COMP5122M Business Understanding Quiz

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15 Questions

What is the CRISP data mining process?

What is the purpose of 'decision analytic thinking' in data science?

Why is it important to appreciate the long time required in data science?

What is included in the 'business understanding' phase of the CRISP data mining process?

What is the main emphasis of 'data understanding' in the CRISP data mining process?

Where can students find additional material for private study related to this lecture?

In data science, when a stakeholder has a vague idea of the problem and no idea how to tackle it, what is expected from a successful data scientist?

What was the strategy adopted by Signet Bank in the 1990s to improve profitability?

What did Signet Bank achieve as a result of its strategy in the 1990s?

What was the aim of QuantiCode from 2016-2020?

What is considered a successful method for solving a problem in data science when dealing with stakeholders who have a vague idea of the problem?

What kind of data preparation task involves converting & transforming data, data linkage, and addressing data leaks?

'Decision analytic thinking' in data science is primarily focused on:

'Unsupervised & supervised tasks' are associated with which aspect of data science?

'Clustering' and 'Co-occurrence grouping' are examples of tasks related to:


Test your knowledge on the business understanding aspects of data science based on the lecture and book 'Data Science for Business' by Foster Provost and Tom Fawcett. Content may include chapters 1, 2, and 11, as well as Appendix A.

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