A Survey of Challenges Facing Streaming Data

  • Sikha Bagui University of West Florida
  • Katie Jin University of West Florida
Keywords: Streaming Data, Sliding Windows, Concept Drift, Data Preprocessing, Data Reduction, Data Streams


This survey performs a thorough enumeration and analysis of existing methods for data stream processing. It is a survey of the challenges facing streaming data. The challenges addressed are preprocessing of streaming data, detection and dealing with concept drifts in streaming data, data reduction in the face of data streams, approximate queries and blocking operations in streaming data.

Author Biographies

Sikha Bagui, University of West Florida

Dr. Sikha Bagui is Professor and Askew Fellow in the Department of Computer Science, at The University West Florida, Pensacola, Florida. Dr. Bagui is active in publishing peer reviewed journal articles in the areas of database design, data mining, BigData and Big Data analytics, and machine learning. Dr. Bagui has worked on funded as well unfunded research projects and has over 70 peer reviewed publications. She has also co-authored several books on database and SQL. Bagui also serves as Associate Editor and is on the editorial board of several journals.

Katie Jin, University of West Florida

Katie Jin completed her MS in Computer Science at The University of West Florida. Her interests are in Big Data Analytics and Machine Learning.


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How to Cite
Bagui, S., & Jin, K. (2020). A Survey of Challenges Facing Streaming Data. Transactions on Machine Learning and Artificial Intelligence, 8(4), 63-73. https://doi.org/10.14738/tmlai.84.8579