Page 54 - Contributed Paper Session (CPS) - Volume 6

CPS1490 Nehall Ahmed Farouk Mohamed
sample of the available big data set makes it quite easy, as it shrinks the size
of data to be trained, also using decentralized storage.

4. Discussion and Conclusion
A massive work had been done in studying big data analytics, especially
predictive analytics. Some problem blocks the completeness of using ML in
big data predictive analysis. Recently some of these problems have been
solved. The overall work of deep learning in this manner is enhanced than
before. But there still an open issues to be studied in the future, like: (a)
training a sample of the data, needs to define the adequate sample design. (b)
The granularity issue needs to be studied over different categories and
classifications to see how it might effect. (c) The issue of the continuous
streaming of data.

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