Posted on by datavisualizationgurus

15 Data Visualization tips you need to know to make Effective Charts

There are many great resources available that offer tips on effective design for data visualization. But who has time to search various articles, websites, and research articles for useful tricks and hidden gems? We want to help you create great graphics right now, so we’ve put together this list of quick tips for you to consider when creating your next presentation.


15 quick data visualization tips
1. Before you start designing your board, stop to think about your story. What are you trying to say? Once you understand your message, the process is much easier.

2. Keep it simple. If it doesn’t support your story, leave it out. You don’t want to saturate your boxes with unnecessary text, colors, drop shadows, or 3D images.


3. Give your painting a strong title that clearly frames your message. Great titles make graphics more memorable and helpful.


4. Scale your board appropriately. Always take care that the scale you use on each axis must have equal intervals. This is a quick way to make sure your chart is displaying correctly.


5. Choose a font for your title, axes and legends labels that are easy to read. You want people to connect to your message quickly.
6. For the sake of transparency, always quote your sources. This builds credibility, builds trust, and gives your readers the opportunity to visit the source for more information.


7. Organize your data logically. Carefully arrange all columns and bars in order by value to make them more easy to compare at a glance.
8. Use color to draw attention to a specific part of your graphic. Bright colors quickly attract attention, helping to get the message across faster especially when you’re working on map visualization.


9. Avoid making rainbows or using mixed color palettes. They may be pretty, but they are not necessarily effective. We suggest that you choose a color for the whole picture or use a touch of color to highlight the important areas in the map visualization or visualization through graphs.


10. Do not select the data you choose to view. While you may have impressive numbers to share, you should give context and tell the full story.


11. Label your data directly, so you can make your table easier to understand quickly. Put labels next to the corresponding lines or bars if a legend takes too long to read.


12. Grid lines should be used only if they make your data easier to read. Play around with vertical and horizontal grid lines until you feel your frame is clear and concise.


13. Always use company colors, fonts, and branding when presenting data internally. This makes your graphics look polished and professional.


14. Try to avoid using pie charts to make comparisons. Pie charts are difficult to compare at a glance; it is best to use bar or column tables.


15. It’s easy to get lost in a visualization when you try to do it right. Give it to a friend or colleague to see if they can understand your message in 30 seconds or less.

Posted on by datavisualizationgurus

Why Use Data Visualization in Communication

Data Visualization tool

Today all companies have data. The term Big data is already mastered in most companies and they know the importance of collecting information.

However, the main flaw that makes it impossible to extract the full potential of the data comes right after it is collected: analysis. And is that the real challenge of Big data is in the interpretation of data.To facilitate this process and to be able to display the information in a simple and understandable way, data visualization tools have been created.

These tools collect all the company’s databases and display them on a single platform, allowing the team to carry out a cross-sectional analysis.

To extract knowledge and transmit messages with the data, we need to have a good data visualization tool that supports and facilitates our analysis.

What Does A Data Visualization Tool Do

To understand in a simpler way how a data visualization tool works, we will explain it:We have a platform where all kinds of databases can be connected. On this platform, we can load data manually and automatically.

Manually, we will make the loads through Excel, CSV, JSON or HTML documents for example. Loading this data over time can be facilitated by sending the databases to the platform by email.The connections that are made automatically can be several. For example, if the visualization tool has developed the connectors, we can connect via API with Facebook, Instagram, Twitter, Google or Adobe Analytics …


Connections can also be made through SAS, Google Big Query or Hadoop. Unlike a DMP, a data visualization tool cannot activate other tools, that is, it does not have the capacity to make a call to the server of our Email Marketing platform to execute any action. It just collects the information and displays it. Although, in recent months, some of these platforms are starting to move towards the activation field.


What Is It Used for in Communication?

The Data Visualization gurus says that the data visualization platform collects the databases, previously labelled with business areas, reputation dimensions or company objectives.
For what? So that the impact of internal efforts can be measured, to have traceability of press releases in all media, to measure the effectiveness of each of the actions of the different campaigns.


It is the best way to control the objectives of the department and the company, to observe the real situation of the actions, the status of the reputation and the effectiveness of our communications.

1) It allows to have a vision of what happens in all the communications of the company. Furthermore, the platform is interactive and usable. It is easy to extract knowledge from graphs.

2) It is an ideal tool for communication since in this business area there has never been a spirit of measurement. However, metrics are already required from all departments and this is an easy way to carry them out.

3)  It has the advantage that all the information comes from the same data source that can be consulted by other departments involved. This guarantees that the data is consistent and there are no inconsistencies in the results of one or another department.

4) It allows metrics and cross-sectional dimensions to be used in all databases, matching them to be able to analyse them together.

Key to Keep in Mind

First of all, for a d3 expert tool to be useful to you, your data needs to be consistent. In other words, you have to have data volume and reliability. The data collection methodology must be consistent across all databases.