We need to do business with big data. Yes, let’s make it assertive. But how do we do this?
We are finding ourselves in the presence of huge amounts of structured and unstructured information. With Artificial Intelligence’s support, we must elaborate it extremely quickly and without limitations so that it is useful for companies.
The real KPI is managing to make it accessible to many more users, even those who don’t have any technical skills. Indeed, to be able to drive the decision-making processes, a manager needs to see between the lines of these data, which are mostly of an unstructured nature, and glimpse a representation of reality.
This data-driven representation is common to Quantitas, a tech start-up established in the heart of VEGA, Venice’s scientific and technological park, which takes care of big data analytics. Indeed, it acquires, processes and shapes data, producing immediately interpretable indications that can be used by company management, which finds them logically organized in a visual format.
But, what role can AI play in processing these large amounts of data? We asked Duccio Schiavon, Data Scientist at Quantitas, who we interviewed during DigitalMeet18.
Q: How do AI algorithms allow for the extraction of knowledge from big data and why is it essential, nowadays, to adopt a data-driven strategy?
A: Actually, Artificial Intelligence takes advantage of the mechanisms that are, so to speak, consolidated in the world of statistics: the information is collected in an automated way on the basis of recommended models. For this reason, the world of Artificial Intelligence has evolved, not so much in terms of its methods as in its technological tools, given that it is now able to collect, analyze and extract information, trends and logical associations from extremely large amounts of data. As a result, it is thought that AI is currently the best tool to bring such vast informative models to life.
Essentially, in today’s digital world, characterized by big data and by the model that Doug Laney, analyst at Gartner, summarized in the 3 Vs (Velocity, Variety, Volume), companies need technologies based on AI that are as automated as possible. This is in order to leverage the added value that such information can give to business.
Q: In the field of marketing, what relationship exists between data analysis and user engagement? Why is it important for business?
A: I think that it’s an increasingly important relationship because the need to take advantage of all those structured and unstructured data available within companies is coming to the fore. This includes numbers concerning turnover, correlated activities, documents, etc., so as to obtain value to be used for marketing purposes. Obviously, before being able to become actionable, they must be “refined” by the many tools offered by data science.
Q: Given the overcrowding of content online, do you believe that AI allows us to emerge from this impasse with its ability to personalize the content offer for each user?
A: Of course! In the diffusion of technological tools, we are heading in this direction both with chatbots, or rather, those solutions that automate forms of communication to always be available every time the user wants to interact with the brand, and with content proposals, designed to be increasingly targeted on the basis of tastes, trends and what it is thought that consumers are looking for.
But, without Artificial Intelligence, all this would be really difficult. Indeed, it allows us to provide personalized information that is calibrated to user needs in real time and on the various channels that the brand communicates through.