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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 24% | - Planning data solutions
|
| Topic 2: Ingesting and processing data | 25% | - Transforming data
|
| Topic 3: Storing and managing data | 20% | - Implementing storage solutions
|
| Topic 4: Preparing data for analysis and machine learning | 13% | - Preparing data for ML
|
| Topic 5: Maintaining and automating data workloads | 18% | - Operationalizing workloads
|
1. You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?
A) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
B) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
C) Deploy the Cloud SQL Proxy on the Cloud Dataproc master
D) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
2. You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?
A) cron
B) Workflow Templates on Cloud Dataproc
C) Cloud Scheduler
D) Cloud Composer
3. You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?
A) Write an Apache Beam pipeline that creates a BigQuery table per data
B) Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.
C) Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.
D) Re-create the tables using DD
E) Partition the tables by a column containing a TIMESTAMP or DATE Type.
F) Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.
4. You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?
A) Cloud Spanner
B) Cloud Bigtable
C) Cloud Datastore
D) Cloud SQL
5. If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?
A) Before you test, run a heavy pre-test for several minutes.
B) Use at least 300 GB of data.
C) Do not use a production instance.
D) Run your test for at least 10 minutes.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: C |
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