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Data Products

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Abstract

Data science is becoming an established scientific discipline and has delivered numerous useful results so far. We are at the point in time where we begin to understand what results and insights data science can deliver; at the same time, however, it is not yet clear how to systematically deliver these results for the end user. In other words: how do we design data products in a process that has relevant guaranteed benefit for the user? Additionally, once we have a data product, we need a way to provide economic value for the product owner. That is, we need to design data-centric business models as well.

In this chapter, we propose to view the all-encompassing process of turning data insights into data products as a specific interpretation of service design. This provides the data scientist with a rich conceptual framework to carve the value out of the data in a customer-centric way and plan the next steps of his endeavor: to design a great data product.

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Correspondence to Jürg Meierhofer .

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Meierhofer, J., Stadelmann, T., Cieliebak, M. (2019). Data Products. In: Braschler, M., Stadelmann, T., Stockinger, K. (eds) Applied Data Science. Springer, Cham. https://doi.org/10.1007/978-3-030-11821-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-11821-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11820-4

  • Online ISBN: 978-3-030-11821-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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