PDE Practice Test 3 — 10 Questions

Question 1

Your team uses Looker Studio to build dashboards on top of BigQuery. The dashboards are slow when filtering on a high-cardinality dimension (e.g., user ID). You want to improve performance without changing the underlying BigQuery table design. Which action should you take?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Enable BigQuery BI Engine on the project.. BI Engine automatically caches the BigQuery tables in memory for Looker Studio, accelerating queries on any dimension. Enabling BI Engine on the project will improve dashboard performance.

Answer

Create a clustered table on the user ID column.

Answer

Apply a filter to limit data to the last month only.

Answer

Use Looker Studio's extract data functionality.

Question 2

A company wants to track data lineage for their BigQuery tables to understand how data flows from source to derived tables. Which TWO Google Cloud services can be used to capture and visualize data lineage? (Choose 2.)

Accepted Answer

Dataplex Data Lineage. Dataplex provides a comprehensive Data Lineage feature that automatically captures lineage for BigQuery jobs. Additionally, the BigQuery Lineage API (part of Data Catalog) allows you to retrieve lineage programmatically.

Answer

Vertex AI Feature Store

Answer

Cloud Composer

Answer

Cloud Data Fusion

Question 3

A data pipeline processes sensitive customer data. You need to ensure that only authorised users can query the data in BigQuery, and that the data is encrypted at rest and in transit. Which THREE steps should you take? (Choose three.)

Accepted Answer

Create authorised views in BigQuery to restrict access to sensitive columns. Encryption at rest is enabled by default with CMEK or CSEK. In-transit encryption is default for BigQuery. Authorised views provide fine-grained access control. IAM roles control dataset access.

Answer

Use a Cloud VPN to encrypt data in transit between on-premises and Google Cloud

Answer

Grant the bigquery.dataViewer role at the dataset level to all users

Question 4

A Dataflow pipeline is processing a high-volume streaming data stream. The job is lagging behind by 30 minutes, and the Dataflow monitoring UI shows high system latency with low CPU utilization. Which action should be taken to improve throughput?

Accepted Answer

Enable Dataflow Shuffle. High system latency with low CPU utilization indicates a bottleneck in data shuffling, not in processing capacity. Enabling Dataflow Shuffle offloads the shuffle operation to Google-managed resources, reducing disk I/O and network overhead, which directly improves throughput in streaming pipelines.

Answer

Enable Streaming Engine

Answer

Increase the number of workers

Answer

Disable hot key detection

Question 5

A data scientist developed a model using custom training on Vertex AI. They want to automate the entire training-to-deployment process. Which service should they use?

Accepted Answer

Vertex AI Pipelines. Vertex AI Pipelines is the correct choice because it provides a fully managed, serverless orchestration service specifically designed to automate ML workflows, including custom training, hyperparameter tuning, evaluation, and deployment. It integrates natively with Vertex AI services and supports Kubeflow Pipelines SDK or TFX for defining reproducible, end-to-end pipelines, making it the ideal solution for automating the entire training-to-deployment process.

Answer

Cloud Composer

Answer

Cloud Build

Answer

Cloud Functions

Question 6

A company uses BigQuery and wants to reduce query costs by using BI Engine for Looker Studio dashboards. The data is stored in a BigQuery dataset with 5 TB of frequently accessed tables. The dashboards run dozens of concurrent queries. What is the recommended approach to enable BI Engine acceleration?

Accepted Answer

Create a reservation in the Administration panel and assign it to the project.. BI Engine is a reserved capacity service that caches data in memory. You must reserve capacity (amount of memory) for a specific BigQuery region, and then BI Engine automatically accelerates queries from Looker Studio and other BI tools. It does not require you to grant specific IAM roles to users (they just need BigQuery permissions) or to create materialized views. You do not need to enable it per dataset; it works at the project/region level.

Answer

Enable BI Engine by setting the dataset option 'enable_bi_engine=TRUE' in the dataset metadata.

Answer

Grant all Looker Studio users the 'biengine.user' IAM role on the project.

Answer

Create materialized views of the tables and connect Looker Studio to the views.

Question 7

A company is using Looker to explore their BigQuery data. They have defined a LookML model with an 'explore' that joins two views: 'orders' and 'customers'. The join is a left join. They want to ensure that only customers with orders are shown when exploring. Which LookML parameter should they modify?

Accepted Answer

Change the join type from 'left_outer' to 'inner'. The 'join_type' parameter in LookML defines the join type. Changing it to 'inner' will exclude customers without orders.

Answer

Set the 'required_joins' parameter on the 'orders' view

Answer

Use a derived table with a WHERE clause

Answer

Add a filter in the 'customers' view to exclude nulls

Question 8

You need to build a Looker model that joins multiple tables from BigQuery. Which LookML object defines the relationship between tables?

Accepted Answer

EXPLORE. In LookML, an EXPLORE defines the starting point and joins to other views. A VIEW defines a single table or derived table. A MODEL contains explores and views. A JOIN is not a top-level object; joins are defined inside explores.

Answer

JOIN

Answer

VIEW

Answer

MODEL

Question 9

A data scientist wants to automate retraining of a classification model when new labeled data arrives. The model is deployed on AI Platform Prediction. Which Google Cloud service should be used to orchestrate the retraining pipeline?

Accepted Answer

AI Platform Pipelines. AI Platform Pipelines (now Vertex AI Pipelines) is the correct service because it provides a fully managed, serverless orchestration engine for building, deploying, and running machine learning pipelines. It integrates with Kubeflow Pipelines and TensorFlow Extended (TFX) to automate the retraining workflow when new labeled data arrives, enabling continuous training and model versioning without manual intervention.

Answer

AI Platform Prediction

Answer

AI Platform Continuous Evaluation

Answer

Cloud Dataflow

Question 10

Your company has a machine learning model that predicts customer churn. The model is deployed on Vertex AI Endpoints with autoscaling. After a marketing campaign, traffic to the endpoint increases by 10x. Some predictions start failing with 'HTTP 503 Service Unavailable' errors. What is the most likely cause?

Accepted Answer

The autoscaling configuration has insufficient maximum nodes to handle the traffic.. A 503 Service Unavailable error from Vertex AI Endpoints indicates that the endpoint is overwhelmed and cannot handle the incoming request volume. With a 10x traffic spike and autoscaling configured, the most likely cause is that the autoscaling configuration has insufficient maximum nodes, so the endpoint cannot scale out enough to handle the load, causing requests to be rejected.

Answer

The model container has a memory leak.

Answer

The model's accuracy has degraded due to data drift.

Answer

The model is using an older version that is not supported.