Get 2022 Updated Free Google LookML-Developer Exam Questions & Answer [Q17-Q40]

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Get 2022 Updated Free Google LookML-Developer Exam Questions and Answer

LookML-Developer Dumps PDF and Test Engine Exam Questions

Google LookML-Developer Exam Syllabus Topics:

Topic	Details
Topic 1	Determine which additional features to use to refine data Analyze business requirements and determine LookML code implementation to meet requirements
Topic 2	Build project-based needs (e.g., data sources, replication, mock reports provided by clients) Determine which views and tables to use
Topic 3	Determine appropriate caching settings based on data warehouse’s update frequency Apply procedural concepts to implement persistent derived tables and caching policies based on requirements
Topic 4	Ensure existing contents are working (e.g., use Content Validator, audit, search for errors) Maintain the health of LookML projects in a given scenario
Topic 5	Modify existing project structure to account for new reporting needs Design new LookML dimensions or measures with given requirements
Topic 6	Analyze data models and business requirements to create LookML objects Determine how to join views into Explores
Topic 7	Optimize SQLs for cost or efficiency based on business requirements Determine why specific queries return results by looking at the generated SQL in SQL Runner
Topic 8	Apply procedural concepts to evaluate the performance of queries and reports Apply procedural concepts to optimize queries and reports for performance

NEW QUESTION 17
A developer needs to implement three persistent derived tables (PDTs) as described below.
The PDTs need to be refreshed after the daily ETL pipeline adds incremental loads to the underlying tables.
Each PDT is built off of one underlying table in the database (one PDT per table).
The underlying tables for each PDT are updated one after the other, and a new row is added to an ETL log table each time a table is updated.
Due to the unpredictable nature of the ETL pipeline, each PDT does not refresh at the same time from day to day.
Each PDT takes over an hour to build, and to save on compute costs each PDT should only be refreshed once per day.
How can the developer set up the PDTs according to these requirements?

Create one datagroup tied to all three PDTs that runs when the total row count across all three tables changes.

Create one datagroup tied to all three PDTs that parameterizes the view name for each PDT in the SQL trigger condition.

Create three separate datagroups tied to three PDTs that run when each corresponding table’s row count changes.

Create three separate datagroups tied to three PDTs that run when a new row is added to the ETL log table.

NEW QUESTION 18
A LookML developer has a transactions view with several measures that each perform complex calculations involving multiple fields. The LookML developer creates an Explore based on the transactions view. The product team wants to perform further functions on these measures, such as SUM, AVG, MIN, MAX, and RANK. The team wants these further functions to be performed at different levels of detail: weekly, monthly, and yearly.
How can the LookML developer model these requirements and minimize the amount of code rewriting?

Add measures to the transactions view of type: number to apply the required functions.

Change the existing measures in the transactions view to dimensions, and add measures of the different required types.

Create a constant for each measure so it can be reused across other areas of the LookML project.

Create native derived tables using transactions as the explore_source.

NEW QUESTION 19
Users report that every time they change the filter on their Explore, the filters take a very long time to populate.
How can the developer improve the filtering experience with this Explore?

Limit the filter suggestions using the suggestions parameter.

Add an always_filter parameter to restrict the filter suggestions.

Use an access_filter parameter to automatically apply filters.

Add persistence to the base view of the Explore.

NEW QUESTION 20
A user reports that, when a date dimension is filtered to “before now” results are returned that consistently include tomorrow. Dimension fill has been ruled out as a cause of the issue.
Which LookML parameter should be used to resolve this issue?

Week_start_day

Convert_tz

Datatype

Fiscal_month_offset

NEW QUESTION 21
A developer creates a derived table and wants to add persistence to it. Because the table is not used on a frequent basis, the developer wants the table to be cached for 12 hours, but only when a user has queried it.
Which persistence parameter should be added to the derived table’s definition in order to satisfy this use case?

persist_with: “12 hours”

datagroup: 12_hours {
max_cache_age: “12 hours”
}

persist_for: “12 hours”

sql_trigger_value: SELECT FLOOR{UNIX_TIMESTAMP{} / {6*60*60}} ;;

NEW QUESTION 22
A developer wants to calculate the ratio of total sales from the orders view and total users from the users view.
Which two methods can be used to create a measure that meets these requirements? (Choose two.)

B)

C)

D)

E)

Option A

Option B

Option C

Option D

Option E

NEW QUESTION 23
Two developers are working on adding a new view to a project. Once both developers have finished their work in the view, the changes will be pushed to production.
Where should the developers write the LookML for this view?

In the master branch, with both users writing to the branch

In one user’s personal branch, with both users writing to the branch

In a new shared branch created from the master branch

In each of their personal branches, with each user writing code separately

NEW QUESTION 24
A developer has the dimensions enrollment_month and graduation_month already defined in the view. Both were created as part of dimension_groups of type: time. The developer need to use these two dimensions in the sql_start and sql_end parameters of a dimension group of type: duration.
Which LookML should be used to calculate the number of month and years between enrollment month and graduation month?
A)

B)

C)

D)

Option A

Option B

Option C

Option D

NEW QUESTION 25
A developer has User Specific Time Zones enabled for a Looker instance, but wants to ensure that queries run in Looker are as performant as they can be. The developer wants to add a datatype: date parameter to all dimension_group definitions without time data in a table-based view, so that time conversions don’t occur for these fields.
How can the developer determine to which fields this parameter should be applied through SQL Runner?

Open the Explore query in SQL Runner and validate whether removing the conversion from date fields changes the results.

Open the Explore query in SQL Runner to determine which fields are converted.

Use the CAST function in SQL Runner to ensure that all underlying fields are dates and conversions are not applied.

Use the Describe feature in SQL Runner to determine which fields include time data.

NEW QUESTION 26
Business users report that an ephemeral derived table tile on the dashboard is slow.
Information about the dashboard includes:
The dashboard filter is linked to the user attributes.
This tile usually takes approximately 5 minutes to complete running.
Which solution should be used to improve the dashboard load time?

Use a conditional WHERE clause for Development Mode.

Build a user attribute filter into the Explore.

Use index distribution_key or sort_key for this derived table.

Persist the derived table.

NEW QUESTION 27
A retail company wants to limit who can see the financial information in their reports to executives and store managers. The LookML Developer creates a user attribute called leadership with the value “000” for executives and “999” for store managers. The developer creates three access grant objects and one dimension:

How should the developer ensure that only authorized users see the data in the Total Revenue dimension?

required_access_grants: [can_view_financial_data]

required_access_grants: [leadership]

required_access_grants: [“000″,”999”]

required_access_grants: [total_revenue]

NEW QUESTION 28
A developer has created a persistent derived table that tracks new or updated orders and they want to cache the results. The cache should be refreshed whenever some new order is available on the underlying datasource table my tablename or at least every 24 hours.
Which datagroup definition will refresh the cache as expected?
A)

B)

C)

D)

Option A

Option B

Option C

Option D

NEW QUESTION 29
A developer is connecting a LookML project to a remote Git repository. The developer wants to track which users are committing code changes, creating pull requests, or deploying to production when the different Git commands are initiated from within Looker.
Which type of Git connection should be utilized to meet this business requirement?

A bare Git repository

Multiple account HTTPS

Single account HTTPS

SSH

NEW QUESTION 30
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)

Option A

Option B

Option C

Option D

NEW QUESTION 31
The daily_forecast Explore used by the sales team needs to be cached for 24 hours. All other Explores used by the sales team need to be cached for one hour.
What is a scalable way to configure this caching logic?

Define two datagroups for the model. Apply persist_with at the model level with the datagroup for 1-hour caching, and apply persist_with to daily_forecast with the datagroup for 24-hour caching.

Define max_cache_age on daily_forecast Explores of 24 hours. Define max_cache_age on all other Explores for one hour.

Define two datagroups for the model. Create a persistent derived table (PDT) for the daily_forecast Explore, and apply datagroup_trigger to it using the datagroup for 24-hour caching.

Define for the model one datagroup that caches for 1 hour. Create a persistent derived table (PDT) for the daily_forecast Explore, and apply sql_trigger_value to it selecting the current date.

NEW QUESTION 32
A user reports an error message on an Explore: “Non-unique value/primary key (or sql_distinct_key), value overflow or collision when computing sum”.
What should the LookML developer check for in the joined views of the Explore?

The sum measure used is defined correctly.

A unique primary key is defined in each view.

Symmetric_aggregates: no is not present in the Explore definition.

No concatenated primary keys are used.

NEW QUESTION 33
A LookML developer creates an Explore that joins two views. The base view has information about users’ interactions with the support team. The joined view contains data about the users. The support team using this Explore feels overwhelmed by the amount of data this Explore shows them and decides to just look at open tickets.
What should the developer add to the Explore in the model to achieve these requirements?

A filtered measure

The hidden parameter

The sql_always_where parameter

A relationship definition

NEW QUESTION 34
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?

Create a measure filtered on Category, and make the filter value controlled by a parameter.

Calculate the measure using a derived table, and then join that derived table back into the Explore.

Create a measure with type: sum_over_dimension, and make the dimension value controlled by a parameter.

Calculate the overall count using table calculations in the Explore.

NEW QUESTION 35
A LookML developer creates a new model and a test dashboard from the model. The developer shares the link to the new dashboard with users, but the users report that all they see is the “Model Not Found” error.
What is a possible cause of this issue?

The developer has not pushed the new model to Production Mode.

The developer has not added users to the new model set.

The users do not have permission to access this dashboard.

The new model is missing an Explore definition.

NEW QUESTION 36
A developer needs to build a new dimension that offers an age-based cohort representation of users.
Which LookML code should the developer use to meet the requirement?
A)

B)

C)

D)