Google ADP Desktop Practice Exam Questions Software

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Processing and Analytics	20-30%	- Use BigQuery and SQL for analytics - Build and maintain data pipelines - Aggregate and summarize data - Apply statistical methods for analysis - Query and analyze datasets
Topic 2: Data Visualization and Insights	20-30%	- Present data insights to stakeholders - Create dashboards and reports - Build visualizations using Looker Studio - Choose appropriate visualization types - Interpret and communicate findings
Topic 3: Data-Driven Decision Making	10-20%	- Assess data quality and completeness - Identify stakeholders and requirements - Define success metrics - Translate business requirements into data solutions
Topic 4: Data Preparation and Exploration	20-30%	- Explore data through visualization and queries - Identify data quality issues - Ingest and acquire data - Transform and prepare data for analysis - Perform exploratory data analysis (EDA)

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100% Pass ADP - Exam Associate Data Practitioner Exercise

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Google Associate Data Practitioner Sample Questions (Q64-Q69):

NEW QUESTION # 64
Your company's customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files' metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?

A. Create an external table.
B. Create a native table.
C. Create an object table.
D. Create a temporary table.

Answer: C

NEW QUESTION # 65
Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?

A. Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.
B. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
C. Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.
D. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.

Answer: D

NEW QUESTION # 66
Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?

A. Create a custom quota for each analyst in BigQuery.
B. Assign each analyst to a separate project associated with their department. Create a single reservation for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.
C. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.
D. Assign each analyst to a separate project associated with their department. Create a single reservation by using BigQuery editions. Assign all projects to the reservation.

Answer: B

NEW QUESTION # 67
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 the gcloud storage command to transfer the data over the internet.
B. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
C. Use Cloud Client Libraries to transfer the data over the internet.
D. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.

Answer: B

NEW QUESTION # 68
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 Cloud Composer to orchestrate and run data workflows.
C. Use Cloud Data Fusion to visually design and manage the pipelines.
D. Use Dataproc to run MapReduce jobs for distributed data processing.

Answer: A

NEW QUESTION # 69
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