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Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Visualization and Insights | 20-30% | - Choose appropriate visualization types - Present data insights to stakeholders - Build visualizations using Looker Studio - Interpret and communicate findings - Create dashboards and reports |
| Topic 2: Data Preparation and Exploration | 20-30% | - Identify data quality issues - Explore data through visualization and queries - Perform exploratory data analysis (EDA) - Transform and prepare data for analysis - Ingest and acquire data |
| Topic 3: Data-Driven Decision Making | 10-20% | - Identify stakeholders and requirements - Assess data quality and completeness - Define success metrics - Translate business requirements into data solutions |
| Topic 4: Data Processing and Analytics | 20-30% | - Apply statistical methods for analysis - Build and maintain data pipelines - Query and analyze datasets - Aggregate and summarize data - Use BigQuery and SQL for analytics |
Google Associate Data Practitioner Sample Questions:
1. 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 --no- clobber option.
B) Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
C) Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
D) Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
2. 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) 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.
B) Export the BigQuery data to a Cloud Storage bucket. Grant the partners the storage.objectUser IAM role on the bucket.
C) Grant the partners the bigquery.user IAM role on the BigQuery project.
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.
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) Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
B) Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
C) Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.
D) Apply a filter to only show products with a positive profit margin.
4. Your team wants to create a monthly report to analyze inventory data that is updated daily. You need to aggregate the inventory counts by using only the most recent month of data, and save the results to be used in a Looker Studio dashboard. What should you do?
A) Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.
B) Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.
C) Create a materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
D) Create a saved query in the BigQuery console that uses the SUM() function and the DATE_SUB() function. Re-run the saved query every month, and save the results to a BigQuery table.
5. Following a recent company acquisition, you inherited an on- premises data infrastructure that needs to move to Google Cloud. The acquired system has 250 Apache Airflow directed acyclic graphs (DAGs) orchestrating data pipelines. You need to migrate the pipelines to a Google Cloud managed service with minimal effort. What should you do?
A) Create a Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
B) Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.
C) Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.
D) Create a Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: B |
Kenneth -
I must say that majority of the questions were almost the same as ADP dumps, which were provided to me in the PrepAway study guide, therefore passing my ADP exam was not a difficult task for me.