Digitalization changes organizations. Data-driven companies not only consider how to improve operational and management processes using data (analysis), but they also think about data products that are delivered as a service to customers. In this post, we will explain what data products and data as a service are, give some examples of different kinds of data products, and also highlight key challenges to tackle when designing and offering such products.
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What Is a Data Product?
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Data analysis aims to retrieve information from data to support or enable decisions. Relevant pieces of information are identified and delivered via business intelligence tools or applications on computers and mobile devices. Which pieces of information are relevant depends on the business process that is being supported. That is where domain knowledge comes in.
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Data analysis can be carried out using business intelligence tools for ad-hoc reporting or Online Analytical Processing (OLAP), or advanced analytical methods can be employed. Providing for reporting and data analysis services on a defined set of data in a software product, we get a simple data product. Generally speaking, data products are a new category of services powered by analytics, business domain knowledge, and scalable IT architectures.
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There are several categories of data products. A simple one is reports, where data is descriptively displayed and made transparent to the user. A typical example would be reports for telephone or credit card bills that are provided to customers and create a value-add by providing more timely information and additional analysis possibilities. A good example is benchmarking, another type of data product. Here, a particular behavior or key performance indicator (KPI) is compared across industries or users. Social networking websites such as ResearchGate and LinkedIn create engagement with users by displaying information about how they score compared to other users in terms of visibility…