At the beginning of the seminar, Dr. Michael Kaufmann, lecturer at Lucerne School of Information Technology, introduced the topic and discussed the various definitions of big data. For example, while IBM defines it based on the four V-criteria of volume, variety, velocity, and veracity, the National Institute of Standards and Technology uses "variability" instead of "veracity" as the fourth "V." Demchenko's model, on the other hand, adds the fifth criteria of "Value." He then explained how management models can create value from data – in line with the interdisciplinary focus of the Data Worlds project – and used several applied examples to make his point.
Big data supports urban planning
Following the introduction, Victor Schlegel, Senior Manager of Big Data Solutions, explained how Swisscom uses big data to help its customers make decisions. He presented two projects involving mobility data from the Swisscom mobile network that is obtained from anonymous and aggregated signal positioning:
- ASTRA: Traffic trends
The mobility data of drivers (e.g. speed) on highways was analyzed to help the Swiss Federal Roads Authority (ASTRA) make predictions about traffic jams.
- Montreux: Parking garage
Montreux's visitor data was analyzed in accordance with certain questions in order to decide whether it is necessary to build a new parking garage. This meant vetting the data – for example based on the visitors' place of origin or means of transport, or whether they mostly come by car or train. The data provided answers for deciding for or against building the new parking garage.
Artificial intelligence helps get the job done
The third Big Data Seminar concluded with a presentation by Dr. Michael Baeriswyl, Head of Software-as-a-Service and an enabler at Swisscom, on the topic of artificial intelligence and its uses at Swisscom. He started by defining the term "artificial intelligence" as a combination of calculations, algorithms and data – three exponentially growing factors at the moment. He also explained why the topic of artificial intelligence is currently so popular.
Although he is aware that many people believe artificial intelligence will end up doing the work for us, he considers it simply to be a more effective means of coping with the flood of data. He presented three use cases of how artificial intelligence supports Swisscom:
- Trend barometer of customers
All interactions between Swisscom and its customers are gathered, aggregated, and made available to employees in some type of visual form, making it possible to query customers' attitudes to certain topics at any time (e.g. what opinions are there on TV topics today compared to four weeks ago?).
- Incident notifications
Customer feedback, for example on social media, is analyzed continuously, and if negative key words (e.g. "No signal") start to accumulate, an "incident notification" is sent automatically to the respective unit. This enables Swisscom to identify any problems at the earliest possible stage.
- Solution for call center
Artificial intelligence can help agents at call center to use queries as basis for devising solutions to the problems they or their customers encounter. This enables them to benefit from their colleagues' knowledge, while the machine running in the background learns more about the problem by analyzing the suggested solutions.
After the three events, the roughly 50 participants had a chance to exchange ideas on current research and business topics relating to big data, data science, and artificial intelligence over drinks and snacks.
The Big Data Seminar is one of the series of events that Lucerne University of Applied Sciences and Arts hosts every six months.
