Section 3 briefly describes the research design, which comprises the applied literature search and analysis strategy. 2, we describe the evolution of BI & A and provide insights into corresponding literature reviews in the field. The remainder of this paper is structured as follows. We conceptualize these underrepresented research characteristics by suggesting a research agenda for future research in the field. Fourth, our analysis clearly reveals research gaps, in which no or only little research exists. ( 2012) and its differences to the observed developments in the past decade. Third, our results foster discussions about the predicted developments in the field, as described by Chen et al. Second, based on that taxonomy, we provide a structured and extensive overview on relevant and up-to-date big data research results within the IS discipline. First, we develop a taxonomy to enable a rigorous classification of BI & A research results. Thereby, our research contribution is fourfold. Against this background, the paper at hand provides an answer to the following research question: How did information systems (IS) research address the emerging research area BI & A 3.0? We aim at drawing a comprehensive descriptive overview about research in the field of BI & A 3.0 between 20. The article at hand extends the existing body of knowledge by a structured investigation of the third wave of BI & A. All existing literature reviews have in common that they either focus on the first or second evolution stage of BI & A or they applied an unstructured or semi-structured search strategy, which increases the probability of an uncompleted or inadequate result set (Vom Brocke et al. Several meta-studies exist that provide an overview on the status quo of the BI research field (e.g., Abbasi et al. ( 2012) published their highly-regarded special issue introductory article for business intelligence and analytics (BI & A) research in the journal MISQ in 2012, many researchers started investigating the third wave of BI & A. Both enable advanced opportunities of collecting and analyzing data. The new and even more changing third wave of data analytics began with new data sources, such as mobile devices and wireless connected sensors. The term big data, which describes the change of data in volume, velocity, variety, and veracity (Chen et al. After this first evolution stage of data analysis research, the upcoming of unstructured data, such as video streams, music or text files, led to an exponential increase of data to be analyzed. Techniques and corresponding research relied on data collection, extraction, and analysis capabilities (Chen et al. Until the early 1990s, structured data, such as numeric data in tables, dominated the area of data analysis. Since the beginning of data analysis in the early 1950s, researchers have been interested in developing new methods to provide insights into data using business intelligence (BI) tools that enable to produce and capture a large quantity of data (Davenport 2013 Davenport and Harris 2007).
Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. The analysis provides an overview on the status quo of BI & A 3.0.
BUSINESS INTELLIGENCE DEFINITION SCHOLAR ARTICLES FULL
Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. By this means, the paper’s contribution is fourfold. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. The third wave of BI & A comprises unstructured and sensor data of mobile devices. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. Thereby, in each decade the rapid development of technologies opened new room for investigation. Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research.
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