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Following are some reference material for actual Google ADP exam test
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Management | 25% | - Data governance and security
|
| Topic 2: Data Preparation and Ingestion | 30% | - Data ingestion into Google Cloud services
|
| Topic 3: Data Analysis and Presentation | 27% | - Data visualization
|
| Topic 4: Data Pipeline Orchestration | 18% | - Pipeline design and automation
|
1. Your organization has a BigQuery dataset that contains sensitive employee information such as salaries and performance reviews. The payroll specialist in the HR department needs to have continuous access to aggregated performance data, but they do not need continuous access to other sensitive dat a. You need to grant the payroll specialist access to the performance data without granting them access to the entire dataset using the simplest and most secure approach. What should you do?
A) Create row-level and column-level permissions and policies on the table that contains performance data in the dataset. Provide the payroll specialist with the appropriate permission set.
B) Create a SQL query with the aggregated performance data. Export the results to an Avro file in a Cloud Storage bucket. Share the bucket with the payroll specialist.
C) Use authorized views to share query results with the payroll specialist.
D) Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.
2. Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?
A) Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.
B) Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
C) Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.
D) Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.
3. Your company wants to implement a data transformation (ETL) pipeline for their BigQuery data warehouse.
You need to identify a managed transformation solution that allows users to develop with SQL and JavaScript, has version control, allows for modular code, and has data quality checks. What should you do?
A) Use Dataproc to create an Apache Spark cluster and implement the transformations by using PySpark SQL.
B) Use Dataform to define the transformations in SQLX.
C) Create BigQuery scheduled queries to define the transformations in SQL.
D) Create a Cloud Composer environment, and orchestrate the transformations by using the BigQueryinsertJob operator.
4. Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?
A) Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
B) Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
C) Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
D) Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
5. You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?
A) Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
B) Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
C) Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.
D) Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: C |
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