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Co-founder and CEO Manfred Spatzierer is Austria’s leading meteorologist and in charge of UBIMET’s department for meteorology and model development.

UBIMET is the leading private weather service provider and the number one address when it comes to meteorological solutions. The founder-led company with a presence on three continents stands for reliable, tailor-made, high-precision weather information and digital services for weather-dependent industries. As a global innovation leader top companies from branches such as insurance, energy, infrastructure, media or sports as well as champions of the new economy rely on us. UBIMET provides high-quality meteorological data, forecasts and warnings that allow weather-dependent industries around the globe to increase safety and efficiency.

UBIMET is one of the original companies taking part in EDI from 2018 and has now decided to repeat again in the second year. Could you tell us how you found out about the European Data Incubator, and why UBIMET decided to apply?

Spatzierer: We have been involved in EDI since the very start, because we realised the huge potential of this initiative for us. UBIMET as one of the leading providers of high-precision meteorology, which processes 90TB of data per day, has always been a Big Data company. Big Data is defined according to the 3V-model using the attributes volume, variety and velocity. The term volume stands for the huge amounts of data which are hard to analyse using conventional means. Variety describes the enormous multitude of data types (and sources), whereas velocity expresses the extremely high rates at which data is processed nowadays. Weather data clearly exhibits all of these attributes. However, our approach to data analysis is of course a meteorological one.

EDI offers us the opportunity to explore new ways for disruptive innovation using Big Data analysis. Even though we are a recognised Big Data specialist, we can also learn from how start-ups deal with our weather data in the EDI challenges. This mutually beneficial process helps us improve our own methods and models and sometimes shows us completely new directions. Nevertheless, the primary motive for us to serve as a data provider for EDI has been to support promising new start-ups with our longstanding experience in Big Data. Helping them to develop weather-related new products that are successful in the market and beneficial for a broader audience is a very satisfying task.

What challenge have you proposed to the EDI start-ups and why did you select this challenge?

Spatzierer: For the first call in 2018 we designed a very difficult challenge, which asked the applying start-ups to find anomalies in weather data from different sensors in the field and mark them. Usually, such anomalies are rather difficult to detect since they are hidden in long sets of data. An anomaly for instance can be a slightly distorted temperature reading from a weather station that turns out to be affected by local vegetation. In the first call, this challenge as well as the necessary weather data came from us.
For the second call in 2019 we provide our highly precise reanalysis data for all kinds of challenges to be solved by interested start-ups. So, this time, we are speaking about the half & half challenge, where start-ups can bring their own challenge and try to solve it with our weather data. Concerning next year’s third call, we are working on a very exciting, innovative new challenge. Details are still secret, but I think a lot of Big Data start-ups will love it.

Which start-ups did you work with for the first round? Having worked with these teams, how has your relationship developed and do you see potential for working together after EDI has ended? (Do you intend to purchase their solution or work on other projects in the future?)

Spatzierer: In the first round we were working with a promising new Italian start-up specialised on scientific climatological consulting called Amigo Climate. As mentioned above, Amigo’s challenge was to detect anomalies in our weather data and mark them. The guys from the Rome based company turned out to be a pleasure working with. Communication has always been very transparent and professional making coordination and intellectual exchange efficient and smooth. The working climate has been very warm and characterised by mutual respect and awareness of each other’s capabilities and strengths. Amigo followed an incremental approach in solving the challenge, which proved to be extremely useful. We expect the detection capability of their algorithm to improve further through the acquisition of new customers and consequently new sets of data being integrated in their calculations.

However, the incubator is not only about solving the challenge. Eventually EDI is about helping a start-up to develop a mature, market-ready product, generating revenue and satisfying customers’ needs. So eventually, the idea is to help promising start-ups to succeed on the market. I think in Amigo’s case the odds are pretty good. Its participation in EDI could really lay the foundation of a valuable new business model for the company.

Could you expand on the value that the start-ups solutions have brought to UBIMET?

Spatzierer: After all, Amigo came up with a very useful solution, even though some aspects still need a little bit of fine tuning. The results do not yet outperform our in-house approach for finding anomalies in big sets of data from weather stations. But the cooperation with Amigo quite impressively proved the strengths of pure Big Data solutions over classic modelling in meteorology for certain problems. In my opinion, there clearly is a niche for these Big Data approaches in meteorology, although it always depends on the case in question. Perhaps Amigo’s findings can even help us improve our capabilities in delivering high-precision forecasts in the future. I honestly see a huge potential for that.

Finally, what would you say to another corporate thinking of applying to be a data provider in EDI?

Spatzierer: Go for it! Big Data methods can be extremely useful to successfully resolve highly complex challenges ranging from sales to traffic forecasts. Very often, Big Data analysis provides totally new insights into your data that potentially can be very illuminating, especially, when you correlate your data with our sophisticated weather data. However, a lot of companies are extremely afraid of sharing their own data sets with others, because they worry competitors might acquire knowledge and insights they are not supposed to get. Of course, nobody wants to share a business secret with outsiders. That’s why EDI provides a secure Big Data infrastructure which serves as a neutral platform for both, the data provider as well as the start-up participating in EDI. As a result, the start-up can work with the data in a safe environment and forward the results to the data provider. The infrastructure makes sure that this is a beneficial win-win situation for both. So, don’t hesitate to apply as a data provider. From over a year of experiencing EDI, I can tell you, it’s really worth it.

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