DSC763: Customer Analytics / College of Computing, Informatics and Mathematics
There is a staggering amount of browsing data and buying patterns that can be found on online shop sites. Extracted customers’ data such as their preferences and navigations can be used to describe their past, present and future behaviours in relation to their purchasing decisions. This course will...
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Universiti Teknologi MARA (UiTM)
2020
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Online Access: | https://ir.uitm.edu.my/id/eprint/92459/1/92459.pdf https://ir.uitm.edu.my/id/eprint/92459/ https://aims.uitm.edu.my/ |
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my.uitm.ir.924592024-03-13T05:08:31Z https://ir.uitm.edu.my/id/eprint/92459/ DSC763: Customer Analytics / College of Computing, Informatics and Mathematics UiTM, College of Computing, Informatics and Mathematics Curriculum Universiti Teknologi MARA There is a staggering amount of browsing data and buying patterns that can be found on online shop sites. Extracted customers’ data such as their preferences and navigations can be used to describe their past, present and future behaviours in relation to their purchasing decisions. This course will offer insight understanding into the key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices. By the end of this course, students will understand how data can be used to describe, explain, and predict customer behaviour. Universiti Teknologi MARA (UiTM) 2020 Teaching Resource NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/92459/1/92459.pdf DSC763: Customer Analytics / College of Computing, Informatics and Mathematics. (2020) [Teaching Resource] (Unpublished) https://aims.uitm.edu.my/ |
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Curriculum Universiti Teknologi MARA UiTM, College of Computing, Informatics and Mathematics DSC763: Customer Analytics / College of Computing, Informatics and Mathematics |
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There is a staggering amount of browsing data and buying patterns that can be found on online shop sites. Extracted customers’ data such as their preferences and navigations can be used to describe their past, present and future behaviours in relation to their purchasing decisions. This course will offer insight understanding into the key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices. By the end of this course, students will understand how data can be used to describe, explain, and predict customer behaviour. |
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UiTM, College of Computing, Informatics and Mathematics |
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UiTM, College of Computing, Informatics and Mathematics |
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UiTM, College of Computing, Informatics and Mathematics |
title |
DSC763: Customer Analytics / College of Computing, Informatics and Mathematics |
title_short |
DSC763: Customer Analytics / College of Computing, Informatics and Mathematics |
title_full |
DSC763: Customer Analytics / College of Computing, Informatics and Mathematics |
title_fullStr |
DSC763: Customer Analytics / College of Computing, Informatics and Mathematics |
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DSC763: Customer Analytics / College of Computing, Informatics and Mathematics |
title_sort |
dsc763: customer analytics / college of computing, informatics and mathematics |
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Universiti Teknologi MARA (UiTM) |
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2020 |
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https://ir.uitm.edu.my/id/eprint/92459/1/92459.pdf https://ir.uitm.edu.my/id/eprint/92459/ https://aims.uitm.edu.my/ |
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13.214268 |