D467 - Exploring Data

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Free D467 - Exploring Data Questions

1.

What are data ethics?

  • Established methods for ensuring data is clean, well-organized, and appropriate for a project

  • Long-standing techniques for confirming that data is always used to benefit society

  • Approved strategies data professionals use to safeguard the privacy and security of a dataset

  • Well-founded standards of right and wrong that dictate how data is collected, shared, and used

Explanation

Explanation:

Data ethics refers to the moral principles that guide how data is collected, shared, and used. It is about ensuring that data practices respect privacy, maintain fairness, and avoid harm. Ethical data handling involves considering the impact of data-related decisions on individuals and society, going beyond mere technical standards or security measures. These standards of right and wrong provide a framework for responsible data management and usage.

Correct Answer:

Well-founded standards of right and wrong that dictate how data is collected, shared, and used

Why Other Options Are Wrong:

Established methods for ensuring data is clean, well-organized, and appropriate for a project

This describes data cleaning or preparation, which is a technical process to improve data quality. It is not the same as ethical considerations regarding how data should be handled or the moral implications of its use.

Long-standing techniques for confirming that data is always used to benefit society

While ethical data use often aims to benefit society, data ethics is broader and more nuanced. It involves principles like consent, transparency, and privacy, not just techniques to guarantee societal benefit.

Approved strategies data professionals use to safeguard the privacy and security of a dataset

Safeguarding privacy and security is one aspect of ethical data practices, but data ethics also covers fairness, accountability, and responsible sharing. It cannot be reduced to only privacy and security strategies.


2.

A data type is a specific kind of data _____ that tells what kind of value the data is.

  • attribute

  • frame

  • model

  • point

Explanation

Explanation:

A data type is a specific kind of data attribute that defines the nature of the data stored in a field or variable, such as whether it is an integer, floating-point number, text, or date. Attributes describe the properties or characteristics of data elements, and the data type sets the rules for what values are valid and how those values can be processed. By specifying an attribute, databases and programming languages know how to store, interpret, and validate the data properly.

Correct Answer:

attribute

Why Other Options Are Wrong:

frame

A frame refers to a structure used to hold or display data, such as a data frame in programming or a visual frame in multimedia, but it does not define the type or nature of a specific value. While data frames can contain multiple data types, the frame itself is not the classification that tells the system whether a value is numeric, text, or another type. It serves as a container rather than a descriptor of value characteristics. Therefore, it cannot represent what a data type is intended to describe.

model

A model represents a conceptual or mathematical framework that describes how data behaves or how relationships among data elements work, such as a predictive model or a database schema. Although models may incorporate various data types within their structure, they do not specify the nature of individual data values like integers or strings. Instead, a model uses data types as building blocks to function, so it is a higher-level concept rather than the actual classification of a value. Consequently, a model is not the correct completion of the statement.

point

A point usually describes a specific location or a singular item in a dataset, such as a point on a graph or a data point in statistics. It refers to an instance of data rather than the definition of what kind of value the data represents. While a data point might contain a value that adheres to a certain data type, the term itself does not describe the rules or properties of that value. Thus, “point” fails to capture the essence of what a data type provides.


3.

In data analytics, what is the term for data that is generated from, and lives, outside of an organization?

  • Peripheral

  • Outer

  • Internal

  • External

Explanation

Explanation:

Data that originates and resides outside an organization is known as external data. This type of data comes from sources such as market research firms, government databases, social media platforms, or public records. It provides insights that are not captured by the organization’s internal systems and can be valuable for competitive analysis, market trends, and decision-making.

Correct Answer:

External

Why Other Options Are Wrong:

Peripheral

Peripheral is not a standard data classification term in analytics. It typically refers to devices connected to a computer rather than a source of data.

Outer

Outer does not describe a recognized data category in analytics and is not used to distinguish data sources.

Internal

Internal data is generated within the organization, such as sales transactions or employee records, which is the opposite of the question’s description.


4.

What are the key characteristics of unstructured data? Select all that apply.

  • Fits neatly into rows and columns

  • Unorganized

  • May have an internal structure

  • Clearly identifiable construction

Explanation

Explanation:

Unstructured data refers to information that does not conform to a fixed schema or easily fit into traditional relational databases. It is typically unorganized and may contain internal patterns or structures, such as metadata or natural language patterns, but lacks a predefined data model. Examples include emails, videos, social media posts, and images.

Correct Answer:

Unorganized

May have an internal structure


Why Other Options Are Wrong:

Fits neatly into rows and columns

This describes structured data, which is organized into predefined tables and fields, unlike unstructured data.

Clearly identifiable construction

Unstructured data lacks a clearly defined construction or schema, which makes it challenging to store and analyze using traditional relational databases.


5.

For data analytics projects, _____ data is typically preferred because users know it originated within the organization.

  • second-party

  • third-party

  • multi-party

  • first-party

Explanation

Explanation:

First-party data is collected directly by an organization from its own customers, website visitors, or users. Because it is gathered at the source, it is considered the most reliable, accurate, and privacy-compliant for analytics and decision-making. Organizations have direct control over how the data is collected and used, which enhances trust and data quality for analytics projects.

Correct Answer:

first-party

Why Other Options Are Wrong:

second-party

Second-party data refers to another organization’s first-party data shared through a partnership. While it can be valuable, it does not offer the same direct control and certainty about data quality as first-party data.

third-party

Third-party data is aggregated from external sources with no direct relationship to the users. It often has issues with accuracy, relevance, and privacy compliance, making it less ideal for precise analytics.

multi-party

Multi-party is not a standard classification of data in analytics. It is not recognized as a specific data origin category, so it does not fit the requirement for trusted, organization-sourced data.


6.

What type of data is the height of a skyscraper?

  • Discrete

  • Qualitative

  • Nominal

  • Continuous

Explanation

Explanation:

The height of a skyscraper is a measurable quantity that can include decimals and can take on any value within a realistic range. This makes it continuous data, as it represents a continuous scale of measurement. It is a numerical, quantitative measure that allows for precise comparison and mathematical operations.

Correct Answer:

Continuous

Why Other Options Are Wrong:

Discrete

Discrete data consists of countable values, such as the number of windows on a building, not measurements that can vary infinitely like height.

Qualitative

Qualitative data describes qualities or characteristics that are not numeric, such as color or design style, which does not apply to height measurements.

Nominal

Nominal data categorizes without order or numeric meaning. Height is a numeric measurement with magnitude, making it unsuitable for a nominal classification.


7.

What are cookies?

  • Types of malware that can damage computers

  • Small files stored on computers that contain information about users

  • Programs that enable users to access websites

  • Pieces of code that store information about a website

Explanation

Explanation:

Cookies are small text files placed on a user’s computer by a website to store information such as user preferences, login details, or browsing activity. They allow websites to remember users between visits, making web experiences more personalized and efficient. Unlike malware or executable programs, cookies are passive data files and do not harm the computer or run as software.

Correct Answer:

Small files stored on computers that contain information about users

Why Other Options Are Wrong:

Types of malware that can damage computers

Cookies are not malicious programs; they cannot self-replicate, damage files, or compromise system integrity like viruses or other malware. Their purpose is to store user data to enhance website functionality, not to harm the computer.

Programs that enable users to access websites

Cookies are not web browsers or applications. They do not provide access to websites but instead are stored by browsers to maintain information between site visits.

Pieces of code that store information about a website

Cookies do not store the website’s code or structure. They store user-related information, such as login states or preferences, and are separate from the website’s internal codebase.


8.

In a data table, where are fields contained?

  • Rows

  • Columns

  • Favorites

  • Charts

Explanation

Explanation:

In a structured data table, fields are contained in columns. Each column represents a specific attribute or property of the data, such as “Name,” “Date of Birth,” or “Order Total.” These columns define the type of information stored for each record, ensuring consistency and organization. Fields remain the same for every row, while the individual rows contain unique records with values for each field.

Correct Answer:

Columns

Why Other Options Are Wrong:

Rows

Rows represent individual records, not fields. Each row provides a single entry or instance in the table, containing values that correspond to the fields defined by the columns. While rows store the actual data values, they do not define the categories or attributes of that data. Therefore, rows are the records themselves, not the containers of fields.

Favorites

Favorites is not a database term related to the structure of a data table. It typically refers to bookmarked or preferred items in applications or web browsers, which has no connection to how fields are organized. Because it lacks any relationship to tabular data storage, it cannot describe where fields are contained.

Charts

Charts are graphical representations of data used for visualization, not for data storage or organization within a table. While charts may display data from specific fields, they do not hold or define those fields. They are a separate tool for analysis and presentation rather than the underlying structure of the database itself.


9.

What are the key aspects of universal participation? Select all that apply.

  • Certain groups of people must share their private data.

  • No one can place restrictions on data to discriminate against a person or group.

  • Everyone must be able to use, reuse, and redistribute open data.

  • All corporations are allowed to sell open data.

Explanation

Explanation:

Universal participation is a fundamental principle of open data that ensures equitable access and freedom of use for everyone. It means that no restrictions can be placed on the data to prevent certain people or groups from accessing or using it. It also guarantees that anyone can use, reuse, and redistribute open data without discrimination. This principle promotes inclusivity and prevents any single organization or individual from monopolizing access or imposing unfair barriers.

Correct Answer:

No one can place restrictions on data to discriminate against a person or group.

Everyone must be able to use, reuse, and redistribute open data.


Why Other Options Are Wrong:

Certain groups of people must share their private data.

Universal participation does not require anyone to share private or personal data. The principle applies to open data that is intentionally made public and does not compel individuals or groups to sacrifice their privacy.

All corporations are allowed to sell open data.

While corporations may use open data, universal participation is about equal access and free reuse, not about selling it for profit. Selling open data conflicts with the idea of unrestricted, free availability for everyone.


10.

A data model is used to organize _____ and how they relate to one another.

  • data visualizations

  • database structures

  • data elements

  • spreadsheet fields

Explanation

Explanation:

A data model defines how data elements are organized and how they relate to each other within a database system. It specifies the structure, relationships, and constraints of the data, ensuring consistency and facilitating efficient storage and retrieval. Data elements are the fundamental units of data—such as names, dates, or product IDs—that the model organizes into entities and relationships.

Correct Answer:

data elements

Why Other Options Are Wrong:

data visualizations

Data visualizations are graphical representations of data used for analysis and presentation, not the basic units that a data model organizes.

database structures

While a data model informs the database structure, it specifically organizes the data elements and their relationships, not just the overall architecture.

spreadsheet fields

Spreadsheet fields refer to cells or columns in a spreadsheet application and are not the conceptual components managed by a data model.


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