Op-Ed: Big Data and the Internet of Things – the evolution of analytics

Modern business intelligence saw a quick and significant evolution in the last decade, as the technology advancement allowed even smaller companies to obtain access to large amounts of data that were previously available only to those with massive resources. Tool automation and in-memory technologies allow even non-specialized personnel to perform their own querying and analysis. As BI has become a more mainstream product, user interface and usability of the latest products became more streamlined, and moved its purpose from canned scheduled reports made by technicians to simpler data exploration and reports made by business departments.

According to a recent market survey performed by the BI software company Sisense, more than half of the companies who use BI technologies expect to consume their data with voice-activated or virtual assistant technologies. More digital-oriented enterprises can even track their chatbot metrics with new inventions such as the BI Bots for Slack, Skype and Facebook Messenger. However, even if the platforms that elaborate it evolved towards simplification, big data itself never stopped growing more complex day by day. So how is the IoT going to help cracking the nut?

Although every small chunk of information can represent a valid data element that may provide a useful insight, the vast majority of the big data everyone wants to get access to is usually buried. Since we can add sensors and chips to almost everything, we can connect every object we currently use in giant networks that will link and report endless amounts of raw data.

According to a recent forecast by Cisco, intelligent devices will provide more than half of the IP traffic not coming from PCs by 2018. Anything, from a simple pen or a headset, to more complex machinery or airplanes, could become a “smart” device that may generate data that could be tracked and analyzed. New, more robust intelligence software will be required to digest all this information accurately, but how are companies going to use it in a practical way?

The examples are literally endless. A courier service could improve its efficiency and performance by monitoring its vehicles’ fuel consumption, cargo temperature and routes followed. A retail store could use data coming from IoTs such as smartphones to track potential customers locations, preferences and trends to optimize its discounts and tailor its offers to improve customer loyalty. A constant flow of data stream can be elaborated in real-time to stop a machine that is out of tolerance in an assembly line to minimize the damage, and that same data can be later analyzed to optimize the whole process and avoid future issues. IoTs can be used to monitor a company’s products, customers, products, machinery and even premises.

Obviously, a lot of people are going be scared by the idea that all this data recording can be used to monitor our daily activities. However, there’s no real risk that all this is going to end in the hands of a single Big Brother entity that would use it to control our lives in a 1984-esque modern dystopia. Indeed, the actual benefits are definitely going to improve the quality of our lives if, for example, big data coming from city traffic will be used by intelligent driverless cars to reduce congestion or help to find parking spaces. Bottom line, although the IoT is surely paving the road to a (relatively near) future where full integration of information can help us breach most of the current BI barriers, the final keycode to safecracking the real big data silos may still requires a few years. On the other hand, with data and related insights already becoming more accessible now than ever before, that day may come sooner than expected.