The Data Visualization Challenge in the IoT Age
Though not really a new concept, it is only now that the idea of data visualization is catching up in India and across the globe. To explain in simple terms, data visualization is about presenting some data or piece of information in a pictorial or graphical format. Or in other words, it is all about delivering data in an understandable format. This is highly helpful in knowing what the information is conveying in an easier manner. In any case, as we all would agree, visualization is a wonderful tool to break down details and it enables the readers to comprehend technicalities effortlessly.
On average, those using data visualization tools report it would take an average of nine hours longer to see patterns, trends, and correlations in their company’s data without data visualization. – SAP
In today’s digital age, when there is a humongous amount of structured and unstructured data being generated, data visualization scores for its ability to express complex bits of information. It makes use of tools such as charts and graphs which look better than hardcopy reports or excel sheets. Thus, when you have a great deal of information presented in a visually appealing format, there is more clarity in arriving at conclusions. These were the basic pros of data visualization. Now let me share a few challenges as well so that we get a complete picture.
Primarily, there are two main challenges which data visualization faces when it comes to dealing with the massive amount of data generated through the IoT devices.
Having the correct tools
This is a pre-requirement for enabling IoT data to transform into meaningful insights. IoT data comes in humongous quantities and in all kinds. Analysing such information requires varied tools and techniques, else precious pieces of data can be wasted. When you need to select a tool, make sure you go for the one which is able to handle the amount of data necessary for your organization. Data size is a solid determinant of the tool.
Then, the correct tool should manage all forms of analytics as well, such as data management. It further should be able to integrate the data and successfully run it on various systems and applications including on the Internet and other mobile devices. Finally, the test lies in acquiring such a tool which is cost effective to a certain extent.
Designing the right dashboards
There are a whole lot of activities which IoT can manage to do for a business, such as computing market trends, tabulating social media activities, understanding recent purchase materials, etc. This means that if the data is to be presented in an interactive format, it should support different forms of visually appealing tools. For example, varied kinds of maps, bubble charts, animations, line graphs, and so on.
If the analyst has these options available for the dashboard, it would be easier to present the information according to the user-needs and also in a combination of styles. The challenge also includes understanding the audience so that the right dashboard can be designed to meet the requirements. The core premise of data visualization is to turn the data into actionable insights. Hence, a dashboard has to have the capability to deal with digital data and transform it into doable actions.
Collect and visualize data in real-time
Apart from the volume of the data, IoT also deals with the complexity of device types, sensors, and types of data. Add to it the fact that the data gets generated in real-time and needs to be analyzed in real-time. The visualization dashboard for IoT needs to almost tell a story of actions and their impact and through that, facilitate a thoughtful decision.
A person dealing with IoT has no time and patience to decipher the information at leisure. Unless the data is comprehendible, taking quick, result-oriented actions is impossible. That is why data visualization is necessary and effective. One of the tasks here is to be able to decide which form of visual works the best for what kind of information and according to who the end users are. On that note, a smaller but equally worth considering challenge lies in finding the right human resources who can fully exploit data visualization techniques to reach out to the consumers. The interconnectedness of data is necessary for complete visualization. Hence, along with acquiring tools which allow such interconnectivity, it would be good to invest in a team which has the domain expertise to successfully understand and further communicates the data results to its prospective users.
Do read the books by Edward Tufte on data visualization, if possible. They present some very interesting thoughts on this topic. And in case you already have, let me know how you found those as well!