- (Exam Topic 6)
You work for a shipping company that has distribution centers where packages move on delivery lines to route them properly. The company wants to add cameras to the delivery lines to detect and track any visual damage to the packages in transit. You need to create a way to automate the detection of damaged packages and flag them for human review in real time while the packages are in transit. Which solution should you choose?

1. A. Use BigQuery machine learning to be able to train the model at scale, so you can analyze the packages in batches.
2. B. Train an AutoML model on your corpus of images, and build an API around that model to integrate with the package tracking applications.
3. C. Use the Cloud Vision API to detect for damage, and raise an alert through Cloud Function
4. D. Integrate the package tracking applications with this function.
5. E. Use TensorFlow to create a model that is trained on your corpus of image
6. F. Create a Python notebook in Cloud Datalab that uses this model so you can analyze for damaged packages.

Correct Answer: A

- (Exam Topic 6)
You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

1. A. Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
2. B. Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.
3. C. Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
4. D. Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.

Correct Answer: D

- (Exam Topic 2)
Flowlogistic wants to use Google BigQuery as their primary analysis system, but they still have Apache Hadoop and Spark workloads that they cannot move to BigQuery. Flowlogistic does not know how to store the data that is common to both workloads. What should they do?

1. A. Store the common data in BigQuery as partitioned tables.
2. B. Store the common data in BigQuery and expose authorized views.
3. C. Store the common data encoded as Avro in Google Cloud Storage.
4. D. Store he common data in the HDFS storage for a Google Cloud Dataproc cluster.

Correct Answer: B

- (Exam Topic 6)
Your company is selecting a system to centralize data ingestion and delivery. You are considering messaging and data integration systems to address the requirements. The key requirements are:
The ability to seek to a particular offset in a topic, possibly back to the start of all data ever captured
Support for publish/subscribe semantics on hundreds of topics
Retain per-key ordering Which system should you choose?

1. A. Apache Kafka
2. B. Cloud Storage
3. C. Cloud Pub/Sub
4. D. Firebase Cloud Messaging

Correct Answer: A

- (Exam Topic 6)
A data scientist has created a BigQuery ML model and asks you to create an ML pipeline to serve predictions. You have a REST API application with the requirement to serve predictions for an individual user ID with latency under 100 milliseconds. You use the following query to generate predictions: SELECT predicted_label, user_id FROM ML.PREDICT (MODEL ‘dataset.model’, table user_features). How should you create the ML pipeline?

1. A. Add a WHERE clause to the query, and grant the BigQuery Data Viewer role to the application service account.
2. B. Create an Authorized View with the provided quer
3. C. Share the dataset that contains the view with the application service account.
4. D. Create a Cloud Dataflow pipeline using BigQueryIO to read results from the quer
5. E. Grant the Dataflow Worker role to the application service account.
6. F. Create a Cloud Dataflow pipeline using BigQueryIO to read predictions for all users from the query.Write the results to Cloud Bigtable using BigtableI
7. G. Grant the Bigtable Reader role to the application service account so that the application can read predictions for individual users from Cloud Bigtable.

Correct Answer: D