Browsing by Author "Eichler, Rebecca"

Now showing 1 - 4 of 4

Open Access
A recommender approach to enable effective and efficient self-service analytics in data lakes
(2023) Stach, Christoph; Eichler, Rebecca; Schmidt, Simone
As a result of the paradigm shift away from rather rigid data warehouses to general-purpose data lakes, fully flexible self-service analytics is made possible. However, this also increases the complexity for domain experts who perform these analyses, since comprehensive data preparation tasks have to be implemented for each data access. For this reason, we developed BARENTS, a toolset that enables domain experts to specify data preparation tasks as ontology rules, which are then applied to the data involved. Although our evaluation of BARENTS showed that it is a valuable contribution to self-service analytics, a major drawback is that domain experts do not receive any semantic support when specifying the rules. In this paper, we therefore address how a recommender approach can provide additional support to domain experts by identifying supplementary datasets that might be relevant for their analyses or additional data processing steps to improve data refinement. This recommender operates on the set of data preparation rules specified in BARENT-i.e., the accumulated knowledge of all domain experts is factored into the data preparation for each new analysis. Evaluation results indicate that such a recommender approach further contributes to the practicality of BARENTS and thus represents a step towards effective and efficient self-service analytics in data lakes.
Open Access
Classification of cryptographic libraries
(2017) Poppele, Andreas; Eichler, Rebecca; Jäger, Roland
Software developers today are faced with choosing cryptographic libraries in order to implement security concepts. There is a large variety of cryptographic libraries for diverse programming languages, without there being a standardized conception of different properties of these cryptographic libraries. This report provides a classification of over 700 cryptographic libraries. The libraries were chosen pertaining to currentness and popularity. In order to provide a standardized overview the most important traits and characteristics of these libraries were gathered and defined. Data collection on these characteristics was performed in a manual as well as automated fashion. The classification contains information that will help experienced and inexperienced developers in the cryptographic field to choose a library that fits their abilities. Furthermore, it may be used as a basis for studies concerning any form of improvement of these libraries and many more.
Open Access
The Enterprise Data Marketplace : a platform for democratizing company data
(2024) Eichler, Rebecca; Mitschang, Bernhard (Prof. Dr.-Ing. habil.)
In the era of big data, multitudes of data are generated and collected in companies. This data contains a potential value that can be leveraged to gain new insights, e.g., for enhancing business models or reengineering industrial products. Extracting data value requires that this data is available for use. Yet, studies show that significant amounts of the data remain unused in companies. In this regard, data democratization initiatives, with the goal of empowering company employees to find, understand, access, use, and share data, are gaining in importance. Towards this end, data marketplaces are studied as metadata-based platforms to facilitate the exchange and provisioning of data and data-related services. However, data marketplaces are mainly investigated for the exchange of data and services between organizations or private individuals, i.e., as external data marketplaces. Little research focuses on the use of data marketplaces in the company-internal context, i.e., as an Enterprise Data Marketplace (EDMP). Topics of how the EDMP differs from an external marketplace, the scope of its offerings and functionality, challenges that arise in the company-internal context, or how the EDMP can be embedded in and leverage the existent company system and tool landscape have not been investigated in detail thus far. In this thesis, the Enterprise Data Marketplace is examined as a platform for democratizing data in companies, and in this context, the above-listed gaps are addressed. To this end, four research goals (RGs) are put forward: (RG1) the identification of the processes and challenges company employees face in finding, understanding, accessing, and sharing data in the enterprise without an EDMP; (RG2) the identification of the distinctive aspects of an EDMP; (RG3) establishing an architectural foundation for building an EDMP; and (RG4) the goal of leveraging existent metadata in the company tool and system landscape in the EDMP. The research goals are covered through nine research contributions. These entail the current data provider and data consumer journeys and challenges, an EDMP type distinction based on an EDMP definition, as well as a presentation of its distinctive characteristics, requirements, and challenges. An enterprise integration and platform architecture, together with an approach for leveraging existent metadata, yields the foundation for building an EDMP. The feasibility of the concepts put forward in this thesis is demonstrated through an EDMP prototype and an evaluation based on an experiment and qualitative assessment. The evaluation yields that the EDMP is well-suited for the effective realization of data democratization within companies and that it not only addresses several of the current issues data providers and consumers face but also increases the efficiency and reduces the complexity in accessing data. This thesis therefore introduces the EDMP as a platform for democratizing company data and lays the foundation for establishing the EDMP within a company.
Open Access
Introducing the enterprise data marketplace : a platform for democratizing company data
(2023) Eichler, Rebecca; Gröger, Christoph; Hoos, Eva; Stach, Christoph; Schwarz, Holger; Mitschang, Bernhard
In this big data era, multitudes of data are generated and collected which contain the potential to gain new insights, e.g., for enhancing business models. To leverage this potential through, e.g., data science and analytics projects, the data must be made available. In this context, data marketplaces are used as platforms to facilitate the exchange and thus, the provisioning of data and data-related services. Data marketplaces are mainly studied for the exchange of data between organizations, i.e., as external data marketplaces. Yet, the data collected within a company also has the potential to provide valuable insights for this same company, for instance to optimize business processes. Studies indicate, however, that a significant amount of data within companies remains unused. In this sense, it is proposed to employ an Enterprise Data Marketplace, a platform to democratize data within a company among its employees. Specifics of the Enterprise Data Marketplace, how it can be implemented or how it makes data available throughout a variety of systems like data lakes has not been investigated in literature so far. Therefore, we present the characteristics and requirements of this kind of marketplace. We also distinguish it from other tools like data catalogs, provide a platform architecture and highlight how it integrates with the company’s system landscape. The presented concepts are demonstrated through an Enterprise Data Marketplace prototype and an experiment reveals that this marketplace significantly improves the data consumer workflows in terms of efficiency and complexity. This paper is based on several interdisciplinary works combining comprehensive research with practical experience from an industrial perspective. We therefore present the Enterprise Data Marketplace as a distinct marketplace type and provide the basis for establishing it within a company.