
As cited by Bernard Marr in this brilliant article for Forbes, we are suffering from data overload. Data is everywhere in many different formats and there is an urgent need to transform this data into information. Information is a key factor in decision-making since it is the most valuable part of the data.
The concept of information is something that is objective, readable, easy to understand, and I will present in this article some tips to extract the best part of data and translate it into useful information in a PowerBI dashboard.

In Data Visualization tools like Power BI, the processed data is displayed in reports or dashboards. The development of a good report or panel takes into account many areas such as Programming, Design, UI/UX, Neuroscience, Language, among others. In order to guarantee the effectiveness of the information, it is essential that a connection be made with the user, and hence the concept of narrative.
If it is your first contact with PowerBI or you don’t have experience in that field, I recommend you to read this article below that explains in detail what is PowerBI and how to start it:
Storytelling
Human beings have an innate ability to tell stories, we tell stories all the time since we were children. Storytelling is a tool used to create a connection with the reader and deliver information as effectively as possible.
To create good storytelling we have to guarantee some fundamental factors such as:
- Beauty and design patterns in visualization – Humans are very addicted to patterns and perfect shapes. If you use some design pattern concepts like the Golden Ratio and some color patterns it will suddenly improve the beauty of your dashboard.
- Simplicity – Sometimes less is more, limit the number of charts in your dashboard to present the most important ones and not use complex wallpapers and a white background instead could be a good start to achieve simplicity.
- Ease of reading and understanding – "A perfect graph is one that needs no further explanation". A chart has to be very clear and easy to understand in the first look for every key user if you have to spend time explaining the chart it is a high chance that it is not a good chart.
- Using the same language as the target audience – Sometimes you are presenting a dashboard to a group of students in a university and sometimes you are developing a dashboard to a CEO of an international company and the language used by them is totally different. So, pay attention to your target audience and adapt your approach for each scenario is very important.
- Data reliability – Data presented in a dashboard has to be reliable. The data quality part is very important to every panel, check every number, KPI, filter interaction, charts that vary over time, and try to compare the numbers with other sources within the company. A wrong number can lead to huge mistakes in the decision-making process and discredit your dashboard.
With time and a lot of studies, we acquired the experience to generate dashboards in an increasingly natural way and with good Storytelling development.
The question that remains is, how can I learn to build a good dashboard and achieve good storytelling with less experience? How can I develop my data visualization skills without reading hours and hours of content? To answer these questions, I’ll present several tips that will help you put together the perfect dashboard for every occasion.
How to choose your chart
It is very important to know which type of graph is best for each type of insight. A wrong choice can increase a lot the difficulty to analyze and understand the insight. The graphical visualization is intended to demonstrate the data in the simplest and most intuitive way possible.
"A perfect graph is one that needs no further explanation."
Dr. Andrew Abela published a nice diagram helping us to decide about which chart is a better fit for each scenario. Click in the link below to see the full diagram:
https://apandre.wordpress.com/dataviews/choiceofchart/
Dr. Andrew Abela states that:
- To Compare data we should use Bar charts if we want to compare data among items

OR use a Line chart to compare values over the time

- To show the Relationship between values, we should use a Scatter plot for two variables and a Scatter plot varying the size of the points for three variables.

- To analyze Data Distribution, we should use mainly a Histogram chart for a single variable or a Scatter plot for two variables.

- To understand the Composition of the data we should use Bar chart or Area chart if the variables change over time

OR a Pizza chart or Waterfall chart if variables are static.

Color palette
Colors are also of utmost importance in your display panel. A poor choice of colors can make your dashboard difficult to read, or visually unappealing. Avoid using too many colors together in the dashboard, if you are going to view from a distance like a PowerPoint presentation choose colors that have high contrast to improve the visualization, view your dashboard from far and up close, show your dashboard to someone else, and look at her feedback, think about whether your audience involves people with color blindness. Below is a basic explanation of how to use the color wheel to assemble your combinations.




Power Bi has several themes with predefined color palettes, but you can also find some on the internet, anyway I left some nice ones in the link below:

How to present your Insights
Insights can be separated into 3 different groups: Business Visibility, Performance Improvement, and Opportunity Discovery.
These 3 different types of insights have different views and optimized for a better understanding in each case and I will explain them better below:
1. Business Visibility
The most common way to present a Business Visibility type insight is through a REPORT. Reports are one-off reports, which are designed to show answers to a specific question about the business. Reports are usually shared by email or presented at PowerPoint. A report is a template that aims to provide insight into a simple metric about the facts that have been happening over time in the business. A simpler view, where it does not suggest insights beyond those shown in the chart.

2. Performance Improvement
The device that is commonly associated with the Performance Improvement insight is the SCORECARD. In Performance Improvement type insights, the graphs are already more elaborated, containing some metrics, showing data that bring values to the target audience such as goals, average, total, maximum and minimum values, so that the team extracts the maximum value from the more practical way. This type of chart uses a lot of KPI (indicators), calculated values , and statistical data.

3. Opportunity Discovery
The device that is usually associated with Opportunity Discovery insight is the DASHBOARD. Dashboards are data presented in many ways in a complex yet easy-to-understand manner for the end-user. Dashboards show data that has already been processed, with various KPIs, correlations, forecasts, data evolution over time, metrics, among others. Normally this type of visualization is constantly used by analysts, managers, investors, coordinators, people who need a huge range of data to make a decision.

General viewing tips
Some general visualization tips to build your perfect dashboard or report.
- Remove borders – try to present your graphics in their natural way, fit it to the background of your report and make it interact, and be an environment with the other graphics, don’t delete it with a border.
- Embrace white space – avoid cluttering too much on your dashboard, often a little white space is good for the harmony of the whole.
- Shrink text – try to wrap text in graphics in the form of a caption or title. Cut a few paragraphs into short, easy-to-understand sentences. "A picture is worth a thousand words, and a graphic is worth a thousand pictures"
Demonstration
Finally, I made a demonstration of transforming a Report by applying the tips shown here in the article. The Report in question brings information about the consumption of beer in the city of São Paulo – Brazil. The first report below presents a long text, with several graphs and indicators on consumption. Colors are standard, the text is too large, graphics are not in standard spaces, a lot of data is difficult to understand. Anyway, it takes a lot of time to understand everything that the report has to go through.

After using the hints, we can see a significant improvement in the graph. The colors are nicer and more personalized, we have better contrast and the important data is highlighted and bigger, the data is in standardized places, the text has been greatly reduced without losing the most important information and finally we can better understand the insights more easy and concise.

Thank you so much for reading! I hope these tips can help you develop dashboards and help you on your journey through knowledge in the data world.
Any questions or suggestions can contact me via LinkedIn: https://www.linkedin.com/in/octavio-b-santiago/