Ghada Eltaweel

Work place: Computer Science Department, Faculty of Computers and Information, Suez Canal University, Ismailia, 41611, Egypt

E-mail: ghada@ci.suez.edu.eg

Website:

Research Interests: Computer systems and computational processes, Computational Learning Theory, Image Compression, Image Manipulation, Image Processing

Biography

Ghada Eltaweel is an associate professor at computer science Dept., Faculty of Computers and Information, Suez Canal University, Egypt. She had received her B.Sc. from faculty of science Cairo University. She had received her M.Sc. from Helwan University, Egypt. He had received her Ph.D. from faculty of computers and informatics Cairo University. Her current research interests are Machine Learning, and biomedical image processing.

Author Articles
Enhancing Big Data Value Using Knowledge Discovery Techniques

By Mai Abdrabo Mohammed Elmogy Ghada Eltaweel Sherif Barakat

DOI: https://doi.org/10.5815/ijitcs.2016.08.01, Pub. Date: 8 Aug. 2016

The world has been drowned by floods of data due to technological development. Consequently, the Big Data term has gotten the expression to portray the gigantic sum. Different sorts of quick data are doubling every second. We have to profit from this enormous surge of data to convert it to knowledge. Knowledge Discovery (KDD) can enhance detecting the value of Big Data based on some techniques and technologies like Hadoop, MapReduce, and NoSQL. The use of Big Data value is critical in different fields.
This survey discusses the expansion of data that led the world to Big Data expression. Big Data has distinctive characteristics as volume, variety, velocity, value, veracity, variability, viscosity, virality, ambiguity, and complexity. We will describe the connection between Big Data and KDD techniques to reach data value. Big Data applications that are applied by big organizations will be discussed. Characteristics of big data will be introduced, which represent a significant challenge for Big Data management. Finally, some of the important future directions in Big Data field will be presented.

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