Coursera Google Data Analytics Professional Prepare Data for Exploration (Week 3) Quiz Answer- Databases: Where data lives.

  

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1. Coursera: Machine Learning
2. Google Data Analytics Professional Certificate.

3.Databases:Where data lives.

Question 1

Primary and foreign keys are two connected identifiers within separate tables. These tables exist in what kind of database?

• Primary
• Relational
• Normalized
• Metadata

Primary and foreign keys are two connected identifiers within separate tables in a relational database.

 

Question 2

Metadata is data about data. What kinds of information can metadata offer about a particular dataset? Select all that apply.

• How to combine the data with another dataset
• Which analyses to perform on the data
• If the data is clean and reliable
• What kinds of data it contains

Metadata helps data analysts identify the type of data, if it is clean and reliable, and how it can be combined with another dataset.

 

Question 3

Think about data as a student at a high school. In this metaphor, which of the following are examples of metadata? Select all that apply.

• Classes the student is enrolled in
• Student’s ID number
• Grades the student earns
• Student’s enrollment date

The student ID number, enrollment date, and classes the student is enrolled in represent structural metadata.

 

Question 4

Think about data as a refrigerator. Which kind of metadata is the refrigerator’s product number?

• Redundant
• Administrative
• Structural
• Descriptive

The refrigerator’s product number is descriptive metadata because it is information that can help identify the refrigerator at a later date.

 

Question 5

What is the process that data analysts use to ensure the formal management of their company’s data assets?

• Data integrity
• Data governance
• Data mapping
• Data aggregation

Data governance is the process of ensuring the formal management of a company’s data assets.

 

Question 6

Describe the key differences between a star and a snowflake schema. Select all that apply.

• A star schema enables very fast data processing.
• A snowflake schema enables very fast data processing. This should not be selected
• A snowflake schema has one or more fact tables referencing any number of dimension tables. A star schema is an extension of a snowflake schema, with more dimensions and subdimensions.
• A star schema has one or more fact tables referencing any number of dimension tables. A snowflake schema is an extension of a star schema, with more dimensions and subdimensions.

A star schema has one or more fact tables referencing any number of dimension tables. A snowflake schema is an extension of a star schema, with more dimensions and subdimensions. It also enables very fast data processing.

 

Question 7

What are some key benefits of using external data? Select all that apply.

• External data is always reliable.
• External data is free to use.
• External data has broad reach.
• External data provides industry-level perspectives.

Some key benefits of using external data are that it has a broad reach and it provides industry-level perspectives.

 

Question 8

A data analyst reviews a database of Wisconsin car sales to find the last five car models sold in Milwaukee in 2019. How can they sort and filter the data to return the last five cars at the top? Select all that apply.

• Filter out sales outside of Milwaukee
• Filter out sales not in 2019
• Sort by date in ascending order
• Sort by date in descending order

The analyst can filter out sales outside of Milwaukee in 2019 and sort by date in descending order.

 

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