Increased hardware capability has allowed many businesses to store massive amounts of data in the previous few years. Streams of data may go on forever, so they are used in so many different applications. Analyzing and querying these streams is challenging for a stream of dynamic information. The term "big data"refers to a collection of methods and tools that must be combined in novel ways to unearth the vast amounts of previously unseen information buried within vast, diverse, and intricate databases. There are several ways to obtain, organize and analyze data in the big data world. In order to deal with streaming data, efficient data mining procedures must be in place. In this article, we examine a variety of Big Data-related concerns and challenges. This paper introduces the features, and challenges of managing big data.
|Title of host publication||2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 15 May 2023|
|Event||2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023 - Dubai, United Arab Emirates|
Duration: 7 Mar 2023 → 8 Mar 2023
|Name||2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023|
|Conference||2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023|
|Country/Territory||United Arab Emirates|
|Period||7/03/23 → 8/03/23|
Bibliographical noteFunding Information:
This research was supported by the National Key R&D Program of China (grant 2016YFA0500901), the National Science Fund for Distinguished Young Scholars (81925015), and the National Natural Science Foundation of China (grants 91649202). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The following grant information was disclosed by the authors: National Key R&D Program of China: 2016YFA0500901.
© 2023 IEEE.
- Big data
- data mining