The digital shift in society is making continuous growth of data. However, choosing a suitable storage architecture to efficiently store, process, and manage data from numerous sources remains a challenge. Currently, there are three storage architecture generations in practice, and the most recent one is Data Lakehouse. Given its novelty, limited research has been done into the rationale behind its introduction, strengths, and weaknesses. In order to fill this gap, this study aims to investigate the secure value (comparative strengths) of the data lakehouse architecture compared to data warehouse and data lake architectures. After conducting a comprehensive systematic literature review, we propose a data storage evolution model showing the comparative strengths and weaknesses of data warehouse, lake, and lakehouse architectures. With the use of the proposed model and expert interviews, this study demonstrates the secure value of the data lakehouse compared to the preceding architectures. In addition, the study presents a high-level view of the overlapping strengths of data Lakehouse with both data warehouse and data lake. In essence, the artifact produced by this study can be used to explain the rationale behind the evolution of data storage architectures. Further, the proposed model will help the practitioners in studying the trade-off between different architectures to offer recommendations. Finally, authors acknowledge that this study has several limitations, such as the limited sample size for the interviews and the bias due to the use of qualitative research approach. However, all the available measures were taken to minimize the effects of these limitations.

E3-value has proven to be a useful modeling technique and method to support the analysis of business models. However, for strategic analysis, the representation of a business model is not sufficient, as it does not include the rationale behind the model. In this paper, we propose an extension of e3-value to support strategic analysis on three dimensions: competition analysis, customer analysis and capability analysis

From a strategic enterprise perspective, the success of e-services depends on their ability to work as a medium for the exchange of business values. Thus, there is a need to be able to describe and analyze business collaborations in a structured way, in order to identify the needs and appropriate offerings of the participating actors. To model business collaborations, business value models are increasingly used. However, a question remains - how to systematically create value models in order to identify the offerings of the involved actors, while spanning the whole life-cycle of a business collaboration? In this study we propose a method for designing more exploratory business models with a focus to how: (a). consumers classify values, and (b). the values are elicited in different phases of business collaboration life-cycle. A case study from the Swedish health care sector is used to ground and apply the presented method.