Data Modeling for the Modern Warehouse
This course provides an introduction to data modeling with an emphasis on the Kimball methodology. Students will learn to build scalable business intelligence systems given source data realities and business requirements. You will develop a vocabulary to describe the different elements of business processes, create artifacts to elucidate and document the business intelligence system, and learn how to handle common data modeling use cases. Though we have not designed the course to be tool specific, there will be references to dbt throughout.
Course taught by expert instructors
Miles Russell
Senior Analytics Engineer at GitLab
Miles is a Senior Analytics Engineer at GitLab. He has held data analysis and analytics engineering roles on data teams large and small, and consistently held technical leader and mentor roles to enable his teammates to excel. He prides himself on his ability to facilitate communication and collaboration between business partners of all varieties.
The course
Learn and apply skills with real-world projects.
New Analytics Engineers looking to formalize their data modeling philosophies.
Data Scientists, Business/Data Analysts, or Product Managers who want to bring some clarity to their data warehouse.
Intermediate SQL skills
Familiarity with relational databases
Try these prep courses first
- Learn
- Fundamentals and vocabulary of data modeling
- Simple but powerfully document relationships in your data ecosystem
- Data Bus Matrix
- Database documentation
- Learn
- Frameworks for approaching data modeling problems
- Involving business partners in the data modeling process
- Conceptual/Logical Data Model
- Entity Relationship Diagram
- Learn
- Build a consistent and definitive reporting structure that can be easily queried by business partners
- Wireframing
- Entity Relationship Diagram
- Pseudo SQL queries
- Learn
- Work backwards from end reporting requirements to guide modeling processes
- Strategies for dealing with common enterprise applications, including subscriptions and web events.
- Integrate a new data source into an existing reporting structure
Real-world projects
Work on projects that bring your learning to life.
Made to be directly applicable in your work.
Live access to experts
Sessions and Q&As with our expert instructors, along with real-world projects.
Network & community
Core reviews a study groups. Share experiences and learn alongside a global network of professionals.
Support & accountability
We have a system in place to make sure you complete the course, and to help nudge you along the way.
Course success stories
Learn together and share experiences with other industry professionals
Every analyst should take this course to understand how the data they query is modeled.
I enjoyed spending time getting to know data models with Miles and everyone in the course. I got to learn more about data modeling, its use in many business-focused exercises, and perspectives on its impact to real-world scenarios. I think what made this course unique was the added benefit of sharing this course with like-minded professionals and learning from them.
I attended a data-modeling lecture by Miles where he went above and beyond to deliver a stellar learning experience for myself and 100+ other data professionals. He clearly understands the modern data stack and how to effectively model data in 2022. After the lecture, I followed up with several questions regarding career advice and was incredibly grateful when he took the time to understand where I was before thoughtfully answering each one.
I learned so much! The course had a nice balance of embracing the ambiguity of working with stakeholders and real life data questions, but also how modeling can tame the sometimes overwhelming data chaos and prevent a data swamp. Also I think Miles is a great, thoughtful and emphatic teacher, thank you!
Miles’ contributions on data modeling for the dbt course have been so valuable and are always a hit each time he presents—he has a very practical and modern approach on how to model data in 2022!
