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| Section | Weight | Objectives |
|---|
| Data Preparation and Ingestion | 30% | - Data ingestion into Google Cloud services
- 1. Cloud Storage ingestion patterns
- 2. Streaming ingestion with Pub/Sub concepts
|
| Data Management | 25% | - Data governance and security
- 1. IAM and access control
- 2. Data lifecycle management
- Storage and data organization
- 1. BigQuery datasets and tables management
- 2. Cloud Storage lifecycle policies
|
| Data Analysis and Presentation | 27% | - Data visualization
- 1. Looker / Looker Studio reporting
- Querying and analyzing data
- 1. BigQuery SQL usage
- 2. Data aggregation and transformation
|
| Data Pipeline Orchestration | 18% | - Pipeline design and automation
- 1. Dataflow pipelines
- 2. Workflow orchestration concepts (e.g., Cloud Composer)
|
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Google Associate Data Practitioner Sample Questions (Q62-Q67):
NEW QUESTION # 62
Your organization has decided to migrate their existing enterprise data warehouse to BigQuery. The existing data pipeline tools already support connectors to BigQuery. You need to identify a data migration approach that optimizes migration speed. What should you do?
- A. Use the existing data pipeline tool's BigQuery connector to reconfigure the data mapping.
- B. Create a temporary file system to facilitate data transfer from the existing environment to Cloud Storage. Use Storage Transfer Service to migrate the data into BigQuery.
- C. Use the BigQuery Data Transfer Service to recreate the data pipeline and migrate the data into BigQuery.
- D. Use the Cloud Data Fusion web interface to build data pipelines. Create a directed acyclic graph (DAG) that facilitates pipeline orchestration.
Answer: A
NEW QUESTION # 63
You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?
- A. Use Cloud Client Libraries to transfer the data over the internet.
- B. Use the gcloud storage command to transfer the data over the internet.
- C. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.
- D. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
Answer: D
NEW QUESTION # 64
Your company uses Looker to visualize and analyze sales dat
a. You need to create a dashboard that displays sales metrics, such as sales by region, product category, and time period. Each metric relies on its own set of attributes distributed across several tables. You need to provide users the ability to filter the data by specific sales representatives and view individual transactions. You want to follow the Google-recommended approach. What should you do?
- A. Create a single Explore with all sales metrics. Build the dashboard using this Explore.
- B. Use Looker's custom visualization capabilities to create a single visualization that displays all the sales metrics with filtering and drill-down functionality.
- C. Use BigQuery to create multiple materialized views, each focusing on a specific sales metric. Build the dashboard using these views.
- D. Create multiple Explores, each focusing on each sales metric. Link the Explores together in a dashboard using drill-down functionality.
Answer: A
NEW QUESTION # 65
Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?
- A. Use Cloud Data Fusion pipelines.
- B. Use Cloud Composer operators.
- C. Use Dataflow pipelines.
- D. Use Dataform workflows.
Answer: D
NEW QUESTION # 66
Your organization has several datasets in BigQuery. The datasets need to be shared with your external partners so that they can run SQL queries without needing to copy the data to their own projects. You have organized each partner's data in its own BigQuery dataset. Each partner should be able to access only their dat a. You want to share the data while following Google-recommended practices. What should you do?
- A. Grant the partners the bigquery.user IAM role on the BigQuery project.
- B. Use Analytics Hub to create a listing on a private data exchange for each partner dataset. Allow each partner to subscribe to their respective listings.
- C. Export the BigQuery data to a Cloud Storage bucket. Grant the partners the storage.objectUser IAM role on the bucket.
- D. Create a Dataflow job that reads from each BigQuery dataset and pushes the data into a dedicated Pub /Sub topic for each partner. Grant each partner the pubsub. subscriber IAM role.
Answer: B
NEW QUESTION # 67
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