An overview of business intelligence technology

By Surajit Chaudhuri, Umeshwar Dayal, Vivek R. Narasayya. Communications of the ACM, 2011

867 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/e536ba7e37bedc07d5cf665738d53616d758c856

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In Computer Networks and Communications

In Management Information Systems

In Management Science and Operations Research

Citations in the corpus

Impact of business analytics and enterprise systems on managerial accounting (2017, background): “Business Intelligence as such may be considered as the management support system for gathering, storing, accessing, and analyzing data for decision making (Chaudhuri et al., 2011).”
The SAP HANA Database -- An Architecture Overview (2012, background): “For those types of reporting, column-stores have become more and more popular [3].”
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories (2021, background): “, building a data warehouse and obtaining aggregated tables, cubes and other graphical representations from the data) [50], but also those that follow more exploratory or interactive scenarios, such as those common in visual analytics [51].”
Business intelligence & analytics in management accounting research: Status and future focus (2018, methodology): “…leading BI&A vendors (Gartner, 2017), there are four basic technological elements of BI&A applications in any organization (Chae and Olson, 2013; Chaudhuri et al., 2011; Elliot and Woodward, 2015; Howson, 2007, 2013; Howson and Arnold, 2013; Sheikh, 2013; Troyansky et al., 2015; Volitich and…”
Big Data: A Survey (2014, background): “Some literature [26–28] discuss obstacles in the development of big data applications.”
Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (2014, background): “Recent works [38], [45], [46] have discussed potential obstacles to the growth of big data applications.”
A Survey on Deep Learning in Big Data (2017, background): “One of the unique characteristics of deep learning algorithms is its ability to utilize unlabeled data during training [34].”
Debating big data: A literature review on realizing value from big data (2017, background): “In essence, sophisticated technologies (Chaudhuri et al., 2011) increasingly allow actors to integrate heterogeneous sources of data and extract insights from their combination.”