[05/Indigirka/02]

Which SQL feature allows the aggregation of values from multiple columns to create new columns for visualization in Explore?

Subquery
Indexing
Aggregate functions (correct)
JOIN

What is the purpose of using SUM(recovered) / SUM(confirmed) in SQL queries?

To extract specific data from the recovered and confirmed cases
To calculate the average of recovered and confirmed cases
To aggregate the recovered and confirmed cases (correct)
To filter the recovered cases from the confirmed cases

Which type of visualization might benefit from the use of aggregated columns in Explore?

Pie chart displaying the percentage of recovered and confirmed cases (correct)
Line graph depicting changes in recovered cases over time
Scatter plot of recovered and confirmed cases
Bar chart showing individual recovered and confirmed cases

In SQL, it is possible to aggregate values from multiple columns using aggregate functions for visualization in Explore.

True (A) Signup and view all the answers

The use of SUM(recovered) / SUM(confirmed) in SQL queries is not allowed for creating new columns for visualization in Explore.

False (B) Signup and view all the answers

Aggregated columns in Explore can only be created using basic SQL functions, not aggregate functions.

False (B) Signup and view all the answers

Match the SQL function with its purpose in creating new columns for visualization in Explore:

SUM(recovered) / SUM(confirmed) = Calculating recovery rate AVG(value) = Calculating average value COUNT(*) = Counting total rows MAX(number) = Finding maximum value Signup and view all the answers

Match the following programming languages with their primary usage:

Python = General-purpose programming JavaScript = Client-side scripting for web applications SQL = Database queries CSS = Styling web pages Signup and view all the answers

Match the mathematical operations with their purpose in SQL queries:

SUM() = Aggregating total values COUNT() = Counting number of records AVG() = Calculating average MAX() = Finding maximum value Signup and view all the answers

What are virtual metrics in Flow.BI used for?

Creating new metrics that are not present in the underlying data sources (A) Signup and view all the answers

How are virtual metrics created in Flow.BI?

By clicking the Create button on the Explore page and entering a SQL expression (A) Signup and view all the answers

What should be done after creating a virtual metric in Flow.BI?

Use it in charts, dashboards, and reports just like any other metric (B) Signup and view all the answers

What is a tip for using virtual metrics in Flow.BI?

Give your virtual metrics clear and concise names (A) Signup and view all the answers

Which type of SQL expression is used to define virtual metrics in Flow.BI?

Descriptive SQL expressions (B) Signup and view all the answers

What do virtual metrics enable users to do in Flow.BI?

Extend the capabilities of Flow.BI and create new and innovative ways to explore and visualize data (D) Signup and view all the answers

What is an example of a virtual metric mentioned in the text?

'Number of source columns' (B) Signup and view all the answers

Why is it important to document virtual metrics?

To communicate their purpose and usage to other users (C) Signup and view all the answers

What should be done before using virtual metrics in production?

Test them thoroughly (B) Signup and view all the answers

Virtual metrics in Flow.BI are created using SQL expressions.

True (A) Signup and view all the answers

Virtual metrics can only be used to create new metrics that are already present in the underlying data sources.

False (B) Signup and view all the answers

To create a virtual metric, you need to enter a name, description, and an SQL expression in the Flow.BI Explore page.

True (A) Signup and view all the answers

After creating a virtual metric, it cannot be used in charts, dashboards, and reports like any other metric.

False (B) Signup and view all the answers

Testing virtual metrics before using them in production is not important.

False (B) Signup and view all the answers

Virtual metrics enable users to extend the capabilities of Flow.BI and create new and innovative ways to explore and visualize data.

True (A) Signup and view all the answers

Aggregated columns in Explore can only be created using basic SQL functions, not aggregate functions.

False (B) Signup and view all the answers

The use of SUM(recovered) / SUM(confirmed) in SQL queries is allowed for creating new columns for visualization in Explore.

False (B) Signup and view all the answers

It is important to give virtual metrics clear and concise names.

True (A) Signup and view all the answers

Match the virtual metric with its example mentioned in the text:

Number of source columns = Aggregating the number of source columns processed Number of data records = Aggregating the number of data records processed Average of revenue = Calculating the average revenue from sales data Total profit margin = Summing up the profit margin for all products Signup and view all the answers

Match the SQL function with its purpose in creating new columns for visualization in Explore:

SUM() = Aggregating numeric values CONCAT() = Combining text strings AVG() = Calculating average values COUNT() = Counting non-null values Signup and view all the answers

Match the tip for using virtual metrics with its description:

Give your virtual metrics clear and concise names. = Ensure easy identification and understanding of virtual metrics Use descriptive SQL expressions to define your virtual metrics. = Provide detailed and explanatory SQL expressions for better comprehension Document your virtual metrics. = Record details and explanations about the virtual metrics for future reference Test your virtual metrics thoroughly before using them in production. = Validate the accuracy and reliability of virtual metrics before implementation Signup and view all the answers

Match the type of visualization with the use of aggregated columns in Explore:

Dashboard = Provides an overview of key metrics and performance indicators Chart = Visual representation of data for comparison or analysis Report = Detailed analysis or summary of data presented in a structured format Data table = Tabular display of raw data or detailed information Signup and view all the answers

Match the purpose of documenting virtual metrics with its importance:

Ensuring transparency and accountability = Allows others to understand and verify the calculation logic behind virtual metrics Facilitating knowledge transfer = Enables sharing insights and best practices related to virtual metric creation Maintaining consistency and standardization = Ensures uniformity and conformity in virtual metric naming and definitions Supporting troubleshooting and error analysis = Aids in identifying issues and resolving discrepancies related to virtual metric usage Signup and view all the answers

[05/Indigirka/02]

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Questions and Answers

Which SQL feature allows the aggregation of values from multiple columns to create new columns for visualization in Explore?

What is the purpose of using SUM(recovered) / SUM(confirmed) in SQL queries?

Which type of visualization might benefit from the use of aggregated columns in Explore?

In SQL, it is possible to aggregate values from multiple columns using aggregate functions for visualization in Explore.

The use of SUM(recovered) / SUM(confirmed) in SQL queries is not allowed for creating new columns for visualization in Explore.

Aggregated columns in Explore can only be created using basic SQL functions, not aggregate functions.

Match the SQL function with its purpose in creating new columns for visualization in Explore:

Match the following programming languages with their primary usage:

Match the mathematical operations with their purpose in SQL queries:

What are virtual metrics in Flow.BI used for?

How are virtual metrics created in Flow.BI?

What should be done after creating a virtual metric in Flow.BI?

What is a tip for using virtual metrics in Flow.BI?

Which type of SQL expression is used to define virtual metrics in Flow.BI?

What do virtual metrics enable users to do in Flow.BI?

What is an example of a virtual metric mentioned in the text?

Why is it important to document virtual metrics?

What should be done before using virtual metrics in production?

Virtual metrics in Flow.BI are created using SQL expressions.

Virtual metrics can only be used to create new metrics that are already present in the underlying data sources.

To create a virtual metric, you need to enter a name, description, and an SQL expression in the Flow.BI Explore page.

After creating a virtual metric, it cannot be used in charts, dashboards, and reports like any other metric.

Testing virtual metrics before using them in production is not important.

Virtual metrics enable users to extend the capabilities of Flow.BI and create new and innovative ways to explore and visualize data.

Aggregated columns in Explore can only be created using basic SQL functions, not aggregate functions.

The use of SUM(recovered) / SUM(confirmed) in SQL queries is allowed for creating new columns for visualization in Explore.

It is important to give virtual metrics clear and concise names.

Match the virtual metric with its example mentioned in the text:

Match the SQL function with its purpose in creating new columns for visualization in Explore:

Match the tip for using virtual metrics with its description:

Match the type of visualization with the use of aggregated columns in Explore:

Match the purpose of documenting virtual metrics with its importance:

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