TY - JOUR TI - Beyond the hype: Big data concepts, methods, and analytics T2 - International Journal of Information Management AB - Size is the first, and at times, the only dimension that leaps out at the mention of big data. This paper attempts to offer a broader definition of big data that captures its other unique and defining characteristics. The rapid evolution and adoption of big data by industry has leapfrogged the discourse to popular outlets, forcing the academic press to catch up. Academic journals in numerous disciplines, which will benefit from a relevant discussion of big data, have yet to cover the topic. This paper presents a consolidated description of big data by integrating definitions from practitioners and academics. The paper's primary focus is on the analytic methods used for big data. A particular distinguishing feature of this paper is its focus on analytics related to unstructured data, which constitute 95% of big data. This paper highlights the need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats. This paper also reinforces the need to devise new tools for predictive analytics for structured big data. The statistical methods in practice were devised to infer from sample data. The heterogeneity, noise, and the massive size of structured big data calls for developing computationally efficient algorithms that may avoid big data pitfalls, such as spurious correlation. DA - 2015/// PY - 2015 DO - 10.1016/j.ijinfomgt.2014.10.007 DP - www.sciencedirect.com VL - 35 IS - 2 SP - 137 EP - 144 LA - en SN - 0268-4012 ST - Beyond the hype UR - https://www.sciencedirect.com/science/article/pii/S0268401214001066 Y2 - 2020/09/03/06:49:51 KW - Big data KW - Data science ER -