What’s up everyone? Today is a bit of a follow-up on the previous episode about building dashboards, check that one out first if you haven’t already.Today we’re taking this a step further and talking about data models and the limits of building dashboards.Here’s a typical stance on dashboard design:It is best to focus on the ideal scenario, and worry about the practicalities of implementation later, Or “let the ops team worry about that” as they call it. Haha yeah… This approach may seem appealing at first, as it allows designers to imagine and create without constraints. However, as a marketing operations person, I’m not a fan of this.Here’s today’s main takeaway: I believe that understanding how a dashboard is powered, and having a sense of what is possible and what is not, is a crucial differentiator.Too often, I have seen dashboard projects built in a vacuum, disconnected from the reality of the data and the systems that support them. In these cases, valuable time and resources are wasted building an idealistic dashboard that cannot be implemented or used effectively.Today we’re going to be breaking down how you can level up your knowledge about data models or the capabilities and limitations of the data and the systems that support the dashboard, and designing solutions that are feasible and effective. By understanding these constraints, designers and marketers can create dashboards that are not only beautiful and engaging, but also practical and useful.I feel like this topic could get hairy pretty fast, so let's break down some definitions for the listeners. Da hell is a data model, let’s start there.What’s a data model?Data modeling is a way to organize and structure data from different sources in a consistent and useful way. It helps to make data more accessible and organized, so it can be easily analyzed and interpreted.Gimme a non marketing example, how would you explain this to your mom?Example: A simple example of a data model is a phone directory. The data model for a phone directory would include information such as the names and contact information of individuals, as well as the relationships between them (e.g. family members, colleagues, friends). By organizing this information in a consistent and structured way, the phone directory can be used to easily look up and contact individuals. This data model helps to make the information more accessible and useful.Okay what about a marketing example, that was too simple.I’ll go with my bread and butter, Email marketing example: One example of a data model for email marketing might include information about the email campaigns that have been sent to different segments of your audience. This data model might include details such as 
the subject lines, 
Type of content, 
Subject line keywords
Main call-to-action 
You would also have the results of the campaigns
open rates, 
click-through rates, 
conversion rates
By organizing and structuring this information in a consistent and meaningful way, the data model can help the email marketing team track the performance of their campaigns and to identify areas for improvement. For example, the data model might show that certain subject lines or content types don’t generate as many opens as some emails but they perform better at driving clicks and conversions, and the email marketing team can use this information to optimize their future campaigns. So why should marketers care about this? It’s to prevent shiny object syndrome and understanding where the numbers are coming from but also give you the ability to customize your dashboard.Exactly. A data model is the first step in allowing you to have a dynamic/interactive dashboard. Describe an interactive dashboard in simple termsDescribe an interactive dashboard in simple terms for the listeners. It’s being able to interact with the charts and elements to analyze different parts of your dashboard, for example; filtering certain elements and changing date ranges. This is what sets