Pere Rovira, Chief Strategy Officer at OneTandem, tells us in this interview the advantages of data visualization for SMEs, the patterns that must be taken into account for a correct data visualization, the different ways to show them in the best possible way, as well as the different tools that exist for this purpose.
- How would data visualization help SMEs?
This is for SMEs as well as micro-enterprises and large companies, and even for citizens. There is a lot of talk about data, but we are not really used to making data-driven decisions, to understanding how data can help us and to better understand reality. We have received little training on this topic.
We never get to see or we don't get to see how data from the world in general, from the social sciences, or from business can help us make better decisions. There are companies in which a lot of data was collected, but decisions were not made and were not useful. One way for people to better understand the data, to have a greater impact on them and to better understand the meaning they can have, is to visualize them. When we turn data into graphs, it is much easier to understand what it means. Therefore, you will understand a series of data that, in isolation or listed, would tell you very little. Now you will understand their importance.
- What patterns should a company take into account for a correct data visualization?
There are many and it also depends a lot on the maturity of the company. I have worked with very large companies that had to start with the most basic, which is that they did not even know what data they had. I have also worked with very small companies that are very clear about what they need to know and what data they have and how they have to use it. There are different levels of maturity. Before we start visualizing the data, we need to understand what the company wants to achieve with that data. What questions do you want to get to answer? These questions are very important because they help us to be concrete and also help us to avoid data for data's sake. What things do you want to understand better thanks to the data? From there we are going to ask ourselves what kind of data do you need to answer these questions. How do we need to order, prepare and store it. Once these requirements are met, we can start to visually explore this data, analyze it, draw conclusions and communicate them in a visual way and give recommendations from the data.
- What are the main designs and formats for data visualization?
The infographics that everyone knows and that can appear in magazines, especially in print media. But there are also quite a few that circulate on social networks. Infographics are a little bit these visual ways of communicating concepts and some data from the graphics themselves that we see every day in digital media, but also in print. We have seen a lot of graphics on the subject of the COVID pandemic and the great monitoring that has been done of this pandemic through its evolution, which was shown through data and trends, to see if cases were going up or down.
From here, the great innovation that I think there has been in recent years is interactive visualization, what is known as interactive data visualization. Static visualization is all very well, it provides us with a series of graphs, and many times it forces us to be much clearer about what we want to say with this data, but especially when we have a large volume of data, it is difficult to be able to offer it through a static image. Interactive visualizations allow us to access them through a web browser, for example, or a mobile application, they allow us to zoom, they allow us to filter, they allow us to go from the most general to the most specific. This is also very important for companies because, for example, they often have to analyze the sales and results of many products in their catalog categorized in very different ways. It would be practically impossible to want to visualize everything at once and they need interactive functionalities that allow them to explore this data and the patterns at different levels of detail.
- What are the main tools for data visualization, are there free tools or ones that cost less?
The tool that everyone knows and everyone has used at one time or another, and is still used in the vast majority of cases, is Excel. It is a tool that everyone has and everyone can use, or its free software equivalents, such as the Google version. From here, there are many limitations. When the volume of data grows a lot, it can be difficult to manage it with a spreadsheet and also we can't do all the types of charts we would like to do. This is why new types of tools have emerged in the business world, such as Power BI (Microsoft), Tableau (Salesforce) or Google Data Studio. These exist in both cost and free versions. For more advanced data usage, programming languages such as R, Phyton or Javascript can be used, the latter consolidating itself as the main language for data visualization, especially interactive and creative data visualization. It is a very suitable language for publishing your visualizations on a website, whether public or private, and therefore it is very easy to provide access to a visualization. There are a multitude of options and also tools used by journalists, such as DataWrapper or Flourish.