Data Model

This tag is associated with 11 posts

When Data Modeling goes too far

One thing I have struggled with when I have created Operational Data Stores is the tendency to create generic tables that promote re-use. I find these are usually tables like Address and Person. In an enterprise environment there may be many applications or Systems of Record that store Person or Address information. There is the … Continue reading

Business Case for creating a Data Model and Data Normalization

I recently came across a great article by @datachick on “Why having a Data Model is important?” on DataVersity. Highly recommended read. Karen Lopez provides a great list of items on why she finds a Data Model helpful. I do believe there is something missing from the list of items though. All of the items … Continue reading

12 Rules to create a Dimensional Model from a Normalized Model in an #agile way

Recently I have been on a project where I have been fortunate enough to develop both a normalized Operational Data Store and a Dimensional Data Warehouse. In addition to this, I have been fortunate to be able to recreate the Dimensional Data Warehouse three times over. This has been because the project has been done … Continue reading

Adaptive Data Model – #Agile or Anathema?

I have seen the concept of an Adaptive Data Model proposed as an Agile method to Data Modelling lately. (Most recently in Ken Collier’s excellent book – “Agile Analytics”) The theory is that you can be more Agile using an ¬†Adaptive Data Model instead of a traditional Data Model of the business domain. Definition An … Continue reading

The state of #Agile according to Data Modellers

DataVersity released their snapshot survey on Data Modelling and the results aren’t good for Data Modellers who want more adoption of Agile by the Data Modelling community. Before we get into the details, DataVersity is a great source of references and webinars for all things data. You can find them by clicking on this link: … Continue reading

#Agile Enterprise Data Model – #holistic and #iterative

I’ve recently been working on a Data Warehouse project that I am trying to do in an Agile way. Unlike Agile Software Development, Agile Data projects have some complexities that cause you to adapt the common Agile methods and practices. I am a big fan of User Story Mapping and creating a User Story Map … Continue reading

Why #Dimensional Modeling matters

I’ve recently completed a data modeling initiative on a major project. After doing this I’ve come to two major conclusions: The coverage area in Insurance is probably the most devious and twisted area of data that I have ever modeled. Dimensional Modeling should be done on every model to ensure you can simply model the … Continue reading

Why do we #DataModel at all?

People in the Database world take Normalization and Data Modeling as something that should be done without question. I compare it to best practices like versioning software. No one expects that anyone would create software without version control anymore.But more often recently I do get questioned and challenged on why we need to normalize and¬†model … Continue reading

Object Model and Data Model differences – Embrace the diversity

In my experience there is a distinctive difference in Data Models when they are created by developers with an Object Model mindset. Usually there is some work and negotiation that needs to be done to properly overcome the Object Model-Data Model impedance problem. I believe that both extreme points lead to less than optimal designs … Continue reading

Data Modeling mistake – Violating 4th Normal Form

As I read David C Hay’s awesome book on Data Model Patterns, I start to realize the mistakes I have made creating certain Data Models in the past. In particular, one mistake that I made repeatedly became very apparent. Data Modeling mistake – Violating 4th Normal Form Looking back in some of the Data Models … Continue reading