Big data: Issues, challenges, tools and Good practices

By Avita Katal, M. Wazid, R. Goudar. International Conference on Contemporary Computing, 2013

927 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Big Data: Survey, Technologies, Opportunities, and Challenges (2014, background): “The following section details various Hadoop projects and their links according to [12, 50–55].”
Learning under Concept Drift: A Review (2019, background): “Data mining in big data environments faces similar challenges to stream data mining [124], [125]: data is generated”
The Challenges of Data Quality and Data Quality Assessment in the Big Data Era (2015, background): “The characteristics of big data come down to the 4Vs: Volume, Velocity, Variety, and Value (Katal, Wazid, & Goudar, 2013).”
Social media big data analytics: A survey (2019, neutral): “For instance, social media assists organizations to obtain customers' feedback regarding their products, which can be used to modify decisions and to obtain value out of their business (Katal, Wazid, & Goudar, 2013; Wu, Zhu, Wu, & Ding, 2014).”
A Bibliometric Analysis and Visualization of Medical Big Data Research (2018, background): “Big data has the characteristics of the “5V” [3]: Variety: the data is from a variety of sources, and the types and formats of data are becoming richer.”
A survey on addressing high-class imbalance in big data (2018, background): “[5] state that these properties, notably associated with big data, make modeling and analysis of such data with traditional methods difficult.”