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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.

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Miles Russell
Senior Analytics Engineer at GitLab
Real-world projects that teach you industry skills.
Learn alongside a small group of your professional peers
Part-time program with 2 live events per week:
Lecture
Monday @ 5:00 PM UTC
Project Session
Wednesday @ 5:00 PM UTC
Next Cohort
November 7, 2022
Duration
4 weeks
Price
US$ 400
or included with membership

Course taught by expert instructors

Instructor Photo
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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.

  • Data Bus Matrix
  • Database documentation
Learn
  • Fundamentals and vocabulary of data modeling
  • Simple but powerfully document relationships in your data ecosystem
  • Conceptual/Logical Data Model
  • Entity Relationship Diagram
Learn
  • Frameworks for approaching data modeling problems
  • Involving business partners in the data modeling process
  • Physical Data Model
  • Entity Relationship Diagram
  • Pseudo SQL queries
Learn
  • Build a consistent and definitive reporting structure that can be easily queried by business partners
  • Enterprise Entity Relationship Diagram
Learn
  • Work backwards from end reporting requirements to guide modeling processes
  • Strategies for dealing with common enterprise applications, including subscriptions and web events.

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

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.

Jason DexterAnalytics Engineer, Sr. Data Analyst

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!

Jake HannanSenior Analytics Engineer, Sigma Computing

Really enjoyed this course! Had an excellent project on Data Modeling and an exceptional fireside chat with Miles Russell, who gave us great feedback and practical examples and pointers on setting up our models. thanks Miles!

Stephanie MottData Warehouse Developer at UC Santa Cruz

This course is for...

•

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.

Prerequisites

Intermediate SQL skills

Familiarity with relational databases

Frequently Asked Questions

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