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What are all of the BigQuery operations that Google charges for?
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You are designing a data mesh on Google Cloud by using Dataplex to manage data in BigQuery and Cloud Storage. You want to simplify data asset permissions. You are creating a customer virtual lake with two user groups: * Data engineers, which require lull data lake access * Analytic users, which require access to curated data You need to assign access rights to these two groups. What should you do?
Your infrastructure team has set up an interconnect link between Google Cloud and the on-premises network. You are designing a high-throughput streaming pipeline to ingest data in streaming from an Apache Kafka cluster hosted on-premises. You want to store the data in BigQuery, with as minima! latency as possible. What should you do?
You are using BigQuery with a regional dataset that includes a table with the daily sales volumes. This table is updated multiple times per day. You need to protect your sales table in case of regional failures with a recovery point objective (RPO) of less than 24 hours, while keeping costs to a minimum. What should you do?
You have a BigQuery table that ingests data directly from a Pub/Sub subscription. The ingested data is encrypted with a Google-managed encryption key. You need to meet a new organization policy that requires you to use keys from a centralized Cloud Key Management Service (Cloud KMS) project to encrypt data at rest. What should you do?
Your company built a TensorFlow neural-network model with a large number of neurons and layers. The model fits well for the training dat a. However, when tested against new data, it performs poorly. What method can you employ to address this?
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Question 14 - Professional Data Engineer discussion

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You want to use a database of information about tissue samples to classify future tissue samples as either normal or mutated. You are evaluating an unsupervised anomaly detection method for classifying the tissue samples. Which two characteristic support this method? (Choose two.)

A.
There are very few occurrences of mutations relative to normal samples.
Answers
A.
There are very few occurrences of mutations relative to normal samples.
B.
There are roughly equal occurrences of both normal and mutated samples in the database.
Answers
B.
There are roughly equal occurrences of both normal and mutated samples in the database.
C.
You expect future mutations to have different features from the mutated samples in the database.
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C.
You expect future mutations to have different features from the mutated samples in the database.
D.
You expect future mutations to have similar features to the mutated samples in the database.
Answers
D.
You expect future mutations to have similar features to the mutated samples in the database.
E.
You already have labels for which samples are mutated and which are normal in the database.
Answers
E.
You already have labels for which samples are mutated and which are normal in the database.
Suggested answer: A, D

Explanation:

Unsupervised anomaly detection techniques detect anomalies in an unlabeled test data set under the assumption that the majority of the instances in the data set are normal by looking for instances that seem to fit least to the remainder of the data set.

https://en.wikipedia.org/wiki/Anomaly_detection

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asked 18/09/2024
Akash Patel
40 questions
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