LOOKER-BUSINESS-ANALYST Online Practice Questions and Answers

An analyst creates a column chart showing the count of total orders and the count of returned orders on each date. The number of returned orders is much smaller than the number of total orders, so the columns for the returned orders are short and it is difficult to compare all the columns visually.

How should the analyst ensure that the differences between returned order counts for each day are more visible?

A. Change the returned orders series to a line type.

B. Move the returned orders series to a new right axis.

C. Change the y-axis height to a higher number of pixels.

D. Set the x-axis to use a log scale.

An analyst has an Explore query that shows the sum of spend over time. The Explore query has the Sum of Spend measure pivoted by a Category of Spend dimension. The Category of Spend dimension has a value for Budgeted Spend and then categories for each type of unbudgeted spend.

Which visualization feature should the analyst use to separate budgeted spend visually from each category of unbudgeted spend?

A. Display row totals for each category.

B. Series type customization on budgeted spend.

C. Grouped series positioning on budgeted spend.

D. Transpose table to separate out budgeted spend.

An analyst is trying to create a pie chart showing the breakdown of the top sales by brand in an Explore. The analyst selects the Brand Name dimension and a measure for the Count of Items Sold. The analyst then selects the pie chart visualization, but sees the error "Too Many Rows: Pie charts can display a maximum of 50 rows of data."

How can the analyst resolve this error and create a pie chart that will always show the top brands by items sold?

A. Sort the data by Count of Items Sold descending and apply a row limit of 50.

B. Sort the data by Brand Name alphabetically and apply a row limit of 50.

C. Apply a filter on the Count of Items Sold measure that requires the count to be greater than zero.

D. Apply a filter on the Count of Items Sold measure that requires the count to be not NULL, sort the data by Count of Items Sold ascending, and apply a row limit of 50.

Two users report seeing different results on the same dashboard.

Which three configurations could explain these discrepancies? (Choose three.)

A. The time zone setting is different for each user.

B. Looker caching is affecting results.

C. The dashboard uses separate Explores for each user.

D. Dashboard filters are being used

E. The dashboard was accessed via different boards.

An analyst has created a line chart with Value Labels enabled, but the values are too long and need to be abbreviated.

Which visualization option should the analyst utilize to alter the display of the value labels?

A. Axis Value Labels

B. Value Format

C. Label Rotation

D. Time Label Format

A company has a Customer Lookup dashboard that can be filtered on a unique customer name. Business users sometimes report unexpected data when they use filters with starts with or contains for the customer name.

How should the analyst ensure that the filter is unique to one customer?

A. Change the filter type to string.

B. Enable the setting Limit one filter value.

C. Use the Matches Advanced filtering option.

D. Disable the setting Allow multiple filter values.

An analyst is building out a company KPI dashboard and creates a blank dashboard. The analyst can

either create a new tile or use an existing Look.

What are two use cases for using Look-linked tile instead of building a query tile? (Choose two.)

A. The analyst wants to use the Look-linked tile in a separate company performance dashboard.

B. The analyst plans on creating a scheduled report of the associated Look.

C. The analyst is considering dashboard performance, and Look-linked tiles on dashboards lead to faster performance.

D. The analyst wants the flexibility to export the Look-linked tile results to additional file formats not supported by query tiles.

An analyst adds a Day dimension and a Signup Count measure to an Explore to show the number of new users added per day. The analyst wants to add a metric that increases by the number of new users per day, on a rolling basis.

How should that metric be calculated?

A. Add a Sum measure to the Explore and re-run the query.

B. Add a table calculation that calls running_portal (${users.signup_count})

C. Add a custom measure of type: running_total

D. Add a table calculation that calls ${users.signup_count:total}

An analyst is trying to rank companies in an Explore and visualize the rank as a column chart. The analyst selects the Brand Name dimension and the Rank dimension. They then select the column chart visualization type, but receive the error "Measure, time or numeric field required: Column graphs require at least one dimension or for the first dimension field to be of type: number or type: time".

How can the analyst resolve this error while showing the rank as a column visualization?

A. Pivot the Explore by the Brand Name dimension.

B. Select a measure to include in the Explore, then create a table calculation that multiplies the dimension by 1.0 using the syntax ${dimension}*1.0. Then hide the measure from the Explore.

C. Pivot the Explore by brand Rank.

D. Select a measure to include in the Explore, then create a table calculation that adds the Rank dimension to the measure multiplied by zero using the syntax ${dimension} + (${measure}*0). Then hide the measure from the Explore.

An analyst creates a dashboard that shows sales at an aggregate and then an individual level. This dashboard is slow to run, and the analyst sees a warning about how load times may be impacted in dashboards with more than 25 tiles.

What should the analyst create to make sure all data sources in this dashboard are connected but still load quickly?

A. Dashboard filter to specify which individual data shows

B. Two dashboards, one with aggregate and one with individual data

C. Two dashboards with a text tile to hyperlink from one dashboard to the other

D. Folder with all dashboard tiles for aggregate data and individual data.