Deliver Better Analytics By Finding What's Missing In Your Current Architecture
Designing a data architecture on paper is one thing.
But successfully implementing it all (without getting sidetracked) is another.
What We Strive For:
What Actually Happens:
More often, teams end up with half-complete architectures that technically "work", but could be 10x better with a few subtle tweaks.
But in the midst of the day-to-day responsibilities, how are you supposed to figure out what's missing?
Not to mention, prioritize what needs to be done first.
To address this issue, I created the 1-Page Analytics Audit.
And in this Skill Session, you'll not only get instant access to this pre-formulated workbook to use for yourself.
But also supporting video lessons to help you get clear on your architecture and quickly identify areas for improvement.
What We’ll Cover:
- The 3 Pillars of Modern Data Architectures (so you can stay focused on what matters most)
- Creating a visual representation of your architecture & team layout (so you can quickly identify problem areas)
- 30+ Recommended Conventions for building reliable data architectures (so you can find specific ways to add more structure & consistency)
Main Topics:
- Understanding Your Current Architecture
- The Conventions Scorecard
- Creating Your 1-Page Audit
Duration: 1hr
Bonus Additional Content:
- Common Data Team Structures
- Why Data Migrations Go Wrong (3 Reasons)
- Why Your Data Team Needs Version Control
- A Typical GitHub Workflow (What to Expect)
- Whta Is DataOps?
Future Q&A Content: I'll be adding videos in the future addressing common comments/questions from students in the course.
IMPORTANT:
This is not a hands-on project-based type of course. The focus of the material is on strategy and concepts.
Please do not enroll if you are looking step-by-step coding tutorials.
ACCESS NOTE: This course is hosted inside my free community called "The Modern Data Community" on Skool.com.
Upon purchase, you will be automatically invited to join and granted access to this material.