Machine Learning Approach for Cloud Data Analytics in IoT

Figure 3.10 Heatmap of the world.

Thus, from the above case study, it is clear that data analytics can be quite helpful for a retail industry, and thus, it has a huge potential in retail apart from various promising fields.

This chapter has discussed the potential and capability of ML approaches for predictive data analytics in the retail industry. Various models have also been discussed briefly. Few use cases have been presented to give readers a clear idea about the spectrum of its application in the retail industry. Although it has observed widespread applications, it still bears some challenges. These challenges as discussed above must be addressed by taking the research ahead.

First and foremost, researchers must work in the direction of maintaining security and privacy of data as data is the most precious asset for any organization. Work should also be done in the direction of conceptualizing usage of big data so as to benefit retailers and customers. The research must be taken ahead in the direction of efficient customized promotions that basically sends promotional messages for a specific product to a specific customer at specific time. Implementation of customized promotion will further enhance the revenue generation. Additionally, it must also be ready to develop new operational models in response to the future need and growth of industry.

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1 *Corresponding author: rakhiakhare@gmail.com

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