A developer would like to add a new dimension of type: yesno for the enabled column in their users table. The column is of type: string in the database and returns yes and no values.
How should the developer define the yesno dimension?
A)

B)

C)

D)

• A.Option C
• B.Option A
• C.Option B
• D.Option D

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A user reports the following SQL error when selecting the discounted sale price field:
ERROR: column "order_items.sale_price"; must appear in the GROUP BY clause or be used in an aggregate function.
The developer checks the field definition and finds it to be:
measure: discounted_sale_price {
type: number
sql: ${sale_price} * 0.8 ;;
}
The developer also finds the LookML definition of the sale_price field to be:
dimension: sale_price {
type: number
sql: ${TABLE}.sale_price ;;
}
What is the likely cause of the SQL error?

• A.The underlying database table does not have a field called sale_price.
• B.The sale_price field should be defined as a measure of type: number, not as a dimension.
• C.The discounted_sale_price field should have a group_by: yes parameter.
• D.The discounted_sale_price field should be defined as a dimension of type: number, not as a measure.

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A LookML developer finishes some LookML work and commits changes in their personal development branch. The developer is asked to Pull and Merge Other Changes.
What does this indicate?

• A.A change has been committed in another developer's personal branch
• B.A change has been deployed to a shared branch.
• C.A change has been committed in another shared branch.
• D.A change has been deployed to production.

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A developer wants to create a measure that shows the item count broken out by category. When a second, more granular dimension is added to the same query, the count broken out by category should still represent the original aggregation and be duplicated on each line. The business wants this "count" in "category" available in the Explore section without any additional work done by the end user. For example:
The Count column represents the count for each combination of Category and Item.
The Count in Category column represents the count for each Category only.

How can the developer address this need with a LookML object?

• A.Create a measure filtered on Category, and make the filter value controlled by a parameter.
• B.Calculate the measure using a derived table, and then join that derived table back into the Explore.
• C.Create a measure with type: sum_over_dimension, and make the dimension value controlled by a parameter.
• D.Calculate the overall count using table calculations in the Explore.

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The developer is creating an Explore that includes the product users, and orders views that will meet the following guidelines.
Joins between the orders and users views should not incur high performance costs.
Users of this Explore will primarily be looking at data from the orders view.
Users of this Explore should only be able to see orders from the retailer "Fashion.ly".
The only field the users need from the products view is product.name.
Which LookML should the developer use?
A)

B)

C)

D)

• A.Option C
• B.Option A
• C.Option D
• D.Option B

Comment: *

Name: *

Email: *

Verification: *