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| Section | Weight | Objectives |
|---|
| Topic 1: Data Analysis and Presentation | 27% | - Data visualization and reporting
- 1. Looker dashboards and reports
- 2. Visualization best practices
- Business intelligence and decision support
- 1. Communicate findings effectively
- 2. Answer business questions with data
- Data exploration and analysis
- 1. BigQuery SQL queries
- 2. Jupyter notebooks for analysis
- 3. Identify trends, patterns, insights
|
| Topic 2: Data Preparation and Ingestion | 30% | - Storage solutions selection
- 1. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner
- 2. Storage location types: regional, dual-regional, multi-regional, zonal
- Data loading methods
- 1. Batch and streaming ingestion
- 2. gcloud, BQ CLI, client libraries
- Data extraction and transfer tools
- 1. Cloud Data Fusion, Storage Transfer Service
- 2. Dataflow, BigQuery Data Transfer Service, Database Migration Service
- Data formats and classification
- 1. Structured, semi-structured, unstructured data
- 2. Formats: CSV, JSON, Parquet, Avro, database tables
|
| Topic 3: Data Pipeline Orchestration | 18% | - Data transformation concepts
- 1. ETL vs ELT processes
- 2. Data transformation requirements
- Transformation tools selection
- 1. Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, Dataform
- Pipeline automation and scheduling
- 1. Schedule and monitor data jobs
- 2. Error handling and monitoring
|
| Topic 4: Data Management and Governance | 25% | - Data security and access control
- 1. Data encryption and protection
- 2. IAM roles and permissions
- Data quality and maintenance
- 1. Data validation and cleaning
- 2. Data lifecycle management
- Compliance and governance
- 1. Data privacy and regulatory requirements
- 2. Data stewardship and cataloging
|
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Google Associate Data Practitioner Sample Questions (Q19-Q24):
NEW QUESTION # 19
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 BigQuery Data Transfer Service to recreate the data pipeline and migrate the data into BigQuery.
- B. Use the Cloud Data Fusion web interface to build data pipelines. Create a directed acyclic graph (DAG) that facilitates pipeline orchestration.
- C. Use the existing data pipeline tool's BigQuery connector to reconfigure the data mapping.
- D. 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.
Answer: C
NEW QUESTION # 20
Your organization has a petabyte of application logs stored as Parquet files in Cloud Storage. You need to quickly perform a one- time SQL-based analysis of the files and join them to data that already resides in BigQuery. What should you do?
- A. Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.
- B. Launch a Cloud Data Fusion environment, use plugins to connect to BigQuery and Cloud Storage, and use the SQL join operation to analyze the data.
- C. Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.
- D. Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.
Answer: D
NEW QUESTION # 21
Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards.
You need to implement a solution quickly and efficiently. What should you do?
- A. Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
- B. Apply a filter to only show products with a positive profit margin.
- C. Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
- D. Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.
Answer: A
NEW QUESTION # 22
You manage a large amount of data in Cloud Storage, including raw data, processed data, and backups. Your organization is subject to strict compliance regulations that mandate data immutability for specific data types.
You want to use an efficient process to reduce storage costs while ensuring that your storage strategy meets retention requirements. What should you do?
- A. Use object holds to enforce immutability for specific objects, and configure lifecycle management rules to transition objects to appropriate storage classes based on age and access patterns.
- B. Configure lifecycle management rules to transition objects to appropriate storage classes based on access patterns. Set up Object Versioning for all objects to meet immutability requirements.
- C. Create a Cloud Run function to periodically check object metadata, and move objects to the appropriate storage class based on age and access patterns. Use object holds to enforce immutability for specific objects.
- D. Move objects to different storage classes based on their age and access patterns. Use Cloud Key Management Service (Cloud KMS) to encrypt specific objects with customer-managed encryption keys (CMEK) to meet immutability requirements.
Answer: A
NEW QUESTION # 23
Your organization needs to store historical customer order dat
a. The data will only be accessed once a month for analysis and must be readily available within a few seconds when it is accessed. You need to choose a storage class that minimizes storage costs while ensuring that the data can be retrieved quickly. What should you do?
- A. Store the data in Cloud Storage using Archive storage.
- B. Store the data in Cloud Storage using Nearline storage.
- C. Store the data in Cloud Storage using Standard storage.
- D. Store the data in Cloud Storage using Coldline storage.
Answer: B
NEW QUESTION # 24
......
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