Cloud Bigtable is Google's ______ Big Data database service.

• A.Relational
• B.mySQL
• C.NoSQL
• D.SQL Server

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Which of the following statements about Legacy SQL and Standard SQL is not true?

• A.Standard SQL is the preferred query language for BigQuery.
• B.If you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.
• C.One difference between the two query languages is how you specify fully-qualified table names (i.e.
  table names that include their associated project name).
• D.You need to set a query language for each dataset and the default is Standard SQL.

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Suppose you have a dataset of images that are each labeled as to whether or not they contain a human face. To create a neural network that recognizes human faces in images using this labeled dataset, what approach would likely be the most effective?

• A.Use K-means Clustering to detect faces in the pixels.
• B.Use feature engineering to add features for eyes, noses, and mouths to the input data.
• C.Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.
• D.Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.

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You are using Google BigQuery as your data warehouse. Your users report that the following simple query is running very slowly, no matter when they run the query:
SELECT country, state, city FROM [myproject:mydataset.mytable] GROUP BY country You check the query plan for the query and see the following output in the Read section of Stage:1:

What is the most likely cause of the delay for this query?

• A.Users are running too many concurrent queries in the system
• B.Either the state or the city columns in the [myproject:mydataset.mytable]table have too many NULL values
• C.Most rows in the [myproject:mydataset.mytable]table have the same value in the country column, causing data skew
• D.The [myproject:mydataset.mytable] table has too many partitions

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An organization maintains a Google BigQuery dataset that contains tables with user-level data. They want to expose aggregates of this data to other Google Cloud projects, while still controlling access to the user- level data. Additionally, they need to minimize their overall storage cost and ensure the analysis cost for other projects is assigned to those projects. What should they do?

• A.Create and share an authorized view that provides the aggregate results.
• B.Create and share a new dataset and view that provides the aggregate results.
• C.Create and share a new dataset and table that contains the aggregate results.
• D.Create dataViewer Identity and Access Management (IAM) roles on the dataset to enable sharing.

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