Updated Google Professional-Data-Engineer Dumps – Check Free Professional-Data-Engineer Exam Dumps (2025) [Q152-Q176]

QUESTION 152
When you store data in Cloud Bigtable, what is the recommended minimum amount of stored data?

QUESTION 153
How can you get a neural network to learn about relationships between categories in a categorical feature?

QUESTION 154
Which Google Cloud Platform service is an alternative to Hadoop with Hive?

QUESTION 155
What Dataflow concept determines when a Window’s contents should be output based on certain criteria being met?

QUESTION 156
You are a head of BI at a large enterprise company with multiple business units that each have different priorities and budgets. You use on-demand pricing for BigQuery with a quota of 2K concurrent on-demand slots per project. Users at your organization sometimes don’t get slots to execute their query and you need to correct this. You’d like to avoid introducing new projects to your account.
What should you do?

QUESTION 157
You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of-Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required.
You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)

QUESTION 158
You are building a model to make clothing recommendations. You know a user’s fashion preference is
likely to change over time, so you build a data pipeline to stream new data back to the model as it
becomes available. How should you use this data to train the model?

QUESTION 159
You are developing a software application using Google’s Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?

QUESTION 160
The marketing team at your organization provides regular updates of a segment of your customer dataset. The marketing team has given you a CSV with 1 million records that must be updated in BigQuery. When you use the UPDATE statement in BigQuery, you receive a quotaExceeded error. What should you do?

QUESTION 161
You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD.You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

QUESTION 162
You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
The user profile: What the user likes and doesn’t like to eat The user account information: Name, address, preferred meal times The order information: When orders are made, from where, to whom The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?

QUESTION 163
You are building a teal-lime prediction engine that streams files, which may contain Pll (personal identifiable information) data, into Cloud Storage and eventually into BigQuery You want to ensure that the sensitive data is masked but still maintains referential Integrity, because names and emails are often used as join keys How should you use the Cloud Data Loss Prevention API (DLP API) to ensure that the Pll data is not accessible by unauthorized individuals?

QUESTION 164
Which of the following statements is NOT true regarding Bigtable access roles?

QUESTION 165
You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query – -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do?

QUESTION 166
Which of these statements about BigQuery caching is true?

QUESTION 167
Why do you need to split a machine learning dataset into training data and test data?

QUESTION 168
How would you query specific partitions in a BigQuery table?

QUESTION 169
When you store data in Cloud Bigtable, what is the recommended minimum amount of stored data?

QUESTION 170
You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now
automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to
query all of the tables for the past 30 days in legacy SQL. What should you do?

QUESTION 171
A data scientist has created a BigQuery ML model and asks you to create an ML pipeline to serve predictions. You have a REST API application with the requirement to serve predictions for an individual user ID with latency under 100 milliseconds. You use the following query to generate predictions: SELECT predicted_label, user_id FROM ML.PREDICT (MODEL ‘dataset.model’, table user_features). How should you create the ML pipeline?

QUESTION 172
Your company is using WHILECARD tables to query data across multiple tables with similar names. The SQL statement is currently failing with the following error:
# Syntax error : Expected end of statement but got “-” at [4:11] SELECT age FROM bigquery-public-data.noaa_gsod.gsod WHERE age != 99 AND_TABLE_SUFFIX = `1929′ ORDER BY age DESC Which table name will make the SQL statement work correctly?

QUESTION 173
Which of these is not a supported method of putting data into a partitioned table?

QUESTION 174
You create an important report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. You notice that visualizations are not showing data that is less than 1 hour old. What should you do?

QUESTION 175
What are two of the benefits of using denormalized data structures in BigQuery?

QUESTION 176
Your company operates in three domains: airlines, hotels, and ride-hailing services. Each domain has two teams: analytics and data science, which create data assets in BigQuery with the help of a central data platform team. However, as each domain is evolving rapidly, the central data platform team is becoming a bottleneck. This is causing delays in deriving insights from data, and resulting in stale data when pipelines are not kept up to date. You need to design a data mesh architecture by using Dataplex to eliminate the bottleneck. What should you do?