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2021•2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP)Requires access

A Review on Privacy-Preserving Techniques in Data Analytics

Norsyahirah Khairul Anuar, Asmidar Abu Bakar, Aishah Abu Bakar

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Abstract

This paper reviews privacy-preserving techniques in data analytics. Data analytics is a concept of processing raw data and analysing the output for various beneficial reasons. There are four types of data analytics stated in this paper, those are descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Data itself contains unstructured, semi-structured and structured data. We compare the privacy-preserving techniques in data analytics to see whether the techniques are suitable or unsuitable to be applied in data analytics.

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What this paper is about

This paper reviews privacy-preserving techniques in data analytics. Data analytics is a concept of processing raw data and analysing the output for various beneficial reasons. There are four types of data analytics stated in this paper, those are descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Data itself contains unstructured, semi-structured and structured data. We compare the privacy-preserving techniques in data analytics to see whether the techniques are suitable or unsuitable to be applied in data analytics.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper reviews privacy-preserving techniques in data analytics. Data analytics is a concept of processing raw data and analysing the output for various beneficial reasons. There are four types of data analytics stated in this paper, those are descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Data itself contains unstructured, semi-structured and structured data. We compare the privacy-preserving techniques in data analytics to see whether the techniques are suitable or unsuitable to be applied in data analytics.

Key concepts: Analytics, Data analysis, Computer science, Data science, Software analytics, Big data, Raw data, Business intelligence

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