Google ADP

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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. You need to design a data pipeline to process large volumes of raw server log data stored in Cloud Storage.
The data needs to be cleaned, transformed, and aggregated before being loaded into BigQuery for analysis.
The transformation involves complex data manipulation using Spark scripts that your team developed. You need to implement a solution that leverages your team's existing skillset, processes data at scale, and minimizes cost. What should you do?

A) Use Dataflow with a custom template for the transformation logic.
B) Use Cloud Data Fusion to visually design and manage the pipeline.
C) Use Dataproc to run the transformations on a cluster.
D) Use Dataform to define the transformations in SQLX.

2. 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) Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.
B) Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.
C) 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.
D) Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.

3. You manage data at an ecommerce company. You have a Dataflow pipeline that processes order data from Pub/Sub, enriches the data with product information from Bigtable, and writes the processed data to BigQuery for analysis. The pipeline runs continuously and processes thousands of orders every minute. You need to monitor the pipeline's performance and be alerted if errors occur. What should you do?

A) Use BigQuery to analyze the processed data in Cloud Storage and identify anomalies or inconsistencies. Set up scheduled alerts based when anomalies or inconsistencies occur.
B) Use the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.
C) Use Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.
D) Use Cloud Monitoring to track key metrics. Create alerting policies in Cloud Monitoring to trigger notifications when metrics exceed thresholds or when errors occur.

4. You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?

A) Use Vertex Al Workbench to develop a custom model for purchase prediction.
B) Use Colab Enterprise to develop a custom model for purchase prediction.
C) Use BigQuery ML to create a logistic regression model for purchase prediction.
D) Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.

5. Your organization uses a BigQuery table that is partitioned by ingestion time. You need to remove data that is older than one year to reduce your organization's storage costs. You want to use the most efficient approach while minimizing cost. What should you do?

A) Require users to specify a partition filter using the alter table statement in SQL.
B) Create a view that filters out rows that are older than one year.
C) Create a scheduled query that periodically runs an update statement in SQL that sets the "deleted" column to "yes" for data that is more than one year old. Create a view that filters out rows that have been marked deleted.
D) Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.

Solutions: