Writing Homework Help

Response 1: Hareesh Kumar Nadendla

One of the most common privacy concerns with data mining in the United States and most other developed economies is the government’s collection of data by an employee’s social media activity or online use of the Internet. The privacy issue with data mining refers to a systematic collection of information about individuals such as Internet usage, social network history. Data mining uses machine-learning algorithms and statistics to analyze data to extract insights from large amounts of data (Sharda et al., 2020). There are many data mining techniques, from data analysis in medical imaging to machine learning in the financial industry to data mining in health care. A privacy issue with data mining is a severe issue when it comes to data mining. The increasing sizes of datasets, the complexity of processing individual pieces of data, and the speed with which data process has raised many privacy issues. Information systems and data mining are all interconnected (Sharda et al., 2020). The number of data sources available to a data miner and the increasing speed with which data process can create an opportunity to access large amounts of data without appropriate safeguards.

A privacy issue with data mining is an integrated discipline where many different algorithms apply to the same problem. Information processing is an interdisciplinary sub-field in which research activities focus on creating new types of information, methods, and technologies for analyzing, identifying, constructing, and using information. Data mining often regard as a tool that can help companies gather information about their customers by finding out what activities are taking place on their web or mobile devices (Kalunge & Deepika, 2021). The Privacy issues with Data mining, also known as data mining, data mining analytics, and data mining analytics, is a field of study used to analyze the structure of a specific type of data, such as text, images, or sounds. Data mining by scientists, engineers, and others want to develop algorithms that can predict something from a few trillion individual pieces of information (Kalunge & Deepika, 2021). Privacy issues with data mining, in the context of data mining, refer to various techniques. Techniques for mining large quantities of data include using a distributed hash table, mining for large sets of critical terms, finding nonlinear relations, and finding relations among different objects. Privacy issues with data mining are essential to understand the concern in data mining, a critical aspect of corporate governance and compliance, and how data mining can integrate into business strategies.

References

Kalunge, V., & Deepika, S. (2021). Data Mining Techniques for Privacy Preservation in Social Network Sites Using SVM. In Techno-Societal 2020 (pp. 733-743). Springer, Cham.

Sharda, R., Delen, Dursun, and Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support. 11th Edition. By PEARSON Education. Inc.