Tag Archive for: Big Data

Data, data, nothing but data. What do we do with it?

According to an IDC study, the total amount of data generated annually worldwide will increase from 33 zettabytes to 175 zettabytes in 2025. IP traffic is also growing analogously. According to a Cisco study, annual global IP traffic will increase to 4.8 zettabytes by 2022. This naturally raises the question of how we want to use this enormous amount of data. For the use of the data, both Big Data analyses and traditional data analyses are important. From the business point of view, possibilities of data utilisation open up through modern business intelligence in order to be able to answer operative and strategic questions. Basically, these questions can be answered on the basis of intuition and experience. Furthermore, people and processes are of high importance and specific tools and concepts can be used. Finally, data and analysis are of central importance. Ideally, all four of the aforementioned aspects come together to answer strategic questions, for example. Especially the underpinning of intuition and experience with concrete, specific data is an added value in this area. The Business Intelligence application supports decision-makers in answering questions and also in asking new questions based on analyses. It is important that results are always critically questioned. Because thinking should be a main task of humans. Business Intelligence is not a new concept. However, it has gained in importance in everyday organisational life in recent years, among other things due to the enormous data generation, collection, linking and analysis. Simpler” methods, instruments and software for data analysis and visualisation, such as PowerBI or Tableau, also make a contribution. This is true both from an operational and a strategic point of view. They support decision-making, e.g. through reports and interactive dashboards. In essence, it is about effectiveness (“doing the right things”), such as the development of new business models or the adaptation of existing business models. But it is also about supporting decisions for initiatives to increase efficiency (“doing things right”) and thus about shaping and optimising an organisation, such as marketing or HR. Business Intelligence is no longer just a tool for (IT) specialists. It is becoming more and more important for normal business users in all areas of an organisation.


1] Reinsel, D., Gantz, J., Rydning, J.: “The Digitization of the World From Edge to Core”, 2018. 2] Cisco Visual Networking Index: Forecast and Trends, White Paper, 2017-2022.

Specialised course at BFH Wirtschaft

The BFH Wirtschaft offers a further education course in management and data-based business management. You can find all the information here.

Connecta Bern 2019

This article was written as part of Prof. Dr. Kim Oliver Tokarski’s presentation at Connecta Bern 2019 and first appeared on The Swiss Post.

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Open Data as a first step towards building a national data infrastructure

In order for government data to develop its potential benefits for the economy and society, it must be made available comprehensively and systematically. Of particular interest are basic registers and geodata for locating these entities. Together with other government data on topics such as transport, energy or healthcare, these form an intangible infrastructure whose coherence, quality and availability determine the successful development of a data economy. Just as public rail and road infrastructures have enabled the development of the industrial society, the knowledge society needs a national data infrastructure – Open Data is the first step on this path. Data is not “oil Although data is repeatedly referred to as the “petroleum” of the 21st century, this metaphor is wrong. Unlike oil, data can be used as an infrastructure resource – comparable to a lighthouse – without rivalry. The arbitrary copyability of digital data allows it to be used without preventing anyone else from sharing it. Moreover, data is an investment good that can be used to create services and end products and can be used for any number of different purposes (OECD 2014: 24). In its report “Data- driven Innovation for Growth and Well- being”, the OECD concludes that data is an important resource that can lead to new knowledge, products, processes and markets, and refers to this trend as data-based innovation (ibid. p. 4). Data can serve, on the one hand, as an infrastructural resource that can in principle be used by an unlimited number of users for an unlimited number of purposes for services and end products, and, on the other hand, as an input for analysis that allows new insights and automated decisions. Creating value with data Data-driven innovation is not a linear process; feedback loops as well as recurring phases of value creation are part of the process (see Figure 1). Today, however, the value chain of data from the first collection to the statement in statistics is still a long sequence of media discontinuities. Different requirements and systems complicate the process of creating or processing data, information and content. This not only slows down the process, but also reduces the quality of the data and unnecessarily complicates their interpretation.


Fig. 1: The Data Value Cycle (OECD 2014: 23)

The positive impact of data-based innovation is not limited to the ICT sector. The activities of financial service providers and companies in the business and professional services sectors are extremely data-intensive, so these companies will invest even more in the development of data-based innovations in the future. In addition, the OECD sees opportunities for data-based innovations in the health and education sectors as well as in public administration, which can have a major impact in a relatively short time (ibid. p. 5). Data governance In order to promote data-based innovation, strategic control and coordination of the Confederation’s data production, data publication and data use across the organisational boundaries of the administration (“data governance”) is needed. In order for data to be used as an infrastructure resource, suitable framework conditions are needed for access to the data as well as for sharing and interoperability of the data. For the regulation of data access, a spectrum opens up from closed data, which is only accessible to the data owner, to open data, to which the public has access without restrictions. Various options also open up for the further use of the data, from the prevention of any further use to free further use without any restriction (“public domain”). The most important obstacle to the free flow of data between potential users are data silos. Especially within large companies and in public administration, these hinder the free flow of data across organisational boundaries. Therefore, data governance must also regulate in particular the networking and integration of data stocks within an organisation. Linked Data is an important technical approach to meet this requirement for the networking and integration of data stocks across organisational boundaries. The Good Basic Data for Everyone programme in Denmark is a good example of the successful development of a national data infrastructure. The basic assumption is that opening up high-quality data as an infrastructure enables public authorities to better fulfil their core business across organisations. In addition, data liberalisation is seen as an innovation driver in Denmark. In the UK, a similar programme called the National Information Infrastructure has been underway since 2013. Starting point Open Data For a few years now, individual federal offices, cantons and cities in Switzerland have begun to make government data available to the public as open data for free use. This is gratifying and de facto a first step on the way to a national data infrastructure. But it is far from sufficient. In order for government data to effectively unfold its enormous potential benefits for the economy, society and culture, it must be made available comprehensively and systematically. Of particular interest are those basic data that are permanently used in all areas of life in the knowledge society: Registers on persons, companies and buildings, addresses as well as geodata for the localisation of these entities.

“Typically, Key Registers hold essential and frequently used public sector information pertaining to persons, companies, land, buildings and other ‘infrastructural’ elements critical to the proper functioning of government. The rationale for establishing a System of Key Registers is the notion that it is in fact infrastructure that is indispensable for fulfilling governmental policy ambitions and societal needs in the context of the evolving (digital) relationship between a government and its citizens and companies” (de Vries/ Pijpker 2013: 4).

Together with other public sector data, e.g. from transport, energy, health, public finances or weather, these basic data form an intangible infrastructure whose coherence, quality and availability determine the successful development of a data economy and culture. Vision National Data Infrastructure Switzerland The EU Commission sees the realisation of a digital single market as a political priority. From its perspective, infrastructure – including data infrastructure – is also a key prerequisite for exploiting the potential of the digital economy. If Switzerland wants to exploit the potential of data-based innovations for economic growth and social well-being in the coming years, then the opening up and networking of the public administration’s and the entire public sector’s data resources, which have so far been isolated in individual silos, is a mandatory prerequisite. Starting with the basic registers for companies, buildings and persons, as well as geographic base data, the national data infrastructure must encompass all data sets from areas such as health, energy, transport, education, etc. that are relevant for the functioning of Switzerland. These data sets should no longer be regarded as isolated installations, but as parts of an overarching intangible infrastructure that enables the development of data-based services and the extraction of relevant knowledge about Switzerland. This infrastructure must make access to the data via online data catalogues, download services, API, etc. as open and simple as possible and only restrict it where legal requirements such as the protection of privacy make it mandatory. In addition to the basic data and data from various economic, administrative and scientific areas, the data infrastructure also includes directories of the data holdings, reference data, terminologies and other tools for indexing the data.


Fig. 2: National data infrastructure

The national data infrastructure is designed to enable the creation of data-based services and applications across different application areas with minimal effort. It is a platform and engine for cross-organisational cooperation and data-based innovations.


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Data as an innovation driver of the smart city

Data has already been called the “oil of the 21st century”. But data will also form the basis for many processes in the intelligent city of the future – the smart city. This will require a platform in which data from a wide variety of sources – sensors and the Internet of Things, open data, government data, data from social media and other third-party providers – can be processed, linked and analysed to extract valuable information and make it available as Linked Open Data. Based on this, both cities and private providers can offer new-value applications and services; the platform thus becomes a location factor and an innovation driver. With increasing digitalisation, society is facing new challenges. At the same time, increased urbanisation is taking place. The societal challenges thus manifest themselves most clearly in the city: densification, public transport, efficient use of resources such as energy and water, security, and – central to the city dweller – improvement of the quality of life. It is therefore worthwhile to address the societal challenges in the urban environment first; a recent OECD study (OECD, 2015) also refers to “cities as hubs for data-driven innovation”. A research project coordinated by the BFH called “City Platform as a Service – Integrated and Open”, or CPaaS.io for short, was launched in July 2016. The project is a collaboration between partners from Europe and Japan and is funded under Horizon 2020 and by the Japanese NICT. It aims to build a cloud-based platform for cities and urban regions that will provide the basis for urban data infrastructure and innovation. The need for such a platform is supported e.g. by a study (Vega-Gorgojo et al., 2015): The study emphasises that “the city will need platforms that support digitalisation and the use of data, culminating in Big Data”, and that “the smart city must work with platforms on which data can be analysed and shared with other sources” smart-city-innovation The goal of an innovation platform is ambitious. It is not just about realising a technical platform, or connecting complementary technologies such as the Internet of Things, Big Data and Cloud. Other projects do that too. Smart City Innovation means that the platform, or new applications and services based on the platform, provide real added value for society and for the actors in the city – residents, visitors, private companies and the public administration. To achieve this, the platform must be open, both in terms of the integration of other data sources and the access of third parties to the data (keyword: open data), naturally in compliance with data protection. In the urban environment, the integration of open public authority data is of particular interest. The project benefits from the fact that more and more authorities are following this trend and publishing their data on open data portals – in Switzerland, for example, on opendata.swiss, but the city of Zurich is also one of the pioneers in this field. CPaaS.io will go one step further here and also make the relevant data available as Linked Data. This means that the data is semantically annotated and also provided with metadata, e.g. on the provenance and quality of the data. Only this enables a simplified machine integration and use of the data in further applications. This can be used during large events, for example: In which direction do streams of visitors move? How has public transport been adapted to the current situation? How is the system reacting to dangerous situations, accidents, weather conditions, etc.? In order to identify beneficial applications for society, to implement them in the project, and thus to be able to validate the benefits of the platform, the involvement of cities is of central importance. To this end, the project has been able to initiate cooperation with several cities that already have experience in the areas of Open Data or Smart City. In Europe, these are Amsterdam, Murcia and Zurich, and in Japan Sapporo, Yokosuka and Tokyo. Field trials are planned in several of these cities. We are convinced that the longer we have more and more data, the more important it becomes to be able to master the social and economic challenges. Based on data infrastructures like the ones CPaaS.io will deliver, new applications and services will be offered and transparency will be increased. And for cities, this will become an important location factor, because innovative companies will prefer to settle where such platforms are available that they can use to provide their services.

Project details Duration: 30 months. Partners: Bern University of Applied Sciences, AGT, NEC, Odin Solutions, The Things Network, University of Surrey, YRP Ubiquitous Networking Laboratory, ACCESS Co, Microsoft Japan, Ubiquitous Computing Technology Corporation, University of Tokyo. Acknowledgements logo-eu The project is funded by the European Union’s Horizon 2020 Research and Innovation Programme (Grant Agreement n° 723076) and NICT in Japan (Management Number 18302).


  • OECD (2015). Data-Driven Innovation: Big Data for Growth and Well-Being. Paris: OECD Publishing, p. 379ff.
  • Vega-Gorgojo, G., et al. (2015). Case study reports on positive and negative externalities. EU FP7 Project BYTE, pp. 141 & 138.
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