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Free CLOUD-DIGITAL-LEADER Exam Braindumps (page: 6)

Page 5 of 104
PDF with 411 Questions

Your organization is developing an application that will manage payments and online bank accounts located around the world. The most critical requirement for your database is that each transaction is handled consistently. Your organization anticipates almost unlimited growth in the amount of data stored.
Which Google Cloud product should your organization choose?

  1. Cloud SQL
  2. Cloud Storage
  3. Firestore
  4. Cloud Spanner

Answer(s): D

Explanation:

Features of Cloud Spanner


Reference:

https://k21academy.com/google-cloud/cloud-sql-vs-cloud-spanner/



Your organization wants an economical solution to store data such as files, graphical images, and videos and to access and share them securely.
Which Google Cloud product or service should your organization use?

  1. Cloud Storage
  2. Cloud SQL
  3. Cloud Spanner
  4. BigQuery

Answer(s): A

Explanation:

- Google Storage is GCP's version of AWS Simple Storage Service (S3) and an S3 bucket would be equivalent to a Google Storage bucket across the two clouds



Your organization wants to predict the behavior of visitors to its public website. To do that, you have decided to build a machine learning model. Your team has database-related skills but only basic machine learning skills, and would like to use those database skills.
Which Google Cloud product or feature should your organization choose?

  1. BigQuery ML
  2. LookML
  3. TensorFlow
  4. Cloud SQL

Answer(s): A


Reference:

https://cloud.google.com/architecture/predicting-customer-propensity-to-buy



Your organization is developing an application that will capture a large amount of data from millions of different sensor devices spread all around the world. Your organization needs a database that is suitable for worldwide, high-speed data storage of a large amount of unstructured data.
Which Google Cloud product should your organization choose?

  1. Firestore
  2. Cloud Data Fusion
  3. Cloud SQL
  4. Cloud Bigtable

Answer(s): D


Reference:

https://cloud.google.com/bigtable
Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, enabling you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key. Bigtable is ideal for storing very large amounts of single- keyed data with very low latency. It supports high read and write throughput at low latency, and it is an ideal data source for MapReduce operations.
Bigtable is exposed to applications through multiple client libraries, including a supported extension to the Apache HBase library for Java. As a result, it integrates with the existing Apache ecosystem of open-source Big Data software.
Bigtable's powerful back-end servers offer several key advantages over a self-managed HBase installation:

Incredible scalability. Bigtable scales in direct proportion to the number of machines in your cluster. A self-managed HBase installation has a design bottleneck that limits the performance after a certain threshold is reached. Bigtable does not have this bottleneck, so you can scale your cluster up to handle more reads and writes.
Simple administration. Bigtable handles upgrades and restarts transparently, and it automatically maintains high data durability. To replicate your data, simply add a second cluster to your instance, and replication starts automatically. No more managing replicas or regions; just design your table schemas, and Bigtable will handle the rest for you.
Cluster resizing without downtime. You can increase the size of a Bigtable cluster for a few hours to handle a large load, then reduce the cluster's size again--all without any downtime. After you change a cluster's size, it typically takes just a few minutes under load for Bigtable to balance performance across all of the nodes in your cluster.






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