequisite details
Read more
Take Udacity's Introduction to Data Warehousing course and learn to create cloud-based data warehouses using Amazon Web Services (AWS).
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Command line interface basics
- Intermediate SQL
- Basic github
- Intermediate Python
- Amazon web services basics
- Relational database basics
- Relational data models
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/wcuhci/cloud
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What's inside
Syllabus
Welcome to Cloud Data Warehouse with Amazon Web Services. In this lesson, you'll learn more about the course and set yourself up for success!
Read more
Syllabus
Welcome to Cloud Data Warehouse with Amazon Web Services. In this lesson, you'll learn more about the course and set yourself up for success!
Read more
In this lesson, you'll be introduced to the business case for data warehouses as well as architecture, extracting, transforming, and loading data, data modeling, and data warehouse technologies.
In this lesson, you'll learn about ELT, the differences between ETL and ELT, and general cloud data warehouse technologies.
In this lesson, you'll learn about AWS Services and how to set up Amazon S3, IAM, VPC, EC2, and RDS. You'll build a Redshift data warehouse cluster and learn how to interact with it.
In this lesson, you'll learn to implement a data warehouse on AWS
In this project, you'll build an ETL pipeline that extracts data from S3, stages data in Redshift, and transforms data into a set of dimensional tables for an analytics team.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops practical skills for creating cloud-based data warehouses in AWS necessary for working with data
Taught by instructors who specialize in data warehousing and analytics technologies
Provides a foundational understanding of data warehousing concepts, technologies, and practices
Builds on foundational knowledge in data warehousing and cloud computing
Involves hands-on implementation of an ETL pipeline using AWS services
Requires intermediate knowledge in SQL, Python, and basic GitHub
Save this course
Save Cloud Data Warehouses to your list so you can find it easily later:
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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 Cloud Data Warehouses with these
activities:
Organize and review course materials
Show steps
Helps students organize and recall key concepts by encouraging them to review and compile course materials.
Browse courses on
Data Warehousing
Show steps
-
Gather and organize course notes, slides, and assignments.
-
Create summaries or mind maps to reinforce understanding.
Review basic SQL and Python
Show steps
Ensures students have a strong foundation in SQL and Python, which are essential for data warehousing tasks.
Browse courses on
SQL
Show steps
-
Review SQL syntax and practice writing queries.
-
Review Python basics and practice data manipulation tasks.
Read and review 'The Data Warehouse Toolkit' by Ralph Kimball and Margy Ross
Show steps
Provides a comprehensive guide to data warehouse design and implementation, covering best practices and industry standards.
View
Kimball's Data Warehouse Toolkit Classics, 3...
on Amazon
Show steps
-
Read through the chapters covering data warehouse fundamentals, design principles, and modeling techniques.
-
Take notes and highlight key concepts.
-
Complete the exercises and review questions at the end of each chapter.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group or online forum for data warehousing
Show steps
Provides opportunities for peer collaboration, knowledge exchange, and support in understanding course concepts.
Browse courses on
Data Warehousing
Show steps
-
Find a study group or online forum related to data warehousing.
-
Participate in discussions, ask questions, and share knowledge.
Read and review 'Data Warehouse Design and Implementation' by Ralph Kimball
Show steps
Provides a foundational understanding of data warehouse design and implementation, covering concepts such as data modeling, ETL, and data analytics.
View
The Kimball Group Reader
on Amazon
Show steps
-
Read through the chapters covering data warehouse fundamentals, design principles, and modeling techniques.
-
Take notes and highlight key concepts.
-
Complete the exercises and review questions at the end of each chapter.
Complete the AWS Data Warehousing Fundamentals Tutorial
Show steps
Provides hands-on experience with AWS data warehousing services and helps reinforce concepts learned in the course.
Browse courses on
Amazon Web Services
Show steps
-
Follow the step-by-step instructions in the tutorial.
-
Create an AWS account and set up the necessary services.
-
Build a sample data warehouse using Redshift.
Create a blog post or article on a data warehousing topic
Show steps
Encourages students to apply their knowledge by sharing their understanding and insights on a specific data warehousing topic.
Browse courses on
Data Warehousing
Show steps
-
Choose a topic that interests you and aligns with the course content.
-
Research and gather information from reliable sources.
-
Write a clear and well-organized article.
-
Publish your article on a relevant platform.
Build a data warehouse using AWS services
Show steps
Provides practical experience in designing, implementing, and deploying a data warehouse using real-world data.
Browse courses on
Data Warehousing
Show steps
-
Define the business requirements and data sources.
-
Design the data model and ETL process.
-
Implement the data warehouse using AWS services.
-
Load and transform data into the warehouse.
-
Analyze the data and create reports.
Organize and review course materials
Show steps
Helps students organize and recall key concepts by encouraging them to review and compile course materials.
Browse courses on
Data Warehousing
Show steps
Show steps
Show steps
- Gather and organize course notes, slides, and assignments.
- Create summaries or mind maps to reinforce understanding.
Review basic SQL and Python
Show steps
Ensures students have a strong foundation in SQL and Python, which are essential for data warehousing tasks.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review SQL syntax and practice writing queries.
- Review Python basics and practice data manipulation tasks.
Read and review 'The Data Warehouse Toolkit' by Ralph Kimball and Margy Ross
Show steps
Provides a comprehensive guide to data warehouse design and implementation, covering best practices and industry standards.
View
Kimball's Data Warehouse Toolkit Classics, 3...
on Amazon
Show steps
Show steps
Show steps
- Read through the chapters covering data warehouse fundamentals, design principles, and modeling techniques.
- Take notes and highlight key concepts.
- Complete the exercises and review questions at the end of each chapter.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group or online forum for data warehousing
Show steps
Provides opportunities for peer collaboration, knowledge exchange, and support in understanding course concepts.
Browse courses on
Data Warehousing
Show steps
Show steps
Show steps
- Find a study group or online forum related to data warehousing.
- Participate in discussions, ask questions, and share knowledge.
Read and review 'Data Warehouse Design and Implementation' by Ralph Kimball
Show steps
Provides a foundational understanding of data warehouse design and implementation, covering concepts such as data modeling, ETL, and data analytics.
View
The Kimball Group Reader
on Amazon
Show steps
Show steps
Show steps
- Read through the chapters covering data warehouse fundamentals, design principles, and modeling techniques.
- Take notes and highlight key concepts.
- Complete the exercises and review questions at the end of each chapter.
Complete the AWS Data Warehousing Fundamentals Tutorial
Show steps
Provides hands-on experience with AWS data warehousing services and helps reinforce concepts learned in the course.
Browse courses on
Amazon Web Services
Show steps
Show steps
Show steps
- Follow the step-by-step instructions in the tutorial.
- Create an AWS account and set up the necessary services.
- Build a sample data warehouse using Redshift.
Create a blog post or article on a data warehousing topic
Show steps
Encourages students to apply their knowledge by sharing their understanding and insights on a specific data warehousing topic.
Browse courses on
Data Warehousing
Show steps
Show steps
Show steps
- Choose a topic that interests you and aligns with the course content.
- Research and gather information from reliable sources.
- Write a clear and well-organized article.
- Publish your article on a relevant platform.
Build a data warehouse using AWS services
Show steps
Provides practical experience in designing, implementing, and deploying a data warehouse using real-world data.
Browse courses on
Data Warehousing
Show steps
Show steps
Show steps
- Define the business requirements and data sources.
- Design the data model and ETL process.
- Implement the data warehouse using AWS services.
- Load and transform data into the warehouse.
- Analyze the data and create reports.
Career center
Learners who complete Cloud Data Warehouses will develop knowledge and skills
that may be useful to these careers:
Data Warehouse Engineer
Data Warehouse Engineer
Data Warehouse Engineers create and maintain data warehouses, which are central repositories for storing and managing large amounts of data. They design and implement data warehouse architectures, load and transform data, and develop and maintain data quality processes. This course provides a foundation in data warehousing concepts and technologies, and will help you develop the skills needed to become a successful Data Warehouse Engineer.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns, and develop insights that can help businesses make better decisions. This course provides a foundation in data warehousing concepts and technologies, which are essential for Data Analysts who want to work with large amounts of data. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse, and to analyze data to identify trends and patterns.
Database Administrator
Database Administrator
Database Administrators (DBAs) are responsible for the performance and security of databases. They install, configure, and maintain databases, and develop and implement data backup and recovery plans. This course provides a foundation in data warehousing concepts and technologies, which are essential for DBAs who want to work with large amounts of data. The course will help you develop the skills needed to design and implement data warehouse architectures, and to load and transform data into a data warehouse.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They collect, analyze, and interpret data to identify trends, patterns, and opportunities. This course provides a foundation in data warehousing concepts and technologies, which are essential for Business Intelligence Analysts who want to work with large amounts of data. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse, and to analyze data to identify trends and patterns.
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems. They develop and apply machine learning algorithms to data to identify patterns and trends, and to build predictive models. This course provides a foundation in data warehousing concepts and technologies, which are essential for Data Scientists who want to work with large amounts of data. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse, and to analyze data to identify trends and patterns.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with a variety of programming languages and technologies to create software that meets the needs of users. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Software Engineers who want to develop data-driven applications. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse, and to analyze data to identify trends and patterns.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. They work with a variety of cloud technologies to create solutions that are scalable, reliable, and secure. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Cloud Architects who want to design and implement cloud-based data warehouses. The course will help you develop the skills needed to design and implement data warehouse architectures, and to load and transform data into a data warehouse.
Data Engineer
Data Engineer
Data Engineers design and implement data pipelines. They work with a variety of data sources and technologies to create pipelines that collect, clean, and transform data. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Data Engineers who want to design and implement data pipelines for data warehouses. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse.
Data Integration Specialist
Data Integration Specialist
Data Integration Specialists integrate data from a variety of sources into a single, unified data warehouse. They work with a variety of data integration tools and technologies to create data warehouses that are accurate, complete, and consistent. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Data Integration Specialists who want to design and implement data warehouses. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse.
Information Architect
Information Architect
Information Architects design and implement data architectures. They work with a variety of data sources and technologies to create data architectures that are scalable, reliable, and secure. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Information Architects who want to design and implement data architectures for data warehouses. The course will help you develop the skills needed to design and implement data warehouse architectures.
Database Developer
Database Developer
Database Developers design and develop databases. They work with a variety of database technologies to create databases that are scalable, reliable, and secure. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Database Developers who want to develop data warehouses. The course will help you develop the skills needed to design and implement data warehouse architectures, and to load and transform data into a data warehouse.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They work with a variety of data stakeholders to ensure that data is used in a consistent and ethical manner. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Data Governance Analysts who want to develop and implement data governance policies for data warehouses. The course will help you develop the skills needed to design and implement data warehouse architectures, and to load and transform data into a data warehouse.
Data Quality Analyst
Data Quality Analyst
Data Quality Analysts ensure that data is accurate, complete, and consistent. They work with a variety of data sources and technologies to identify and correct data quality issues. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Data Quality Analysts who want to work with data warehouses. The course will help you develop the skills needed to extract, transform, and load data into a data warehouse, and to analyze data to identify data quality issues.
Data Security Analyst
Data Security Analyst
Data Security Analysts protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. They work with a variety of security technologies and processes to implement data security measures. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Data Security Analysts who want to work with data warehouses. The course will help you develop the skills needed to design and implement data warehouse architectures, and to load and transform data into a data warehouse.
Data Privacy Analyst
Data Privacy Analyst
Data Privacy Analysts ensure that data is collected, used, and disclosed in a compliant manner. They work with a variety of privacy laws and regulations to implement data privacy measures. This course provides a foundation in data warehousing concepts and technologies, which can be helpful for Data Privacy Analysts who want to work with data warehouses. The course will help you develop the skills needed to design and implement data warehouse architectures, and to load and transform data into a data warehouse.
For more career information including salaries, visit:
OpenCourser.com/course/wcuhci/cloud
Reading list
We've selected ten 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
Cloud Data Warehouses.
This classic guide by Ralph Kimball provides foundational knowledge in data warehousing principles and best practices. It is an excellent resource for those seeking a comprehensive understanding of data warehouse design, architecture, and implementation.
Focuses on cloud-based data warehousing solutions, including Amazon Redshift. It covers essential concepts, architecture, and implementation strategies for building and managing data warehouses in the cloud.
Provides a broad introduction to data science and data mining techniques. While not specific to data warehousing, it offers valuable insights into data analysis and modeling, which are essential skills for data warehouse professionals.
Hadoop widely used distributed computing framework for big data processing. While not directly related to data warehousing, this book offers valuable background knowledge on data management and processing techniques that can be beneficial for data warehouse professionals.
Provides a comprehensive introduction to SQL, a fundamental language for data management and querying. It valuable resource for those seeking to strengthen their SQL skills and gain a deeper understanding of data manipulation and analysis.
Python versatile programming language widely used in data science and data analysis. offers a practical guide to using Python for data exploration, processing, and visualization, which can be beneficial for data warehouse professionals.
Provides a deep dive into the principles and patterns behind designing scalable and reliable data-intensive applications. While not specific to data warehousing, it offers valuable insights into data architecture, consistency, and performance considerations.
Focuses on dimensional modeling, a key aspect of data warehouse design. It provides a detailed explanation of dimensional modeling techniques and best practices, making it a valuable reference for data warehouse professionals.
Offers a beginner-friendly introduction to data management concepts and best practices. While it may not be directly related to data warehousing, it provides a solid foundation for understanding data management principles.
Save
Provides a deep dive into big data architectures and technologies. While not specific to data warehousing, it offers valuable insights into data processing, stream processing, and data management challenges at scale.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wcuhci/cloud
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Effort
4 weeks
Level
Intermediate
Via
Udacity
Instructors
Sean Murdock
Matt Swaffer
Ben Goldberg
Amanda Moran
Valerie Scarlata
Language
English
Good to know
Develops practical skills for creating cloud-based data warehouses in AWS necessary for working with data
Taught by instructors who specialize in data warehousing and analytics technologies
Provides a foundational understanding of data warehousing concepts, technologies, and practices
Builds on foundational knowledge in data warehousing and cloud computing
Involves hands-on implementation of an ETL pipeline using AWS services
Requires intermediate knowledge in SQL, Python, and basic GitHub
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