Hi, I would like to ask if you plan to adress the technical debt in modeling. Like, what happens if legacy tables were modeled using a certain method and you want to change it, or used no modeling at all, how to deal with this kind of changes. Thanks!
Really excited about this newsletter! Practical data modeling is something a lot of us learn only by doing, so having a resource that breaks it down step‑by‑step is super valuable. I’m looking forward to posts that cover real‑world examples, clear explanations of concepts like normalization, ER diagrams, and dimensional models, and how to apply them in actual database design. Thanks for creating this — it’s great to see content that bridges theory and practice!
Really excited about this newsletter! Practical data modeling is something a lot of us learn only by doing, so having a resource that breaks it down step‑by‑step is super valuable. I’m looking forward to posts that cover real‑world examples, clear explanations of concepts like normalization, ER diagrams, and dimensional models, and how to apply them in actual database design. Thanks for creating this — it’s great to see content that bridges theory and practice!
Stumbled onto Practical Data Modeling this week and am VERY excited to dive in and come along for the ride - i'm an Analytics Engineer and am planning to double down on my data modeling skills
I've been following your work on data engineering and data modeling with great interest and am excited about the upcoming book. My career has been centered on finance, operations, and data and analytics layers in middle-market, private equity-backed businesses, a segment I believe is underserved by data and analytics and data science currently.
In my role, I frequently encounter the challenge of activating for analytics and data science multiple versions of disparate systems - from PoS to CRMs and ERPs, etc. - especially in businesses undergoing acquisitions. The analytics layer integration is crucial for operational management and demonstrating value to potential buyers, ideally in lieu of costly and time consuming source system integrations (especially if nothing is broken where hands hit the keyboard and data is produced).
Given these complexities, I hypothesize MDM and Data Modeling to be even more critical in my context than perhaps it may be for others.
Therefore, the practical insights your substack intends to highlight I suspect will not be just helpful, but essential for navigating these challenges.
I was watching a data modeling course and your comment brought one of its concepts to mind. One thing that was mentioned is that data modeling and database design use similar techniques. So while you're describing is more logical modeling, I suspect what he's referring to that there needs to be more discussion of conceptual modeling(one level above logical) before we consider more logical modeling/DB design. Hope that helps!
Hi, I would like to ask if you plan to adress the technical debt in modeling. Like, what happens if legacy tables were modeled using a certain method and you want to change it, or used no modeling at all, how to deal with this kind of changes. Thanks!
Really excited about this newsletter! Practical data modeling is something a lot of us learn only by doing, so having a resource that breaks it down step‑by‑step is super valuable. I’m looking forward to posts that cover real‑world examples, clear explanations of concepts like normalization, ER diagrams, and dimensional models, and how to apply them in actual database design. Thanks for creating this — it’s great to see content that bridges theory and practice!
Thank you
Really excited about this newsletter! Practical data modeling is something a lot of us learn only by doing, so having a resource that breaks it down step‑by‑step is super valuable. I’m looking forward to posts that cover real‑world examples, clear explanations of concepts like normalization, ER diagrams, and dimensional models, and how to apply them in actual database design. Thanks for creating this — it’s great to see content that bridges theory and practice!
<a href="https://onlineitguru.com/data-modeling-training">data modelling courses free</a>
Stumbled onto Practical Data Modeling this week and am VERY excited to dive in and come along for the ride - i'm an Analytics Engineer and am planning to double down on my data modeling skills
Any update into your data engineering spec release?
What are you referring to?
In this article you mentioned Andrew Ng asking you to spearhead a data eng specialization over at deep learning.ai
I would be first to sign up whenever/if that comes out!
I enjoyed the recorded session on YouTube.
Throughout the session, Joe recommended many book including:
The data model resource book Vol. 1, Vol2, and Vol3.
Can’t wait!
Looking forward to this!
Very excited!
I've been following your work on data engineering and data modeling with great interest and am excited about the upcoming book. My career has been centered on finance, operations, and data and analytics layers in middle-market, private equity-backed businesses, a segment I believe is underserved by data and analytics and data science currently.
In my role, I frequently encounter the challenge of activating for analytics and data science multiple versions of disparate systems - from PoS to CRMs and ERPs, etc. - especially in businesses undergoing acquisitions. The analytics layer integration is crucial for operational management and demonstrating value to potential buyers, ideally in lieu of costly and time consuming source system integrations (especially if nothing is broken where hands hit the keyboard and data is produced).
Given these complexities, I hypothesize MDM and Data Modeling to be even more critical in my context than perhaps it may be for others.
Therefore, the practical insights your substack intends to highlight I suspect will not be just helpful, but essential for navigating these challenges.
Looking forward to your guidance, Joe!
I was watching a data modeling course and your comment brought one of its concepts to mind. One thing that was mentioned is that data modeling and database design use similar techniques. So while you're describing is more logical modeling, I suspect what he's referring to that there needs to be more discussion of conceptual modeling(one level above logical) before we consider more logical modeling/DB design. Hope that helps!