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Google ADP Exam Syllabus Topics:

SectionWeightObjectives
Data Management and Governance25%- Compliance and governance
  • 1. Data privacy and regulatory requirements
  • 2. Data stewardship and cataloging
- Data quality and maintenance
  • 1. Data validation and cleaning
  • 2. Data lifecycle management
- Data security and access control
  • 1. Data encryption and protection
  • 2. IAM roles and permissions
Data Analysis and Presentation27%- Data visualization and reporting
  • 1. Looker dashboards and reports
  • 2. Visualization best practices
- Business intelligence and decision support
  • 1. Answer business questions with data
  • 2. Communicate findings effectively
- Data exploration and analysis
  • 1. BigQuery SQL queries
  • 2. Jupyter notebooks for analysis
  • 3. Identify trends, patterns, insights
Data Pipeline Orchestration18%- Data transformation concepts
  • 1. Data transformation requirements
  • 2. ETL vs ELT processes
- 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
Data Preparation and Ingestion30%- Data loading methods
  • 1. Batch and streaming ingestion
  • 2. gcloud, BQ CLI, client libraries
- Data formats and classification
  • 1. Structured, semi-structured, unstructured data
  • 2. Formats: CSV, JSON, Parquet, Avro, database tables
- Data extraction and transfer tools
  • 1. Dataflow, BigQuery Data Transfer Service, Database Migration Service
  • 2. Cloud Data Fusion, Storage Transfer Service
- Storage solutions selection
  • 1. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner
  • 2. Storage location types: regional, dual-regional, multi-regional, zonal

Google Associate Data Practitioner Sample Questions:

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. 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.
  • B. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.
  • C. 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.
  • D. Create a custom quota for each analyst in BigQuery.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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 Dataform to define the transformations in SQLX.
  • B. Use Dataflow with a custom template for the transformation logic.
  • C. Use Dataproc to run the transformations on a cluster.
  • D. Use Cloud Data Fusion to visually design and manage the pipeline.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
  • B. 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.
  • C. 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.
  • D. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

You need to create a new data pipeline. You want a serverless solution that meets the following requirements:
* Data is streamed from Pub/Sub and is processed in real-time.
* Data is transformed before being stored.
* Data is stored in a location that will allow it to be analyzed with SQL using Looker.
Which Google Cloud services should you recommend for the pipeline?

  • A. Dataflow BigQuery
  • B. BigQuery Analytics Hub
  • C. Dataproc Serverless Bigtable
  • D. Cloud Composer Cloud SQL for MySQL
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

You are designing a pipeline to process data files that arrive in Cloud Storage by 3:00 am each day. Data processing is performed in stages, where the output of one stage becomes the input of the next. Each stage takes a long time to run. Occasionally a stage fails, and you have to address the problem. You need to ensure that the final output is generated as quickly as possible. What should you do?

  • A. Design the processing as a directed acyclic graph (DAG) in Cloud Composer. Clear the state of the failed task after correcting any stage output data errors.
  • B. Design a Spark program that runs under Dataproc. Code the program to wait for user input when an error is detected. Rerun the last action after correcting any stage output data errors.
  • C. Design the pipeline as a set of PTransforms in Dataflow. Restart the pipeline after correcting any stage output data errors.
  • D. Design the workflow as a Cloud Workflow instance. Code the workflow to jump to a given stage based on an input parameter. Rerun the workflow after correcting any stage output data errors.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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