Read original article at 112.ua
Big data is no longer the future, since its time has already come and big data now covers all spheres of business, state and life, even in Ukraine. Ukrainian mobile operators use Big Data in their own services and offer analytical products for business and the state. If you live in Kyiv, Lviv, Odesa or in their suburbs, then with a high degree of probability you have already noticed the benefits of big data. 112.ua found out more about the areas of Big Data use and how mobile operators plan to develop a new direction in their technologies.
Sphere of use
An important remark: before we proceed to specific examples, it is important to understand that the data are depersonalized, and neither the operator himself nor his clients know that, for example, a specific Ivan in the specific month in the company of his wife and mistress left Kyiv for vacations in Odesa. Moreover, since the contractual connection is not popular in Ukraine, operators in principle do not know who their subscribers are. They can only assume with some degree of probability, based on usage scenarios, who the subscriber can be - his age, sex, income, car availability, etc. At the same time, the data itself is not transmitted to the customer - only the analyst receives it.
Kyivstar and Vodafone Ukraine say that for the city authorities in Ukraine they provide data for free, the service is paid only for business. Vodafone did not voice tariffs, they say that the approach to different customers is individual, as long as there are no box solutions as such. Moreover, even the cases of a global partner in Ukraine will not help in this issue - the specifics of each country are different.
Infrastructure and transport
Operators "see" how subscribers are moving: around the city, across the country, where do they go abroad. Based on the data on the movement of people in the world, public transport routes are being created and adjusted; roads and railways are being built.
An example from Ukrainian practice: the World Bank allocates funds for our country to repair roads. But this money is not enough to finance everything - you need to correctly prioritize. Big data from mobile operators helped in this issue. The analysis shows exactly how Ukrainians move. And not only on which roads, but also between specific points. Based on this information, you can understand where the reconstruction of the road is required, and where in general a new road is needed.
Another example of Ukrainian practice. Using the operator with BigData, you can track how many people and from where cross the border, and thus determine where there is a need for equipping check points and what infrastructure they should have.
Kyiv used big data to analyze passenger traffic between the right and left banks of Dnipro river, as well as between satellite cities, in order to determine the most loaded directions. Thanks to this, the city accessed the needs for transport. The data helped to develop new transport routes that were launched this year.
In Vodafone Ukraine they say that Lviv is requesting Big Data to properly develop the city, build and organize transport infrastructure.
Tourism and culture
Data on who comes to Ukraine and how people move around the country, are of great value for the tourism industry. Information can be used to create guidebooks (to direct the attention of tourists to objects that for some reason are not popular), translating them into popular languages among tourists, building infrastructure facilities where people go, understanding the beginning and end of the high season.
Within the framework of Ukraine, the Odesa region used Big Data to understand where tourists most often are coming from, and where the region lacks advertising, find out how many months the season lasts. Also Big Data became one of the arguments for launching a train from Kyiv to Izmail.
To organizers of festivals, camera data will help to understand their audience, where they came from, what interests they have. In Vodafone Ukraine they say that the organizers of LvivMozArt applied to them with a request.
Internet of things and smart city
Large data allows finding hidden patterns, approaching the problem from unexpected sides and detecting anomalies (for example, that some objects consume more electricity than similar ones, which means that something is wrong with their work). Internet of things and Big Data save city budgets and make cities safe and comfortable.
In Ukraine, for various reasons, the Internet of things is not yet developed, especially in the "urban" environment. Ukrainian agronomists have already started using sensors in fields and agricultural machinery, the Internet of things penetrates into logistics and transport. For example, in Lviv, there are "smart" traffic lights, the city is also thinking about "smart" garbage removal. "Smart" electricity meters were installed in some point of our country. But we are still far from the mass use of the Internet of things.
In developed cities, sensors are used in the area of housing and communal services, allowing you to control the removal of garbage - from places of accumulation and the need for regular cleaning to entering the processing sites. Sensors are used in the construction of buildings or infrastructure (roads, bridges), they collect information about the state of the objects - they notify about the need for repair or replacement and thus save significant funds to owners, helping to prevent the problem, and not deal with the consequences. Sensors, which are installed in the fields, give agronomists data on the soil state, which makes plant care easier and yields grow. The Netherlands, being a small country, has become one of the world leaders in food production. All thanks to technology in agriculture.
Banks operators’ data also help in the work process. For example, if a client goes to a bank to take a loan, the bank can ask the operator for analysis of the client's mobile number. Software based on large data and machine learning can predict how likely a person will return a loan.
Big data operators are useful for retailers for two purposes - business expansion and cost optimization. For example, they can help the retailer understand where exactly its target audience is and where there is a need to open a shopping point. Vodafone Ukraine, for example, uses this kind of analytics for opening its own branded stores. The operator sells this service to its customers. These are PrivatBank, Alfa-Bank, shop chains (Silpo, ATB, Watsons, etc.) and advertising companies (in particular, TNS, BigBoard).
Optimization of costs can be achieved by the same analysis of traffic in the outlet. For example, a sales outlet can change the work schedule, adjusting to the time when most of the clients are near it, or to increase the number of employees during peak hours.
Why do operators need this?
Operators have one problem and a lot of data to solve it. In one of the articles we already told that they are looking for new ways of monetizing what they have. For example, they create instant messengers and other services, sell additional services (or at least plan to do so) to their audience.
Big data is another asset that can be monetized. And unlike messengers, insurance, books and television, the demand from the potential audience of the service is enormous, and there are not so many competitors. Of course, those can be called services like Google or Facebook, but they don’t willingly share what they know about their audience. Maximum – they help in targeting advertising within the same service. But, firstly, the operator data has more connection with the offline, so they are useful, for example, in improving the urban infrastructure. In the developed countries of the world, where the Internet of things is already fully introduced, it is mobile connections that are most often used to "connect" devices. Secondly, it is difficult to imagine a situation in which Google would share with the business some data about how the owner of the Android-smartphone behaves, being near its point, or helping the city in the creation of Smart City services.
But hoping for Big Data, Ukrainian operators are faced with another problem - a shortage of specialists in the industry. By and large, Ukrainian universities do not teach a new profession in demand, and now all the hope is mainly for those who understand the issue itself. The two largest mobile operators - Kyivstar and Vodafone - each took their own decision in the personnel question.
Vodafone Big Data Lab
This week Vodafone Ukraine announced the opening of Big Data Labs. As part of the project, the operator will provide its own data set for developers and specialists on big data. According to the company, daily users generate 400 terabytes. The project participants will have access to data of 100,000 subscribers from eight regions of Western Ukraine (data will be depersonalized, altered and coded), as well as to computing power to work with this data.
The operator is interested in solutions for the city and business, as well as improving the quality of life. The project will last three months, the entry for participation is already open, the selection will be held until November 24. Participants should be familiar with statistical data analysis, have experience working with Python / R. and demonstrate creativity. There can be independent IT professionals, students and corporate development teams. Within the framework of the project, it is envisaged to provide lessons with operator data, a hackathon and an accelerator for specialists. The winning projects will be presented to investors.
Big Data School from Kyivstar
Kyivstar for studying machine learning and data science has opened Big Data School. The course is aimed at students, developers, analysts and mathematicians, their teachers are specialists in the field of big data. The students of the course get access to the anonymous data of the operator for the period of training, and during the course they will solve the real business task of the client. Graduates of the course can receive the job in the company. Kyivstar boasts that their student and subsequently a young employee was bought by Google, and one of the former students and current employees developed a scoring system for fighting fraud - the product is used by one of the banks.