BBVA API Market
The purpose of data visualization is to present information graphically in such a way that it is clear, efficient and easy to understand. Achieving this goal will depend largely on the story we want the data to tell and how it is told.
In an article by Jonathan A. Schwabish, published in the Journal of Economic Perspectives, the author mentions a series of basic principles to present economic information visually so the story we are being told is quickly understood. These principles can be summed up as:
Show the data: for the viewer to understand the story told by the chart, we have to show the data that it is based on. This does not mean that we have to show all the data; only those that are needed to understand the story.
Remove any distractions: avoid using an unnecessary amount of colors, different fonts, too many visual elements, marks, notes, etc.
Combine the text and charts: the text should not be a separate element that describes the elements that appear in the chart. Ideally, it should complement the visual elements and be completely integrated in the visualization.
On the other hand, Edward Tufte, professor of statistics and political science at Yale University and a well-known name in the field of data visualization, along with Stephen Few, provided a list of key points for the generation of data visualization. The list was originally published in their book The Visual Display of Quantitative Information, published in 1983, and a summary can be found in this Wikipedia entry.
If we ignore these principles, our visualizations will be confusing, overloaded and ambiguous.
Next, we will show some examples of poor visualization and the correction proposed by Schwabish in his article.
This first example combines several poor practices in an attempt to associate economic data with educational data (the use of different colors without a defined criterion, a vertical scale that does not begin with 0, text separated from the chart)
The following visualization corrects these problems and tells the story in a manner that is visually more attractive and direct
The next example shows the poor use of pie charts for the comparison of economic data
The quantitative comparison of the amounts shown is complicated at first view. In addition, there are texts of different sizes spread out throughout the chart. The correction below tells the same story much more efficiently
It is now very easy to compare the amounts visually. Moreover, the text has been moved and is now easier to read, while the percentage symbols have been removed and their interpretation has been included in the heading.
Open banking is driving the development of new apps that are integrated into company platforms, all in an effort to offer banking services to customers. Thanks to APIs, any banking operation, such as opening an account, can be done without the need to exit an application.
Open banking has changed the financial paradigm as we have known it so far. The widespread use of new digital platforms, connected devices and technology consumers has led to a boom in business opportunities for every company, many of which are already leveraging their benefits as much as possible.
The digital transformation has not been fully implemented in the automotive sector yet, at least not as quickly as in other distribution sectors. APIs can be this sector's best ally by speeding up its digitization, especially in those areas involving the purchasing process.