4.1 Preparing Data for Visualization PROFESSIONAL-DATA-ENGINEER Practice Questions (Page 3)

Questions 11–15

1. 11expert · hard

   A company uses Looker to build dashboards on BigQuery. The dashboards are used by executives and need to be fast. The team has enabled BigQuery BI Engine, but some dashboards are still slow. The team suspects that the queries are not being accelerated by BI Engine. What is the most likely reason?

   • AThe BI Engine capacity is too small for the dataset size.
   • BThe queries use non-deterministic functions like RAND() or CURRENT_TIMESTAMP().
   • CThe Looker service account does not have the BigQuery Job User role.
   • DThe dashboards are using Looker's caching instead of BI Engine.
   Reveal Solution Discussion Select an answer first
2. 12expert · hard

   A data engineer is troubleshooting a slow BigQuery query that joins a large fact table with a smaller dimension table. The query filters on a date column in the fact table. The fact table is partitioned by date and clustered on the join key. The query still takes a long time. What is the most likely cause?

   • AThe join key in the fact table is not the same data type as the join key in the dimension table.
   • BThe query is scanning too much data because the filter on the date column is not selective enough.
   • CThe query is using a LEFT JOIN instead of an INNER JOIN.
   • DThe query is not filtering on the partition column in the dimension table.
   Reveal Solution Discussion Select an answer first
4. 13application · medium

   A logistics company has a BigQuery table `shipments` with columns `shipment_id`, `origin_zip`, `destination_zip`, `weight_kg`, and `shipped_at`. Analysts frequently create dashboards that group shipments by the day of the week and compute average weight. The query scans the entire table each time. Which approach best reduces query cost and simplifies the dashboard queries?

   • AAdd a clustered column for `shipped_at` and keep the dashboard queries unchanged.
   • BCreate a materialized view that groups by day-of-week and computes average weight.
   • CCreate a view that precomputes the day-of-week and average weight per day.
   • DUse BigQuery BI Engine to cache the entire table in memory.
   Reveal Solution Discussion Select an answer first
5. 14application · medium

   A data analyst reports that a BigQuery query joining two large tables takes over a minute to complete. The query filters on a timestamp column in one table and joins on a common key. The tables are not partitioned or clustered. What is the most effective first step to improve query performance?

   • ACreate a materialized view that precomputes the join result.
   • BIncrease the number of slots in the project's reservation.
   • CAdd partitioning on the timestamp column and clustering on the join key.
   • DUse a wildcard table to combine the two tables into one.
   Reveal Solution Discussion Select an answer first
6. 15foundation · easy

   A BigQuery query is running slowly because it scans a large amount of data. Which optimization is most likely to reduce the data scanned?

   • AEnabling the cache for the query
   • BUsing a wildcard table to combine multiple tables
   • CAdding partitioning and clustering to the table
   • DIncreasing the number of slots for the query
   Reveal Solution Discussion Select an answer first