Recent Lessons

Show all results for ""

Feature Overview

Ace your exams with our all-in-one platform for creating and sharing quizzes and tests.

Quizzes

Create quizzes and tests automatically from your content using AI.

Flashcards

Automatically turn your notes into digital flashcards.

Share, Export & Embed

Share with classmates or export to Excel and your learning management system.

Stats & Reporting

Auto-grading quizzes and tests with detailed stats and reports.

Mobile Apps

The smarter way to study – wherever you are.

Pricing

Search...

15 Questions

0 Views

COMP5122M Business Understanding Quiz

Choose a study mode

Play Quiz

Study Flashcards

Spaced Repetition

Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is the CRISP data mining process?

A method for data understanding

A framework for thinking about business problems

A standard process for data mining (correct)

A simple approach to understanding business problems

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

To simplify business problems

To complicate business problems

To understand business problems more deeply (correct)

To speed up the decision-making process

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

To reduce the overall project cost

To manage client expectations (correct)

To avoid taking on complex projects

To complete the project faster

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

Thinking about the problem to be solved and the use scenario Signup and view all the answers

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

Assessing the strengths and limitations of historical data Signup and view all the answers

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

Minerva Learning Resources Signup and view all the answers

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?

To have a deep understanding of the stakeholder's business and terminology Signup and view all the answers

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

Investing in acquiring necessary data and modeling Signup and view all the answers

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

It spun off credit card operations into Capital One Signup and view all the answers

What was the aim of QuantiCode from 2016-2020?

To develop novel data mining and visualization tools and techniques Signup and view all the answers

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?

Preferably have face-to-face discussions, especially the first time Signup and view all the answers

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

Data quality Signup and view all the answers

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

'Engineering' a solution to business problems Signup and view all the answers

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

'Modelling' Signup and view all the answers

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

'Link prediction' Signup and view all the answers