Deck 16: Data and Analytics

Question 1

What are the advantages of structured query language (SQL)?

A) Obtain and analyse data.
B) Obtain and categorize data.
C) Obtain and list data.
D) Obtain and clean data.

Answer 1

Obtain and clean data.

Question 2

What is big data?

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.

Answer 2

Data that has limitations because of its size.

Question 3

What were the initial criteria for big data?

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

Answer 3

Volume, variety and velocity.

Question 4

Describe IoT.

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 5

What is scanner data?

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 6

When were scanners first used in the supermarkets?

A) 1984.
B) 1974.
C) 1976.
D) 1986.

Question 7

What is dark data?

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 8

How is unstructured data represented?

A) Only as numeric data.
B) Only as text data.
C) As both numeric and text data.
D) Only as analysed data.

Question 9

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 _______.

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

Question 10

What is the purpose of data analytics?

A) To create models.
B) To produce huge amounts of information.
C) To convert data into meaningful information.
D) To create expert knowledge.

Question 11

What is the limitation of spreadsheets?

A) Spreadsheets cannot be used to prepare basic reports.
B) Spreadsheets are inefficient when handling large datasets.
C) Spreadsheets cannot process data and apply statistical tools.
D) Spreadsheets cannot prepare datasets.

Question 12

What is the chief role of Chief Data Officer?

A) To handle and govern the company's data.
B) To share the company's data with others.
C) To collect data.
D) To analyse the data.

Question 13

How does data analytics help business?

A) By helping to share information.
B) By helping to collect data.
C) By helping to govern the data.
D) By helping to measure marketing activities.

Question 14

What tools have helped marketing analytics be incorporated in decision making?

A) Cross-tabulated data.
B) Metric calculation.
C) CRM tools.
D) CRM tools and ERP software.

Question 15

What is CRM?

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 16

What purpose does Customer Lifetime Value serve?

A) To predict customer's future sales.
B) To analyse the role of business in increasing the number of customers.
C) To calculate the value of sales to customers.
D) To forecast business trends.

Question 17

Why are cognitive biases important 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 18

Tom has seen quite a few Instagram posts about a new gym clothing company and read some reviews about the brand. Based on what he has seen on social media he decides to purchase via the brand's website and also uses the opportunity to read more about the brand and how the clothing is made. The brand decide to do some analysis to determine if Instagram is instrumental in consumer decision making, via a technique known as_______.

A) Customer value.
B) Attribution modelling.
C) Social listening.
D) Data visualisation.

Question 19

How is data obtained from the web?

A) Website, web-based APIs and PDFs.
B) Twitter and Facebook.
C) Website and social media sites.
D) Tools and tutorials.

Question 20

What data can be produced from mobile phones that are valuable for marketers?

A) Mobile network.
B) Network potential.
C) Travel history.
D) Customer impression.

Question 21

Name one important secondary research group.

A) Focus groups.
B) Social media groups.
C) Exploratory research groups.
D) Mobile groups.

Question 22

Data science is an amalgamation of which skills?

A) Statistics, programming and business skills.
B) Statistics, IT and algorithms.
C) Statistics, SQL and customer knowledge.
D) Statistics, marketing and IT.

Question 23

What is data munging or data wrangling?

A) Data categorization
B) Data preparation.
C) Data analysis.
D) Data mining.

Question 24

What are the essential computing resources?

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

Question 25

Name an advanced programming language.

A) R/R Studio.
B) Python.
C) WinBugs.
D) IBN Hana.

Question 26

Name the three types of marketing analytics.

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

Question 27

What is customer churn?

A) A customer buys a product in excess.
B) A customer invites more customers to buy a product.
C) A customer stops buying a product.
D) A customer buys a product for future use.

Question 28

What is CSAT?

A) Customer service attainment technique.
B) Customer statistics.
C) Customer satisfaction.
D) Customer satisfaction parameter.

Question 29

Name the analytical technique used to recommend products to customers.

A) Basket analysis.
B) Market basket analysis.
C) Associate basket analysis.
D) Data basket analysis.

Question 30

Optus has recently changed the colour of an advertisement in their App which links customers to the website to provide special discount offers. As Optus measures the click through rate, this is an example of___________.

A) A/B testing.
B) Market basket analysis.
C) Python.
D) HR analysis.

Question 31

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

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

Question 32

What are internal analytics used for?

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

Question 33

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

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 34

Name one type of software used to spot visual patterns.

A) Spotify.
B) Tablend.
C) Spoton.
D) Tableau.

Question 35

What does data mining do?

A) Look for futuristic patterns in data.
B) Look for patterns in data.
C) Look for futuristic information.
D) Look for additional data.

Question 36

Deep learning helps to solve problems related to which fields?

A) Natural learning processing, computer vision and information technology.
B) Computer vision, information technology and bioinformatics.
C) Natural learning processing, computer vision and bioinformatics.
D) Natural learning processing, information technology and machine learning.

Question 37

How is textual information categorised?

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

Question 38

What is data that is presented in rows and columns called?

A) Unstructured data.
B) Excel spreadsheet.
C) Structured or relational data.
D) Opinionated data.

Question 39

What is data snooping?

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 40

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

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

Question 41

How do Just-In-Time (JIT) opportunities help retailers?

A) Reduce waste and increase profits.
B) Reduce cost and increase profits.
C) Reduce waiting time and increase profits.
D) Reduce buying time and increase profits.

Question 42

Why is quantum computing an area of interest for the future of data and analytics?

A) Faster computers.
B) Assist in large scale data.
C) Quicker decision making.
D) Option a and b.

Question 43

What type of data is most produced?

A) Social data and structured data.
B) Personal data and structured data.
C) Social data and unstructured data.
D) Personal data and unstructured data.

Question 44

What are the key skills needed by a quantitative analyst?

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.

Question 45

How can data snooping be avoided?

A) By making sure that the model is reproducible.
B) By following ethical guidelines.
C) By governing data.
D) By confirmation of data.

Question 46

What is the main legal and ethical issue in data analytics?

A) Selling of data.
B) Identity theft.
C) Confirmation bias.
D) Purchase history.

Question 47

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

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

Question 48

What is the future of analytics?

A) JIT opportunities.
B) Right data at the right time.
C) Technology integration.
D) API in cloud and open-source software.

Question 49

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

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

Question 50

Why is data governance and stewardship important?

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.