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Google Associate Data Practitioner Sample Questions:

1. You need to design a data pipeline that ingests data from CSV, Avro, and Parquet files into Cloud Storage.
The data includes raw user input. You need to remove all malicious SQL injections before storing the data in BigQuery. Which data manipulation methodology should you choose?

A) ETL
B) ELT
C) ETLT
D) EL

2. You are designing a BigQuery data warehouse with a team of experienced SQL developers. You need to recommend a cost- effective, fully-managed, serverless solution to build ELT processes with SQL pipelines.
Your solution must include source code control, environment parameterization, and data quality checks. What should you do?

A) Use Dataform to build, orchestrate, and monitor the pipelines.
B) Use Dataproc to run MapReduce jobs for distributed data processing.
C) Use Cloud Data Fusion to visually design and manage the pipelines.
D) Use Cloud Composer to orchestrate and run data workflows.

3. 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) Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.
B) Apply a filter to only show products with a positive profit margin.
C) Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
D) Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).

4. You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?

A) Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.
B) Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.
C) Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.
D) Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.

5. 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 Dataflow pipelines.
B) Use Dataform workflows.
C) Use Cloud Composer operators.
D) Use Cloud Data Fusion pipelines.

Solutions: