Question 1

According to LinkedIn, what are the two top skills required by a data scientist?

Accepted Answer

A)  Python and data analysis. 
B)  Analytical thinking and statistical analysis. 
C)  Statistical analysis and data collection. 
D)  Statistical analysis and error identification. 
A)  Python and data analysis. 
B)  Analytical thinking and statistical analysis. 
C)  Statistical analysis and data collection. 
D)  Statistical analysis and error identification.

Question 2

What is data snooping?

Accepted Answer

A)  When an analyst used personal data. 
B)  When an analyst uses a model to confirm what they want to prove. 
C)  When an analyst uses data without the knowledge of customer. 
D)  When an analyst uses unethical data. 
A)  When an analyst used personal data. 
B)  When an analyst uses a model to confirm what they want to prove. 
C)  When an analyst uses data without the knowledge of customer. 
D)  When an analyst uses unethical data.

Question 3

Name the three types of marketing analytics.

Accepted Answer

A)  Predictive, descriptive and addictive. 
B)  Predictive, addictive and prescriptive. 
C)  Predictive, prescriptive and vindictive. 
D)  Predictive, descriptive and prescriptive. 
A)  Predictive, descriptive and addictive. 
B)  Predictive, addictive and prescriptive. 
C)  Predictive, prescriptive and vindictive. 
D)  Predictive, descriptive and prescriptive.

Question 4

How is textual information categorised?

Accepted Answer

A)  Facts and information. 
B)  Information and news. 
C)  Facts and source data. 
D)  Facts and opinions. 
A)  Facts and information. 
B)  Information and news. 
C)  Facts and source data. 
D)  Facts and opinions.

Question 5

What are internal analytics used for?

Accepted Answer

A)  Employee performance and productivity. 
B)  Internal HR data. 
C)  Sales data. 
D)  Customer demand. 
A)  Employee performance and productivity. 
B)  Internal HR data. 
C)  Sales data. 
D)  Customer demand.

Question 6

Ben and Jerry's did some analysis of their consumers and found a strong correlation between an increase in ice-cream consumption and times when there was a full moon. These variables logically do not seem related. This is an example of _______.

Accepted Answer

A)  Noisy data. 
B)  Marketing insights. 
C)  Social data. 
D)  Spurious correlation. 
A)  Noisy data. 
B)  Marketing insights. 
C)  Social data. 
D)  Spurious correlation.

Question 7

What is CRM?

Accepted Answer

A)  A tool to collect customer data. 
B)  A tool to manage customer data. 
C)  A tool to provide information to customer. 
D)  A tool to interact with customer. 
A)  A tool to collect customer data. 
B)  A tool to manage customer data. 
C)  A tool to provide information to customer. 
D)  A tool to interact with customer.

Question 8

Describe IoT.

Accepted Answer

A)  Collection of data by all products and services for everyday operation. 
B)  Collection of data by all products and services for storage. 
C)  Collection of data by all products and services for information. 
D)  Collection of data by all products and services for users. 
A)  Collection of data by all products and services for everyday operation. 
B)  Collection of data by all products and services for storage. 
C)  Collection of data by all products and services for information. 
D)  Collection of data by all products and services for users.

Question 9

What is big data?

Accepted Answer

A)  Data that has negative connotation. 
B)  Data that has not lived up to its promised potential. 
C)  Data that is not useful. 
D)  Data that has limitations because of its size. 
A)  Data that has negative connotation. 
B)  Data that has not lived up to its promised potential. 
C)  Data that is not useful. 
D)  Data that has limitations because of its size.

Question 10

When consumer information is intentionally or unintentionally released, this is called a____.

Accepted Answer

A)  security breach. 
B)  data snooping. 
C)  data breach. 
D)  cybercrime. 
A)  security breach. 
B)  data snooping. 
C)  data breach. 
D)  cybercrime.

Question 11

What were the initial criteria for big data?

Accepted Answer

A)  Volume, variety and vagary. 
B)  Volume, vagary and value. 
C)  Volume, variety and velocity. 
D)  Volume, value and velocity. 
A)  Volume, variety and vagary. 
B)  Volume, vagary and value. 
C)  Volume, variety and velocity. 
D)  Volume, value and velocity.

Question 12

Why are cognitive biases important in data analytics?

Accepted Answer

A)  Because such biases must be dismissed as an error. 
B)  Because they help to determine pricing. 
C)  Because understanding of irrelevant judgement helps to avoid errors. 
D)  Because it should be avoided in data analytics. 
A)  Because such biases must be dismissed as an error. 
B)  Because they help to determine pricing. 
C)  Because understanding of irrelevant judgement helps to avoid errors. 
D)  Because it should be avoided in data analytics.

Question 13

What is scanner data?

Accepted Answer

A)  Data scanned from various resources. 
B)  Detailed data on marketing. 
C)  Data on predictions of consumer choice. 
D)  Detailed data on sales of consumer goods. 
A)  Data scanned from various resources. 
B)  Detailed data on marketing. 
C)  Data on predictions of consumer choice. 
D)  Detailed data on sales of consumer goods.

Question 14

Why is data governance and stewardship important?

Accepted Answer

A)  To avoid misuse of data. 
B)  To avoid data snooping. 
C)  Because data is an asset and should not be misused. 
D)  To prevent disclosures. 
A)  To avoid misuse of data. 
B)  To avoid data snooping. 
C)  Because data is an asset and should not be misused. 
D)  To prevent disclosures.

Question 15

What is dark data?

Accepted Answer

A)  Data that is highly classified. 
B)  Data that is unstructured. 
C)  Data that is irrelevant. 
D)  Data that is never analysed but stored. 
A)  Data that is highly classified. 
B)  Data that is unstructured. 
C)  Data that is irrelevant. 
D)  Data that is never analysed but stored.

Question 16

How do we prevent an over-fit of a model?

Accepted Answer

A)  By using simple data for validation. 
B)  By using complex data for validation. 
C)  By using test data for validation. 
D)  By using traditional data for validation. 
A)  By using simple data for validation. 
B)  By using complex data for validation. 
C)  By using test data for validation. 
D)  By using traditional data for validation.

Question 17

What are the essential computing resources?

Accepted Answer

A)  Efficient IT systems. 
B)  Efficient employees. 
C)  Spreadsheets. 
D)  Hardware for storage and distribution of data and software to analyse it. 
A)  Efficient IT systems. 
B)  Efficient employees. 
C)  Spreadsheets. 
D)  Hardware for storage and distribution of data and software to analyse it.

Question 18

Why is the competitive advantage of data analytics on the decline?

Accepted Answer

A)  Lack of planning perspective. 
B)  Inadequate statistical applications. 
C)  Most businesses are running similar statistical techniques. 
D)  Unable to retrieve relevant data. 
A)  Lack of planning perspective. 
B)  Inadequate statistical applications. 
C)  Most businesses are running similar statistical techniques. 
D)  Unable to retrieve relevant data.

Question 19

Up to how many differences are allowed between versions A and B in A/B testing?

Accepted Answer

A)  12. 
B)  4. 
C)  1. 
D)  3. 
A)  12. 
B)  4. 
C)  1. 
D)  3.

Question 20

What are the key skills needed by a quantitative analyst?

Accepted Answer

A)  Data literacy, statistical reasoning and data mining. 
B)  Data mining, statistical reasoning and technology integration. 
C)  Numeracy, statistical reasoning and technology integration. 
D)  Data literacy, statistical reasoning and numeracy. 
A)  Data literacy, statistical reasoning and data mining. 
B)  Data mining, statistical reasoning and technology integration. 
C)  Numeracy, statistical reasoning and technology integration. 
D)  Data literacy, statistical reasoning and numeracy.

According to LinkedIn, what are the two top skills required by a data scientist?

What is data snooping?

Name the three types of marketing analytics.

How is textual information categorised?

What are internal analytics used for?

Ben and Jerry's did some analysis of their consumers and found a strong correlation between an increase in ice-cream consumption and times when there was a full moon. These variables logically do not seem related. This is an example of _______.

What is CRM?

Describe IoT.

What is big data?

When consumer information is intentionally or unintentionally released, this is called a____.

What were the initial criteria for big data?

Why are cognitive biases important in data analytics?

What is scanner data?

Why is data governance and stewardship important?

What is dark data?

How do we prevent an over-fit of a model?

What are the essential computing resources?

Why is the competitive advantage of data analytics on the decline?

Up to how many differences are allowed between versions A and B in A/B testing?

What are the key skills needed by a quantitative analyst?

Introduction to Marketing

The Marketing Environment and Market Analysis

Market Research

Consumer Behaviour

Business Buying Behaviour

Markets: Segmentation, Targeting and Positioning

Product

Price

Promotion

Distribution Place

Services Marketing

Digital Marketing

International Marketing

Social Marketing and Not-For-Profit Marketing

Marketing Planning, Implementation and Evaluation

Filters

Exam 16: Data and Analytics

According to LinkedIn, what are the two top skills required by a data scientist?

What is data snooping?

Name the three types of marketing analytics.

How is textual information categorised?

What are internal analytics used for?

Ben and Jerry's did some analysis of their consumers and found a strong correlation between an increase in ice-cream consumption and times when there was a full moon. These variables logically do not seem related. This is an example of _______.

What is CRM?

Describe IoT.

What is big data?

When consumer information is intentionally or unintentionally released, this is called a____.

What were the initial criteria for big data?

Why are cognitive biases important in data analytics?

What is scanner data?

Why is data governance and stewardship important?

What is dark data?

How do we prevent an over-fit of a model?

What are the essential computing resources?

Why is the competitive advantage of data analytics on the decline?

Up to how many differences are allowed between versions A and B in A/B testing?

What are the key skills needed by a quantitative analyst?

Introduction to Marketing

The Marketing Environment and Market Analysis

Market Research

Consumer Behaviour

Business Buying Behaviour

Markets: Segmentation, Targeting and Positioning

Product

Price

Promotion

Distribution Place

Services Marketing

Digital Marketing

International Marketing

Social Marketing and Not-For-Profit Marketing

Marketing Planning, Implementation and Evaluation

Filters