Quiz #10

*Veracity, Variability*, *Value*, and *Visualization* of data are terms applicable exclusively to Big Data.

FALSE

Fully developed data warehouse or a pure data lake are *the only two choices* for large analytical data repositories.

FALSE

Unstructured and semi-structured data can become a *source of data for a data warehouse* after being processed by Hadoop.

TRUE

The *same data* in the data lake can be transformed and analyzed by multiple groups of users in different ways for a variety of different purposes.

True

Big data techniques *increase* the ability to analyze the data that the organization owns or to which it has access.

True

Collection of alphanumeric comma-separated data showing temperatures for each second of the day for a set of 10,000 commercial smart-refrigerators is an *example of big data*.

True

Big data methods, such as MapReduce, *replace* database and data warehousing approaches developed for managing and utilizing formally modeled data assets.

FALSE

Big data sets, when *compared* with most databases and data warehouses:

Have higher possibility of different interpretations

A corporation engaged in data analysis can create and maintain *both* data warehouses and data lakes at the same time.

True

CONSTANT DOCUMENTARIAN is an organization that receives each day a one-hour log video from 50 contributors around the world, recording mundane daily-life scenes.  It also receives one daily 200-words email from its contributors.  Consider the following CONSTANT DOCUMENTARIAN data sets: \n - Set A: collection of daily one-hour videos from the 50 contributors \n - Set B: collection of daily 200-words emails from its contributors \n - Set C: video footage of its 24/7 CCTV camera constantly recording scenes outside its headquarters \n - Set D: relational table containing first name, last name, phone number, and email address of each contributor \n   \n Which data set is exhibiting the lowest *volume*?

Set D

*Volume, Variety,* and *Velocity* of data are terms applicable exclusively to big data.

FALSE

CONSTANT DOCUMENTARIAN is an organization that receives each day a one-hour log video from 50 contributors around the world, recording mundane daily-life scenes.  It also receives one daily 200-words email from its contributors.  Consider the following CONSTANT DOCUMENTARIAN data sets: \\n - Set A: collection of daily one-hour videos from the 50 contributors \\n - Set B: collection of daily 200-words emails from its contributors - Set C: video footage of its 24/7 CCTV camera constantly recording scenes outside its headquarters \\n - Set D: relational table containing first name, last name, phone number, and email address of each contributor \\n   Which data set is exhibiting the lowest *velocity*?

Set D

Which of the following is *NOT* true?

The programmer using Hadoop has to write the functions for distributing the data among nodes.

Where on the Spectrum of Solutions for Large Analytical Data Repositories, would the following example best fit?

*Data from 10 data sources is extracted.  Two of those sources have the exact same structure, so the data from those two sources is pasted together before loading. There is a small overlap of data in those two sources, so the duplicates are eliminated before loading. The rest of the sources are loaded as they were.*

Inside the spectrum, closer to the left edge of the spectrum (Pure Data Lake).

*SQL* provides all the necessary functionalities for managing and analyzing big data.

FALSE

CONSTANT DOCUMENTARIAN is an organization that receives each day a one-hour log video from 50 contributors around the world, recording mundane daily-life scenes.  It also receives one daily 200-words email from its contributors.  Consider the following CONSTANT DOCUMENTARIAN data sets: \n - Set A: collection of daily one-hour videos from the 50 contributors \n - Set B: collection of daily 200-words emails from its contributors \n - Set C: video footage of its 24/7 CCTV camera constantly recording scenes outside its headquarters \n - Set D: relational table containing first name, last name, phone number, and email address of each contributor \n   \n Which data set is exhibiting the highest *velocity*?

Set C

Which of the following data examples has the most *structure*?

A row in a relational table

Which of the following is applicable to a *data lake*?

Potentially analytically useful data is extracted from sources and then placed in the data lake.

CONSTANT DOCUMENTARIAN is an organization that receives each day a one-hour log video from 50 contributors around the world, recording mundane daily-life scenes.  It also receives one daily 200-words email from its contributors.  Consider the following CONSTANT DOCUMENTARIAN data sets: \n - Set A: collection of daily one-hour videos from the 50 contributors \n - Set B: collection of daily 200-words emails from its contributors \n - Set C: video footage of its 24/7 CCTV camera constantly recording scenes outside its headquarters \n - Set D: relational table containing first name, last name, phone number, and email address of each contributor \n   \n  Which data set is exhibiting the highest *volume*?

Set A

A large fact table in a data warehouse is an *example of big data*.

FALSE

CONSTANT DOCUMENTARIAN is an organization that receives each day a one-hour log video from 50 contributors around the world, recording mundane daily-life scenes.  It also receives one daily 200-words email from its contributors.  Consider the following CONSTANT DOCUMENTARIAN data sets: \n - Set A: collection of daily one-hour videos from the 50 contributors \n - Set B: collection of daily 200-words emails from its contributors \n - Set C: video footage of its 24/7 CCTV camera constantly recording scenes outside its headquarters \n - Set D: relational table containing first name, last name, phone number, and email address of each contributor \n   \n Which data set has the most *structure*?

Set D

Which of the following (regarding the telemetry data set in the Insurance Company Example) is *NOT* true?

Telemetry data could be used as a source for adding data about the range of prices of new vehicles to the warehouse.