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ItemImplementation Challenges of Self Service Business Intelligence: A Literature Review( 2018-01-03)In a traditional Business Intelligence (BI) system, power users serve less experienced casual users. Power users analyze and gather data requested by casual users, and produce the reports and visualizations that casual users base their decisions on. When data volumes and the usage frequency of a traditional BI system increase, power users have problems serving all the requests from casual users. The Self Service Business Intelligence (SSBI) approach can enable users to be more self-reliant and less dependent on power users. Although SSBI promises more benefits compared to a traditional BI system, many organizations fail to implement SSBI. The literature review presented in this paper discusses six SSBI challenges related to "Access and use of data" and four challenges related to "Self-reliant users". Awareness of these ten challenges can help practitioners avoid common pitfalls, when implementing SSBI, as well as guide SSBI researchers in focusing on their future research efforts.
ItemDoing Good with Data: Development of a Maturity Model for Data Literacy in Non-governmental Organizations( 2018-01-03)Data literacy is the ability to use data productively and to think about it in a critically reflective way. However, can its complexity really be broken down to only this? Data literacy is one of the most important skills in the 21st century for organizations, employees, and citizens. We present a data literacy maturity model (DLMM) that was developed in the context of non-governmental organizations (NGOs). Based on the development of a preliminary maturity model, action design research (ADR) is used to develop the model throughout three iteration phases. The main contribution is a data literacy maturity grid that describes 11 data literacy competencies on four competence levels that is complemented by a self-assessment tool. The proposed maturity model should enhance the understanding of the required skills that are needed to kick off data projects, identify strengths and gaps, and thus empower to plan future data practices in accordance with predefined goals.
ItemOrganizational Data and Analytics Contracting in Smart City Fog Computing Platforms( 2018-01-03)Smart City infrastructures require contracts between public and private organizations collaborating in what is frequently referred to as fog computing platforms. We investigate contract provision variations from different stakeholder perspectives. Our methodology relies on complex adaptive systems theory, and we simulate different contract provision scenarios to identify patterns that emerge. The specific contract provisions we investigate in this paper are related to analytical model and data ownership paradigm variations. We find that some variations offer advantages to stakeholders that include those who participate in the smart city fog platform and those who may have ownership of smart city fog platform infrastructure.