Major Project Theme



Big Data 

In recent years the amount of data that is being generated increased dramatically making way for big data. Big data refers to data so big that traditional processing tools can not handle such an amount effectively. According to IBM big data can be defined as 'data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency.' The attributes that define big data are volume, variety, velocity, and variability. Big data became an integral part of many industries. With the usage of the internet and the development of technology more data is being stored. It is due to the Internet of Things, Artificial intelligence, social media or simply mobile devices where data is being constantly collected.
Machine learning is a part of artificial intelligence that involves the use of algorithms to enable machines to learn from data and improve their performance over time without being explicitly programmed. Machine learning algorithms are particularly useful for analyzing big data, as they can detect patterns and trends that would be difficult for humans to identify.
The combination of big data and machine learning is a huge beneficent for industries. By collecting algorithms from machine learning data can be analyzed which can result in making better predictions by the companies. For example in healthcare algorithms can be used to evaluate the patients data to prevent them from getting diseases. In finance, machine learning is used to detect misleading activities and make better investment decisions. In marketing, machine learning is used to analyze consumer data to improve customer experience and increase sales.




References:

Geissinger, M. (2017). Available at: https://www.pexels.com/photo/black-server-racks-on-a-room-325229/ (Accessed: 07 May 2023).

Big Data Analytics (no date) IBM. Available at: https://www.ibm.com/analytics/big-data-analytics (Accessed: 27 April 2023). 

 


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