Question 1

Infographics and user-friendly graphs and charts are features of the big data analysis technique known as data visualisation.

Accepted Answer

Infographics and user-friendly graphs and charts are commonly used in data visualisation to help users comprehend complex datasets easily.

Question 2

What are the five Vs of big data? Give an example of each and explain why it is important that organisations be able to manage, process and analyse the five Vs of big data.

Accepted Answer

The five Vs of big data are volume, velocity, variety, veracity, and value.

1. Volume: This refers to the sheer amount of data being generated. For example, a social media platform like Facebook generates petabytes of data every day from user posts, photos, and videos.

2. Velocity: This refers to the speed at which data is being generated and needs to be processed. For example, financial trading platforms need to process and analyze market data in real-time to make split-second decisions.

3. Variety: This refers to the different types of data being generated, including structured, unstructured, and semi-structured data. For example, a retail company may need to analyze customer transaction data, social media sentiment, and website clickstream data.

4. Veracity: This refers to the quality and accuracy of the data being generated. For example, sensor data from IoT devices needs to be accurate and reliable for predictive maintenance in manufacturing.

5. Value: This refers to the insights and actionable information that can be derived from the data. For example, a healthcare organization can use big data analytics to identify patterns and trends in patient data to improve treatment outcomes.

It is important for organizations to be able to manage, process, and analyze the five Vs of big data because it allows them to gain valuable insights, make data-driven decisions, and stay competitive in their respective industries. By effectively managing and analyzing large volumes of data at high speeds, organizations can uncover hidden patterns, trends, and correlations that can lead to improved operational efficiency, better customer experiences, and new revenue opportunities. Additionally, ensuring the veracity of the data is crucial for making accurate and reliable decisions. Overall, the ability to harness the five Vs of big data can lead to innovation, improved decision-making, and a competitive advantage in the marketplace.

Question 3

Last week, Doug bought a new tent, sleeping bag and lantern from an online retailer. Today, while using Instagram, he notices that the advertisements are featuring items such as boots, camping stoves and backpacks. Which of the following is influencing the advertisements Doug sees?
A) Recommendation engines
B) Internet of Things (IoT)
C) Chatbots
D) Privacy impact assessments (PIA)

Accepted Answer

Doug's previous purchase history on the online retailer is likely influencing the advertisements he sees on Instagram, as recommendation engines use data and algorithms to suggest products based on a user's previous history and behavior.

Question 4

Amazon's choices of suggested products that it displays to a consumer is based on a recommendation engine.

Accepted Answer

Amazon's recommendation engine uses algorithms and data analysis to suggest products based on a consumer's browsing and purchasing behavior, as well as other factors such as product ratings and reviews.

Question 5

A person's digital footprint refers to
A) artificial intelligence programs that simulate interactive human conversation.
B) the body of data that records an individual's digital interactions.
C) the integration of physical objects and information networks.
D) how valuable data related to a person is to an organisation.

Accepted Answer

A person's digital footprint refers to the data trail they create while interacting in a digital environment, which includes their online activities, posts, comments, and interactions with others. It is a record of a person's digital interactions and can be used to track their online behavior and preferences.

Question 6

While big data analysis provides insights to customer-focused organisations, it has not yet proven to be useful in other areas of society.

Accepted Answer

Big data analysis has been proven to be useful in various areas of society such as healthcare, transportation, and education among others.

Question 7

Which of the following five Vs of big data refers to the diversity of sources, formats and dimensions of data?
A) Volume
B) Variety
C) Value
D) Veracity

Accepted Answer

The five Vs of big data are Volume, Variety, Velocity, Veracity, and Value. Among these, Variety refers to the diversity of sources, formats, and dimensions of data.

Question 8

Arnold is a software developer for a popular social networking company. He is monitoring how many unique posts users generate per minute. Considering the five Vs of big data, which is Arnold most concerned with during this exercise?
A) Value
B) Veracity
C) Variety
D) Velocity

Accepted Answer

Arnold's concern is with the velocity of the data, which refers to the speed at which data is generated and processed. In this case, he is monitoring how many unique posts users generate per minute, which means he needs to keep up with the high velocity of incoming data. The other Vs of big data - value, veracity, and variety - are not as relevant to this particular task.

Question 9

The life cycle of big data is the sequence of stages that a particular unit of data goes through.

Accepted Answer

The statement is true. The life cycle of big data typically includes stages such as data collection, storage, processing, analysis, and utilization.

Question 10

Charlene's job is to propose strategies that her organisation can use to monetise the data they collect. Charlene is concerned with
A) variety.
B) value.
C) velocity.
D) volume.

Accepted Answer

Charlene's concern with monetising the data suggests that she is focused on the value that can be obtained from the data, rather than the other Vs of big data (variety, velocity, and volume).

Question 11

Why is it important that organisations only collect necessary personal information?
A) Collecting personal information is challenging and time-consuming.
B) Over-collection of personal information can increase risks of mishandling that information.
C) Organisations often don't have the resources available to do this type of collection well.
D) Collecting personal information can be expensive.

Accepted Answer

Over-collection of personal information can increase the risks of mishandling that information, which can lead to data breaches, identity theft, and other privacy violations. It is important for organizations to collect only the necessary information to minimize these risks. The other choices are not relevant to the importance of collecting necessary personal information.

Question 12

Which step in the information life cycle is not a risk mitigation strategy?
A) Destroy or de-identify personal information that is no longer needed
B) Collect and hold personal information needed for service and tasks
C) Put into place strategies to protect personal information held
D) Embed privacy protections into personal information handling practices

Accepted Answer

Collecting and holding personal information is not a risk mitigation strategy, but rather a necessary step in the information life cycle. The other options (destroying or de-identifying information, implementing strategies to protect information, and embedding privacy protections) all involve reducing the risk of unauthorized disclosure or misuse of personal information.

Question 13

Artificial intelligence programs that simulate interactive human conversation are known as
A) real-time big data.
B) digital footprints.
C) the Internet of Things (IoT).
D) chatbots.

Accepted Answer

Artificial intelligence programs that simulate interactive human conversation are known as chatbots.

Question 14

Choose two sectors-health care, retail, wholesale trade, and so on-and explain how the application of big data is contributing to each sector.

Accepted Answer

The answer of Choose two sectors-health care, retail, wholesale trade,...

Question 15

Big data analytics allow global financial markets to track current numbers and trends.

Accepted Answer

Big data analytics provide a comprehensive view of current and historical trends in financial markets.

Question 16

The difference between tacit knowledge and explicit knowledge is
A) the first is carried in the mind and is difficult to access while the second has been expressed and can be stored and passed on.
B) the first is common to everyone while the second is not.
C) the first is theory while the second is technical.
D) the first is literary while the second is not.

Accepted Answer

Tacit knowledge refers to knowledge that is held in someone's mind and is difficult to access or articulate, while explicit knowledge is knowledge that has been expressed and can be easily recorded and shared with others.

Question 17

Which of the following techniques for analysing big data enables the access, examination and integration of large amounts of historical data from multiple data sources?
A) Data visualisation
B) Predictive analytics
C) Data mining
D) In-memory analytics

Accepted Answer

Data mining is a technique for analysing big data that involves accessing, examining, and integrating large amounts of historical data from multiple sources. It is used to identify patterns, relationships, and trends within the data that can be used to make better business decisions. Data visualization is a technique for presenting the data in a graphical format to make it easier to understand. Predictive analytics is a technique for using data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. In-memory analytics is a technique for processing the data in-memory, which enables faster analysis of large amounts of data.

Question 18

What is the key to the sharing of tacit and explicit knowledge within and between organisations?
A) Knowledge services
B) Knowledge-management programs
C) Effective communication
D) Social networks

Accepted Answer

Effective communication is essential for sharing both tacit and explicit knowledge within and between organizations. It involves creating a culture of open communication, encouraging knowledge sharing, providing opportunities for employees to collaborate, and establishing clear channels for sharing knowledge. Knowledge services, knowledge-management programs, and social networks can support effective communication, but they are not the key to sharing knowledge.

Question 19

The purpose of data visualisation is to access, examine and integrate large amounts of historical data from multiple data sources.

Accepted Answer

The primary purpose of data visualization is to communicate information clearly and efficiently via graphical means, making complex data more accessible, understandable, and usable, not specifically to access, examine, and integrate historical data from multiple sources.

Question 20

A successful organisation achieves its business goals with a knowledge-management process by
A) using web-based and digital technology only.
B) exploring the potential of its staff.
C) changing how people work and earn an income.
D) aligning its big data activities and knowledge-management strategies with business objectives and people management.

Accepted Answer

Aligning big data activities and knowledge-management strategies with business objectives and people management ensures that the organisation uses its resources in a strategic manner to achieve its business goals. Using only web-based and digital technology may not be enough, exploring the potential of staff is important but not sufficient, and changing how people work and earn an income may not relate directly to knowledge management.

Quiz 12: Managing Big Data and Knowledge

Infographics and user-friendly graphs and charts are features of the big data analysis technique known as data visualisation.

What are the five Vs of big data? Give an example of each and explain why it is important that organisations be able to manage, process and analyse the five Vs of big data.

Last week, Doug bought a new tent, sleeping bag and lantern from an online retailer. Today, while using Instagram, he notices that the advertisements are featuring items such as boots, camping stoves and backpacks. Which of the following is influencing the advertisements Doug sees?

Amazon's choices of suggested products that it displays to a consumer is based on a recommendation engine.

A person's digital footprint refers to

While big data analysis provides insights to customer-focused organisations, it has not yet proven to be useful in other areas of society.

Which of the following five Vs of big data refers to the diversity of sources, formats and dimensions of data?

Arnold is a software developer for a popular social networking company. He is monitoring how many unique posts users generate per minute. Considering the five Vs of big data, which is Arnold most concerned with during this exercise?

The life cycle of big data is the sequence of stages that a particular unit of data goes through.

Charlene's job is to propose strategies that her organisation can use to monetise the data they collect. Charlene is concerned with

Why is it important that organisations only collect necessary personal information?

Which step in the information life cycle is not a risk mitigation strategy?

Artificial intelligence programs that simulate interactive human conversation are known as

Choose two sectors-health care, retail, wholesale trade, and so on-and explain how the application of big data is contributing to each sector.

Big data analytics allow global financial markets to track current numbers and trends.

The difference between tacit knowledge and explicit knowledge is

Which of the following techniques for analysing big data enables the access, examination and integration of large amounts of historical data from multiple data sources?

What is the key to the sharing of tacit and explicit knowledge within and between organisations?

The purpose of data visualisation is to access, examine and integrate large amounts of historical data from multiple data sources.

A successful organisation achieves its business goals with a knowledge-management process by