Big Data is growing enormously. With an annual global growth of 40% in Big Data and IoT, the expectation is that many companies will start facilitating data this year. The type of companies that use Big Data is very diverse. Nevertheless, the share of the investment sector is largest: 39% of the investment companies already use Big Data.
To think that there may be a sector not touched by Big Data and IoT is pure utopia. The challenge for companies will be how to realize data monetization, a concept that can have thousands of facets, from knowing how to position a product because it generates more sales up to the anticipation of a demand that can come from the market at a specific moment. While for some the Big Data is just a new way of experimenting, for others it is a real disruption, even a threat, for its survival. Let’s see some examples of the most impacted industries:
Big Data and the automotive industry
The transformation of the driving experience. If someone has recently driven on roads in California, you will have felt the same chill as I did when you saw one of those white cars with the Google logo, driving alone, without a driver.
It is a strange sensation that produces you, halfway between the fascination, the terror and the certainty that nothing will ever be the same again. What is the gasoline that moves the self-driven Google car? The Big Data, because the amount of information that each vehicle needs to collect and process through its sensors to drive safely is 1 Gigabyte every second.
Companies are going to need advanced database tools to collect and interpret this amount of data, and the future of data management will rest in JD Edwards. These programs will provide the type of insight companies need to make the most of tomorrow’s economy.
The ability to connect to telematic sources of information that many manufacturers incorporate in so-called connected cars will allow our vehicles to recommend the best route to avoid traffic jams, warn us that a hailstorm is approaching, analyze our driving to give us advice on how to optimize consumption of gasoline, let us know that a piece is about to break or let us know that we passed close to a store that has our favorite brand of drink on offer. Thus we see that while formerly brands competed in style, performance or engine, today the battle is played in the field of Big Data.
Big Data and insurance: pay as you behave
Effectively, or will not be necessary or the only insurance premium that exists will be that of the vehicle manufacturer. The insurance industry will be entirely affected by Big Data. Until now the price of our insurance was influenced by the characteristics of our vehicle and our sociodemographic data.
However, innovative companies have launched to install sensors in the cars of their policyholders that collect via satellite the speed at which we drive, the times we brake abruptly, the number of accidents on each stretch of road we travel or the frequency with which we operate. That we made the same journey.
This concept of pay as you behave will be transferred to other branches, and we will be able to see how our health insurance goes down when we go out regularly to do exercises or how the home is triggered because a sensor has indicated that we have left a burner on several times.
Big Data and retail
The retail sector for years have understood that data analysis was the main factor to achieve an authentic competitive advantage. In the era of Big Data, retailers are fully exploiting these capabilities to get to know their customers much better, sell more, manage inventories much better, reduce costs and even predict monthly sales of an item using algorithms that monitor the comments that people make on Twitter and Facebook about specific products. The Big Data will allow any supermarket with the algorithm and the technological capacity necessary to change the prices in a real time of each item based on the analysis of the available units.
Big Data and tourism
The right trip, at the right price and at the right time. The world has changed so much that the tourist company with the most significant number of customers, Airbnb, has no hotels, no beds, only has data. In the tourism sector, it no longer sells more who has more offer, but who is able to know better how the mind of the client works when hiring a trip and is able to offer the customer the right tour, at the right price and at the right price. The right moment.
Internet tourism companies have become experts in the dynamic management of prices and have accustomed us to see prices vary at every moment that they publish on the Internet and are managed by intelligent algorithms that decide in milliseconds what cost to display on our screen, depending on how many seats are available, how many other people are watching that same trip or how flexible the price says we are our purchasing history.
Airbnb has developed a price suggestion engine for its advertisers that analyzes five billion data and gives an optimal price for each day depending on the neighborhood, the events that will take place in the city or the size and characteristics of the home, making sure that they get to marry tourist supply and demand better than anyone else.
In the public sector, tourism managers are analyzing millions of comments and photos from social networks to geolocate tourists and understand their patterns of recreation in different cities, deriving traffic from tourists to cold spots in the town and optimizing revenue. Of the shops.
Big Data and health
Personalized and precision medicine. Big Data tools have also been vital to accelerate and lower the costs of sequencing the human genome and to facilitate the use of wearables or wearable devices, which collect millions of data generated by our organism through sensors. These two technological changes will allow us to realize the promise of a truly personalized and precision medicine.
Doctors will be able to personalize the treatment not only based on clinical trials, as up to now, but taking into account each of our individual characteristics: genetics, eating habits, physical shape, lifestyle and even mood. Variables that will be taken into account to ensure that each patient is given the appropriate treatment at the right time to provide the best health outcomes.
The Big Data will improve the diagnostic capabilities of physicians based on machines that complement their experience and knowledge. As IBM’s Watson, an Artificial Intelligence system capable of analyzing more than half a million medical tests, around 2 million pages of research text on breast and lung cancer, and records of 1.5 million patients diagnosed. It can correctly diagnose 90% of cases of lung cancer. On average, an oncology specialist is only able to diagnose 50% accurately.
The significant thing about Big Data is not the data itself, nor the technologies we use to process them, but what we are capable of doing with Big Data to transform the world and the society in which we live.