Data Management

You have sensitive data in Cloud Storage that needs to be deleted after 30 days to comply with regulatory requirements. What is the most efficient way to manage this?

You need to ensure that PII (Personally Identifiable Information) in BigQuery is automatically detected and tagged across your organization. Which Dataplex feature should you enable on your Lake?

Which service should you use to search for and discover datasets across your entire Google Cloud organization?

You need to control access to specific columns in a BigQuery table using Dataplex-integrated policy tags. What must you create before you can apply a policy tag to a column?

What is the purpose of a 'Data Zone' in Dataplex?

What happens if you delete a Dataplex Lake?

You are configuring a Dataplex Data Quality task. You want to validate that a 'user_id' column has no NULL values. Where do you define this rule?

You need to audit who accessed sensitive data in a Dataplex Lake. Which service should you monitor to see access logs for these data assets?

Which role is required to manage Dataplex assets within a Zone?

You have a Data Catalog taxonomy that you want to share across multiple projects. How do you achieve this?

What is the primary function of the 'Dataplex Discovery' process?

You need to track lineage for a BigQuery table populated by a Dataflow pipeline. How does Dataplex help?

What is the role of the 'Dataplex Data Steward'?

Which service allows you to view the schema and metadata of a BigQuery table that has been registered in Dataplex?

You want to enforce that all data in a specific Dataplex Zone must be encrypted with a Customer-Managed Encryption Key (CMEK). How do you enforce this?

You have data scattered across multiple projects and need to provide a unified data governance view. What is the recommended hierarchy?

A user complains they cannot see a Dataplex Lake in the console. You verify they have the 'Viewer' role on the project. What is missing?

Which of the following is NOT a benefit of using Dataplex?

What does 'Data Lineage' show you in Dataplex?

You need to move an asset from one Dataplex Zone to another. What is the correct procedure?

You want to perform data quality checks on a BigQuery table that is updated daily. How should you schedule the Dataplex task?

You have an automated pipeline that deletes files in a GCS bucket every hour. Dataplex shows the asset as 'Out of sync'. Why?

You have a Dataplex Lake containing data from two different regions. How does this affect data access?

Which console menu would you navigate to in order to access Dataplex?

You are configuring a Dataplex asset that points to a GCS bucket. You want to ensure that only files in a specific folder are included in the asset. How do you specify this?

Which TWO of the following statements about Dataplex discovery are true? (Choose two)

You have noticed that your data quality tasks are failing. Which THREE of the following are potential causes for failure? (Choose three)

You need to organize your data governance strategy. Which TWO of the following are valid ways to use Dataplex Zones to improve your data organization? (Choose two)

A team is migrating to Dataplex. Which TWO of the following are prerequisites for adding a BigQuery dataset as an asset to a Lake? (Choose two)

You are implementing a security strategy for your data lake. Which THREE of the following are supported ways to control access to data within a Dataplex Lake? (Choose three)

When setting up a new Dataplex Lake, which TWO of the following configurations are required? (Choose two)

You need to ensure data compliance for PII. Which THREE of the following tools or features should you use in combination with Dataplex? (Choose three)

Which TWO of the following are true about Dataplex assets? (Choose two)

Which THREE of the following are common administrative tasks when managing a Dataplex Lake? (Choose three)

Which TWO of the following are valid locations for a Dataplex Lake? (Choose two)

Which TWO of the following are true regarding Dataplex security? (Choose two)

You need to migrate legacy data to a Dataplex Lake. Which THREE of the following should you consider for a successful migration? (Choose three)

Which TWO of the following tools allow you to interact with Dataplex? (Choose two)

A retail analytics team stores raw clickstream events in a Cloud Storage bucket. They want to query this data with BigQuery using standard SQL without loading it into BigQuery native storage, and they want to minimize cost by avoiding duplicate storage. Which Google Cloud feature should they use?

You are the data engineer for an online retailer. A Cloud Storage bucket named orders-raw contains daily CSV exports from an on-premises order management system. Each file is named with a date stamp, and new files arrive once per day. You need to load this data into BigQuery with minimal ongoing operational effort, and the load must automatically pick up each new file as it arrives. What should you do?

A marketing analyst needs to run a one-time SQL query that joins a BigQuery table containing campaign performance data with a small CSV file stored in a Cloud Storage bucket. The CSV is updated weekly by an external partner. The analyst wants the query to always reflect the latest CSV without loading it into BigQuery each week. What should the analyst do?

You manage a BigQuery dataset that contains a table with millions of rows. Analysts frequently query only the most recent 30 days of data, but full-table scans are expensive. You need to reduce query costs and improve performance for these time-based queries with minimal changes to the table structure. What should you do?

You are designing a data lake in Cloud Storage and need to ensure that data is organized for efficient querying by BigQuery and other analytics services. You plan to use a Hive-style partitioned directory structure. Which two practices should you follow? (Choose two.)

You are designing a BigQuery table for a fleet of IoT devices that emit one reading per second. The table will hold years of data, and most queries filter by device identifier and a time range. You want to reduce the bytes scanned by these queries and control long-term storage cost. (Choose two.)

Your organization stores sensitive customer data in a Cloud Storage bucket. You need to ensure that data is automatically classified and tagged as 'PII' when it is written, and that the tags are available for audit and access control decisions. You want to minimize manual effort and use Google Cloud native tooling. What should you do?

A data engineer needs to load a 500 GB CSV file from a Cloud Storage bucket into a BigQuery table once per day. The CSV has a header row and uses comma delimiters. The engineer wants the simplest managed approach that requires no code and handles schema autodetection. What should the engineer use?

You need to grant a data analyst read-only access to a specific BigQuery dataset. The analyst should be able to query tables but must not be able to modify data or view other datasets in the project. Which IAM role should you grant on the dataset?

You are the data engineer for a retail company on Google Cloud. Analysts query a BigQuery table that contains 400 TB of point-of-sale records and almost always filter by transaction_date. Query costs have grown sharply because every query scans the full table. You need the most cost-effective change that reduces bytes scanned for date-filtered queries without altering the table schema. What should you do?

A healthcare analytics team stores patient encounter records in Cloud Storage as CSV files and needs to run SQL over them in BigQuery without loading or duplicating the data. The files must remain the system of record, and the team wants to avoid storage charges for a second copy. Which BigQuery feature should they use?

You have a BigQuery table that is partitioned by day on a DATE column. You need to ensure that data older than 90 days is automatically deleted to reduce storage costs, while keeping the table structure and recent data intact. What should you do?

You need to load a large CSV file from Cloud Storage into BigQuery. The file contains a header row, and you want to automatically detect the schema. You also need to ensure that if any row has a type mismatch, the load job fails and reports the error. Which load configuration should you use?

A healthcare organization needs to analyze sensitive patient data in BigQuery while ensuring that analysts can see aggregated results but cannot view individual patient identifiers. Which Google Cloud feature should they implement?

Your analytics team stores clickstream events in Cloud Storage as newline-delimited JSON files. They want to query this data with BigQuery using SQL without loading it into native BigQuery storage, and they want the table definition to refresh automatically when new files land in the bucket. What should you configure?

You manage a BigQuery dataset that contains a table with 500 TB of historical order data. Analysts frequently run queries that filter on the `order_date` column. Query costs are rising because every query scans the entire table. You want to reduce the bytes scanned and cost without changing the table name or existing SQL. What should you do?

You are designing a data lake in Cloud Storage and need to ensure that analysts can query the data using BigQuery without moving or copying the data. You also need to enforce fine-grained access control at the column level for sensitive fields. Which two actions should you take? (Choose two.)

Your company stores sensitive customer records in a Cloud Storage bucket. A compliance officer requires that every object in the bucket be automatically classified and that any object containing credit card numbers be flagged for review. You want a managed Google Cloud service that samples and inspects the data without writing custom code. What should you use?

You have a BigQuery table that is partitioned by ingestion time. You need to reduce storage costs by automatically deleting data older than 90 days. You want to ensure that the deletion happens without manual intervention and that the partitions are completely removed. What should you do?

You are designing a data governance strategy for a BigQuery environment. You need to automatically apply policy tags to columns that contain sensitive data so that only authorized users can query those columns. Which two actions should you take? (Choose two.)

A compliance officer requires that a Cloud Storage bucket holding customer records retain every object version for seven years, and that no user, including project owners, be able to delete or overwrite those versions during that period. You need a configuration that enforces this even against accidental or malicious deletion attempts. What should you configure?

A retail company stores point-of-sale events in Pub/Sub and wants them available for SQL analysis in BigQuery with minimal operational overhead and near-real-time latency. The team has no servers to manage and wants the simplest supported path. Which approach should they use?

You are a data analyst at a marketing firm. You need to query a large dataset stored in BigQuery, but you want to minimize query costs. The dataset contains a column named event_time of type TIMESTAMP. Most of your queries filter on event_time for a specific day. What should you do to reduce the amount of data scanned by your queries?

A retail company ingests point-of-sale events into BigQuery. Analysts frequently filter by store_id and by transaction date, and the table grows by several hundred gigabytes per month. You want to reduce the bytes scanned by these filtered queries with the least effort. What should you do?

You are loading a daily CSV file from Cloud Storage into a BigQuery table. The file contains a header row, uses comma delimiters, and has some rows with extra trailing columns. You want the load to tolerate these malformed rows by skipping them and recording how many were skipped, without failing the whole job. Which load configuration should you use?

You are a data engineer at a healthcare company. You need to create a Dataflow pipeline that reads from a Pub/Sub subscription and writes to BigQuery. The pipeline must handle late-arriving data and ensure exactly-once processing. You also need to minimize cost. Which of the following should you use?

Your organization stores raw event data in a Cloud Storage bucket that receives new files throughout the day. Analysts want to query this data with SQL in BigQuery without loading it into native BigQuery storage first. The data is in Parquet format and partitioned by date in the folder structure. What should you create?

A fintech firm streams transaction events into a Pub/Sub topic. The analytics team needs near-real-time aggregates in BigQuery and must also retain the raw events for seven years in Cloud Storage for compliance. They want a managed service with minimal code. Which pipeline should you recommend?