The increasing access we have to more information is the force that has driven the development of Machine Learning and Artificial Intelligence, but all the data in the world is useless if it cannot be understood, which is why data visualization is it’s about how to present data, to the right people, at the right time, to enable them to get insights more effectively. So if a picture is worth a thousand words, data visualization is worth at least a million. This is the current fact.
Data visualization is an umbrella term that describes any effort to help people understand the importance of data by placing it in a visual context. Patterns, trends, and correlations that can sometimes go unnoticed in your data can be more easily exposed and recognized with data visualization libraries.
What is data visualization?
Talking about this term obliges us, in a certain way, to mention business intelligence. They are applications, technologies, and methodologies capable of gathering and transforming data into valuable and structured information to be used and analyzed directly. In this way, the data becomes useful information for decision-making. That’s why data visualization is something important.
Current data visualization tools go beyond the graphs and squares that we were used to making in Excel spreadsheets, data is now displayed in a more sophisticated way such as infographics, geographic maps, and heat maps, among others. Images may include interactive capabilities, allowing users to manipulate them and drill down into the information displayed there.
They have been very important in democratizing data and analytics and making data-driven insights available to programmers throughout the organization.
Data visualization libraries play an important role in companies, as they began to accumulate large amounts of data, over the years, they needed a quick and easy way to get an overview of their data, and of course, the tools displayed were a natural fit to this.
Visualization is critical to advanced analytics for similar reasons, when you are programming machine learning algorithms it is important to visualize the results to monitor the results and ensure that the models perform as intended. This is because the visualizations of the results of machine learning algorithms are generally easier to interpret than the numerical output.
In summary, the importance of implementing graphs to your data is the following:
Data visualization is a way of displaying complex data in a way that is graphical and easy to understand. This can be especially helpful when trying to explore data and become familiar with it.
Also, since a picture is worth a thousand words, plots and graphs can be very effective in conveying a clear description of data, especially when disseminating results to an audience or sharing data with other data scientists.
Additionally, they can be invaluable when it comes to backing up any recommendations you make to client managers or other decision-makers in your field.
We hope this post was informative. Thank you for reading and have a nice day!
