DAR Methodology (Dashboard structure)

Jorge Mendoza Rivilla
3 min readJun 12, 2023

As a Data Analyst, the main objective is to help stakeholders make decisions through data. Commonly a product that helps is the Dashboard.

The dashboard helps summarize the amount of data that is represented with charts, pivot tables, and KPIs.

However, a Dashboard with an incorrect structure it will cause make bad decisions, get bad insights, and not be usability.

The Dashboard structure would allow tell a history, and there are several tips, but this note talks about DAR Methodology.

DAR motivation

Claude Shannon proposed behavioral patterns that explain how humans interact with information.

The main elements: Perception (data collection), cognition (data processing), and action (decisions making).

Claude Shannon, the “father of information theory.”

On the other hand, there are two kinds of perception: Top Down and Bottom Up.

The top-down perception is when what we perceive is influenced by our past experiences. While the bottom-up perception is not influenced by our expectations. It’s our first impression of something.

In summary when joining the PCA theory and the kind of perception we can design a dashboard with a high level of usability.


The main objective of the first section called the dashboard shows the principal information and has the least amount of interactivity/clicking. The mission is to get a summary about the overall status of their business and we would read it in at least 2 minutes.

Usually, this section shows KPI and high-level information, gives a few basic filters, and has a hierarchy to your information to make scanning easy (The most important information should be larger than your least important information).


The analysis section must allow for getting insights and answering the “why” question.

This section helps users to explore their data and look for answers to questions they may have formed on the dashboard page. Contain more filters and silo information, pages can scroll vertically, and introduce more charts and tables.


The last section allows analyze the granular information and is util to take action. Here the users filter de information, and interact with tables and rows details.

Dowloand example PowerBI Disney project here.



Jorge Mendoza Rivilla

Data Analytics | Management | Football Analytical | AI | I Write to Understand