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Total Questions and Time Limit – 95 Questions and there is no time limit.
Exam Format and Passing Score – Multiple Choice and Passing score is 80%
GCP Compute Assessment Questions And Answers
Contents of Article [show]
A) The infrastructure-centric solution
(B) The platform-centric solution
C) The serverless logic solution
D) In the middle (cluster)
A) A container is a fully managed database service.
B) A container imitates a computer.
C) A container answers queries of very large datasets.
(D) A container makes it easier for teams to package, manage, and ship their code.
(A) Kubernetes Engine is a managed environment for deploying containerized apps.
B) Kubernetes Engine is a solution meant to help organizations achieve zero ops.
C) Kubernetes Engine provides practically unlimited computing power using virtual machines (VMs) in the cloud.
D) Kubernetes Engine is built on the closed-source Kubernetes system, making it easy to orchestrate container clusters or groups of containers.
4 – Developer agility comes from building systems composed of small, independent units of functionality focused on doing one thing well, so how does Cloud Functions help improve developer agility?
A) Cloud Functions lets organizations that really value time to market build apps quickly.
B) Cloud Functions lets organizations deploy and maintain a fleet of VMs through a series of containers.
C) Cloud Functions lets organizations make changes to the kernel by providing their own network or graphics drivers to squeeze out the last drop of performance.
(D) Cloud Functions lets organizations build and deploy services at the level of a single function, not at the level of entire applications, containers, or VMs.
A) Compute Engine is a type of software-as-a-service (SaaS).
B) Compute Engine provides innovative storage solutions using an open source container-orchestration system.
C) Compute Engine is a computing platform provided as a service, called a “platform-as-a-service” (PaaS).
(D) Compute Engine provides practically unlimited computing power using virtual machines (VMs) in the cloud.
A) Need to connect and extend cloud services.
B) Need a fully managed database service.
C) Don’t want to touch a server or infrastructure.
(D) Need complete control over the virtual-machine infrastructure.
7 – During the app building process, which of these challenges are relieved by App Engine that organizations would have previously had to do on their own? Select the 3 correct answers.
(A) Build their own infrastructure.
B) Control over the virtual-machine infrastructure.
(C) Grow the app as their computing needs increase.
(D) Make sure it’s available night and day.
A) User authentication
B) Machine learning
(C) Serverless economics
D) Relational database
A) App Engine routes packets across the globe and stores data at the edge of the network closest to the user so that the organization’s data is where their users need it.
B) App Engine allows organizations to manage a server or runtime environment.
(C) App Engine saves organizations time and cost in software application development by eliminating the need to buy, build, and operate computing hardware and other infrastructure.
D) App Engine deploys and maintains a fleet of VMs that enable organizations to create containerized workloads.
D) Serverless Logic
(A) Compute Engine makes it easy to create and configure high-performance VMs that will quickly and easily scale to any size workload.
B) Compute Engine provides better kernel-level control and encryption.
C) Compute Engine stores and serves object (or BLOB) data.
D) Compute Engine automates with event-driven functions that respond to cloud events.
(A) More rapid application development
B) Content delivery network
(C) Monitor app stability and performance
D) Worldwide autoscaling and load balancing
13 – Which product included in Google Cloud networking allows organizations to connect GCP resources in a separate network or domain and isolate them from each other for security and compliance?
A) Cloud Interconnect
B) Cloud CDN
(C) Virtual Private Cloud
D) Cloud DNS
A) Maximize resource utilization.
(B) Scaling without downtime.
C) Improve application reliability through integrated health checking.
D) Seamlessly migrate code from development to production.
A) A “network” is an SDK available across most popular mobile platforms.
B) A “network” is a container deployed regionally via the cloud.
C) A “network” is a series of instances deployed at the global network level.
(D) A “network” is an isolated, global resource holding configuration.
A) Portability achieved by using Docker and Kubernetes
(B) User authentication, versioning, and robust security tools like Cloud Security Scanner
C) TensorFlow for machine learning models and algorithms
D) Messaging service to pass data from gathering and processing systems
A) When every millisecond of latency counts, Google Cloud networking ensures that content is delivered with high throughput.
B) Google Cloud networking only operates outside of GCP.
(C) Organizations benefit from Google’s superb networking.
D) For the past 15 years, GCP has been building out a fast, powerful, high quality cloud infrastructure.
A) control of virtual machines
(B) time to market
C) patching zero-day exploits
D) testing datasets for machine learning
A) It adds files to a storage system.
(B) It provides a layer of logic so that organizations can write code to access other services.
C) It patches operating systems.
D) It removes unnecessary data from a container.
20 – Organizations can build apps that run on Kubernetes Engine that: (Select the 2 correct answers)
(A) Will scale up to handle massive computing loads quickly and efficiently.
(B) Are highly secure and reliable and backed by Google’s service level agreement.
C) Can connect to and extend cloud services.
D) Have high availability without a complex architecture.
A) Transfer data from on-premises to the cloud.
B) Route packets across the globe and store data closest to the user.
C) Eliminate the need to buy, build, and operate computing hardware.
(D) Develop faster and easier with cloud backend services.
22 – Mobile app teams can integrate their mobile apps with one of the available __________ and manage the integrated Firebase services via _____________ which includes tools from Google for developing apps, engaging with users, and earning more through mobile ads.
A) VMs (virtual machines), App Engine
B) containers, Docker
C) data kits, the interface
(D) SDKs (software development kits), the console
A) Google can capture up to a petabyte of data on one Transfer Appliance without impacting the outbound network.
(B) Google-grade data centers give you scale and security that would be very expensive to achieve on-premises.
C) Google bills in per-second increments, so you only pay for the compute time you use. With sustained use discounts, Google automatically gives discounted prices for long-running workloads with no up-front commitment required.
D) Google’s global private network is superior in performance to other clouds that route your traffic over the internet.
24 – Firebase is GCP’s mobile extension. Several of Firebase’s products are built on top of GCP products, providing mobile-optimized SDKs and capabilities. Which of these products can be amplified via Firebase?
A) Cloud Spanner
B) Cloud Engine
(C) Cloud Storage
D) Cloud SQL
25 – Which product included in Google Cloud networking serves content to end users with high availability and high performance?
A) Cloud DNS
B) Cloud Interconnect
(C) Cloud CDN
D) Virtual Private Cloud
(A) “With Cloud Functions, I can write simple, single-purpose functions that are attached to events emitted from my cloud infrastructure and services.”
B) “Cloud Functions saves me time and money in software application development by eliminating the need to buy, build, and operate computing hardware and other infrastructure.”
C) “Thanks to Cloud Functions, I finally have a platform to build my apps, allowing me to focus on fine-tuning the customer experience rather than on maintaining my infrastructure.”
D) “I now have practically unlimited computing power by using virtual machines (VMs) through Cloud Functions.”
27 – How does Compute Engine provide the same computing power that Google uses for its infrastructure?
A) By improving quality and time to market.
B) By reducing costs.
(C) By using virtual machines (VMs) in the cloud.
D) By focusing on writing code and not touching a server, cluster, or infrastructure.
A) Monitor app stability and performance
B) More rapid application development
(C) Content delivery network
(D) Worldwide autoscaling and load balancing
(A) Development agility
B) Insufficient storage
C) Big data complexity
D) App infrastructure
A) developer productivity
B) ease of use
(C) saving time and cost
D) SDKs and consoles available
GCP Storage And Databases Assessment Questions And Answers
A) It’s not good for very large amounts of data.
B) It’s not good for flat data and databases with lots of read-write actions.
(C) It’s not good for highly structured databases or transactional databases.
D) It’s not good for analytical data.
A) Cloud Firestore provides daily results for queries to show the changing data.
(B) Cloud Firestore takes care of scalability and operations for running document-oriented databases.
C) Cloud Firestore provides multi-document ACID transactions for SQL databases.
D) Cloud Firestore helps you schedule downtime for upgrades, resizing, or configuration changes.
4 – Cloud Storage ____________ object (or BLOB) data. Organizations can store an unlimited number of objects, up to 5 ___________ in size each.
(A) stores and serves, terabytes
B) ingests and transfers, gigabytes
C) transforms and organizes, zettabytes
D) processes and analyzes, petabytes
A) An enterprise-grade database service built for the cloud specifically to combine the benefits of relational database structure with relational horizontal scale.
B) A tool for developing and executing a wide range of data processing patterns on very large datasets.
(C) A flexible, scalable NoSQL cloud database to store and sync data for client- and server-side development.
D) An industry-leading local SDD that integrates with the other products in the Google Cloud Platform suite.
(A) If an organization’s app works with MySQL or PostgreSQL, it will work with Cloud SQL.
B) Cloud SQL builds on performance innovations in Compute Engine and persistent disk.
C) You don’t need to reserve Cloud SQL instances ahead of time to get savings, and you pay by the minute, not by the hour.
D) It’s easy to control with less infrastructure for you to manage and operate.
7 – “High availability and durability via replications is just there; you don’t need to think about it or manage it. No scheduled downtime for upgrades, resizing or configuration changes.” Which of the following concerns is addressed by this Cloud Firestore value proposition?
A) Infrastructure costs
8 – With Cloud Bigtable, organizations can accelerate time to market for their data-intensive applications, enable seamless, ________________, reduce operational overhead, and improve business operations.
A) cost configurability
B) availability of SDKs and consoles
(C) elastic scaling with zero downtime
D) future proofing
9 – Using your understanding of GCP options/products meant to address storage and database areas, which statement best aligns with where Cloud Bigtable fits within GCP?
A) Cloud Bigtable is a fully managed database service that makes it easy to set up, maintain, manage, and administer relational MySQL and PostgreSQL databases in the cloud.
B) Cloud Bigtable helps organizations capture data and rapidly pass massive numbers of messages securely between other Google Cloud Platform big data tools and other software applications.
C) Cloud Bigtable is good for relational database service management at scale that requires high availability and HTAP.
(D) Cloud Bigtable is aligned to the non-relational database requirements and is good for heavy read and write, events, and analytical data.
10 – What is Cloud SQL?
A) Compute SQL offers industry-leading local SSD performance and integrates with the other products in the Google Cloud Platform suite.
(B) Cloud SQL is a fully managed database service that makes it easy to set up, maintain, manage, and administer relational MySQL and PostgreSQL databases in the cloud.
C) Cloud SQL helps organizations capture data and rapidly pass massive amounts of messages securely between other Google Cloud Platform big data tools and other software applications.
D) Cloud SQL ingests event streams from anywhere, at any scale, for simple, reliable, real-time stream analytics.
A) Because Cloud Bigtable lowers warehousing costs and augments existing warehouses.
B) Because Cloud Bigtable scales up to handle massive computing loads quickly and efficiently.
C) Because Cloud Bigtable is a fully managed database service that makes it easy to set up, maintain, manage, and administer relational MySQL and PostgreSQL databases in the cloud.
(D) Because Cloud Bigtable is a high-performance NoSQL database service for large analytical and operational workloads.
12 – “Cloud Datastore enables you to hand off the responsibility of running a highly scalable document-oriented database to Google. From 10 users to 100s of millions of users, you will no longer need to spend time optimizing, configuring the database, updating it, or monitoring system health.” Which of the following concerns is addressed by this Cloud Datastore value proposition?
A) Infrastructure costs
A) Organizations that need to store binary data such as images, media serving, and backups.
B) Training and testing data that’s used in machine learning to validate data sets.
C) Organizations that are using relational databases at scale and need to store user metadata.
(D) Developing mobile and web applications and reducing operational burden with an enterprise-grade database.
(A) Time to market for data-intensive applications
B) Access from storage to compute servers within the region
(C) Scaling without downtime
D) Fully managed relational database
15 – With Cloud Firestore, you no longer need to determine the number of nodes or add servers or storage because:
(A) It’s a fully managed database service.
B) It’s a database service that uses SQL.
C) It’s a database service that allows complete control.
D) It’s a fully managed compute service.
A) Standard connectors and standard tools that allow for seamless integrations with existing SQL workflows.
B) Fully managed relational database services that use edge caching to provide performance.
(C) Regional buckets that enable faster access from storage to compute servers within the region.
D) Application patches and updates that optimize data processing when it comes to leveraging user data.
A) By providing intelligence from data.
B) Includes tape libraries and backup capabilities.
(C) Single API and millisecond data access latency across storage classes.
D) Most reliable service, according to Gartner.
A) Training data that’s used in machine learning.
B) Tertiary data such as website traffic, clicks, and returning page visitors.
(C) Binary data such as images, media serving, and backups.
D) Testing data that’s used to validate data sets.
A) Cloud Spanner is good for binary data such as images, media serving, and backups.
(B) Cloud Spanner is good for relational database management systems at scale that require high availability and HTAP.
C) Cloud Spanner is good for configuring replications and applying updates.
D) Cloud Spanner is good for object database management at scale that requires the capacity to process millions of objects in near real time.
A) Relational database management at scale that requires high availability and HTAP.
B) Flat data and databases with lots of read-write actions.
C) Highly structured databases or transactional databases.
(D) Organizations with non-relational data that want to reduce their operations burden with an enterprise-grade database.
21 – Related to ease of use, organizations can focus on their app, not their infrastructure, because Cloud Spanner:
A) Distributes organizations’ load-balanced resources in single or multiple regions around the globe, close to their users, to help them meet high-availability requirements.
(B) Eliminates complex database tasks so there is no need to engineer a complex replication or backup infrastructure.
C) Provides a layer of logic that organizations can write code in order to access other services.
D) Reduces network latency, offloads some work from the origin server, and reduces serving costs.
(A) Cloud Datastore is aligned to non-relational database requirements and is good for heavy read and write, events, and analytical data.
B) Cloud Datastore is a proven production system, serving organizations for 10 years.
C) Cloud Datastore is a fully managed NoSQL document database that scales from zero to global scale without configuration or downtime.
D) Cloud Datastore is ideal for rapid and flexible web and mobile development.
23 – Connecting to Cloud SQL databases looks the same as connecting to a MySQL or PostgreSQL database by using:
A) Non-traditional transforms and standard tools like Hadoop.
(B) Standard connectors and standard tools like MySQL workbench.
C) Standard containers and standard tools like BigQuery.
D) Non-traditional connectors and standard tools like PostgreSQL BETA
(A) Offline transfers
B) Topline transfers
C) Manual transfers
D) Hardline transfers
A) Data transfer options reduce risk by providing a better understanding of what is happening to allow for greater visibility.
B) Data transfer options run clusters ephemerally; in other words, only when needed.
(C) Data transfer options lead to many other GCP products and solutions that fit an organization’s needs.
D) Data transfer options lower warehousing costs and augment existing warehouses.
26 – Organizations considering Cloud Spanner often find ACID transactions valuable. What are ACID transactions?
A) Automatic, Constant Infrastructure, Decentralized
B) Autonomous, Centralized, Independent, Dependent
C) Analog, Chronological, Intelligent, Database
(D) Atomic, Consistent, Isolated, Durable
27 – What is an example of a time-consuming task required to set up and run a database that organizations can hand off to Google when they choose to use Cloud SQL?
A) Migrating data between data centers.
B) Managing contractors.
C) Developing apps.
(D) Applying patches and updates.
A) Analyzes data to capture insights to be used for more informed decision making.
B) Scales up to handle massive computing loads quickly and efficiently.
C) Allows organizations to easily use MapReduce, Pig, Hive, and Spark to process data before storing it, for example, in Cloud Storage or BigQuery.
(D) Automates loading data into BigQuery from YouTube, AdWords, and DoubleClick.
29 – Cloud Spanner is:
A) A tool for developing and executing a wide range of data processing patterns on very large datasets.
B) A fully managed database service that makes it easy to set up, maintain, manage, and administer relational MySQL and PostgreSQL databases in the cloud.
(C) An enterprise-grade, globally distributed, and strongly consistent managed database service built for the cloud specifically to combine the benefits of relational database structure with non-relational horizontal scale.
D) A managed environment for deploying containerized apps.
30 – “High availability and durability via replications is just there: you don’t need to think about it or manage it. No scheduled downtime for upgrades, resizing or configuration changes.” Which of the following concerns is addressed by this Cloud Datastore value proposition?
B) Infrastructure costs
(A) Relational database
B) Non-relational database
C) Object database
D) Warehouse database
32 – With Cloud Spanner, if one region goes offline, data can still be served from another region. How does Cloud Spanner make this possible?
(A) Cloud Spanner uses synchronous replication within and across regions to achieve greater availability.
B) Cloud Spanner stores and serves an unlimited number of objects and up to 5 terabytes of object data for each.
C) Cloud Spanner captures up to a petabyte of data on one Transfer Appliance without impacting the outbound network.
D) Cloud Spanner automates loading data into BigQuery from YouTube, AdWords, and DoubleClick.
(A) Data center migration
(B) Decommission tape libraries and infrastructure
C) Virtual Private Cloud
D) Preferred locations
A) Cloud SQL Transfer Service
B) Hardline Transfer
C) Cloud Engine Transfer Service
(D) BigQuery Data Transfer Service
35 – What aspect of Cloud Datastore allows organizations to worry less about making changes to their underlying data structure as their application evolves?
A) The warehouse database with a proven production system.
(B) The schemaless document-oriented database with ACID transactions.
C) The object-oriented database with containerized applications.
D) The relational database with configuration and downtime.
GCP Big Data And Machine Learning Assessment Questions And Answers
1 – Cloud IoT is a set of fully managed and integrated services that allows organizations to easily and securely connect, manage, and collect data from devices across the globe at a large scale. Knowing this, what stage of big data processing does Cloud IoT belong in?
(A) Availability, security, and preferred locations
B) Customer 360 analysis and log analysis
C) Massively parallel databases and multiple data marts
D) Machine learning APIs and Tensorflow
(A) Ease of use and speed
B) Idle clusters and scaling inflexibility
C) Integration and customization
D) High PUC cores and GPUs
4 – Cloud Dataflow is a tool for developing and executing a wide range of data processing patterns on very large datasets. Which of these examples aligns with what Cloud Dataflow can do?
A) Process queries written in structured query language (SQL).
B) Scale without downtime.
(C) Perform the transformations in “extract, transform, and load (ETL).”
D) Develop apps faster and easier with cloud backend services.
5 – Cloud Dataflow is a fully managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness. Knowing this, where does Cloud Dataflow fit in the big data processing model?
A) Cloud Pub/Sub
B) Cloud Engine
D) Data Warehouse
A) Eliminates the need to buy, build, and operate computing hardware.
B) Getting queries answered rapidly over very large data sets.
(C) Accelerates development for batch and streaming data processing pipelines.
D) Allows for fast SQL queries on structured data.
8 – The Cloud Dataproc approach allows organizations to use Hadoop/Spark/Hive/Pig when needed. It takes on average only 90 seconds between the moment resources are requested and a job can be submitted. What makes this possible?
A) The absence of management and maintenance.
(B) The separation of storage and compute.
C) The configuration of jobs and workflows.
D) The use of queries and containers.
9 – BigQuery can bring in other Google products because within the common big data processing model, BigQuery is found in the ________ phases.
A) Ingest and Process
(B) Storage and Analyze
C) Apps and Devices
D) Ingest and Storage
10 – Google Cloud’s AI provides modern machine learning services, with ________ models and a service to generate your own __________ models.
A) scalable, batch
(B) pre-trained, tailored
C) storage, process
D) virtual machine, dataset
A) Predictive datasets
B) Market datasets
C) QA datasets
(D) Training datasets
A) Multiple data marts are inefficient: they are complex and costly, and they make data difficult to use.
B) Organizations that want to take advantage of machine learning need to centralize their data with a managed data store that can consolidate structured and semi-structured data.
(C) Accepting that most devices can theoretically be connected to a network, building and managing such networks in a global, secure way—and then getting data out of them for analysis—is complex and difficult for organizations.
D) Organizations find it difficult to stay ahead when they continuously have to accommodate new data sources and more data without sacrificing efficiency.
(A) Ease of use and implementation
D) Reduces OPEX
14 – Which statement best describes where Cloud Dataproc falls on the big data processing model and the role it plays?
A) Cloud Dataproc allows organizations to scale data storage and ensures accessibility without compromising security.
B) Cloud Dataproc allows organizations to transform and enrich data in stream and batch modes.
(C) Cloud Dataproc allows organizations to easily use MapReduce, Pig, Hive, and Spark to process data before storing it, and it helps organizations interactively analyze data with Spark and Hive.
D) Cloud Dataproc allows organizations to ingest event streams from anywhere, at any scale, for simple, reliable, real-time stream analytics.
15 – A query is how you retrieve information from a database, so which of these paths demonstrates the journey of a query?
(A) Query > Database > Table with Data
B) Query > Table with Data > Database
C) Table with Data > Database > Query
D) Table with Data > Query > Database
16 – Which of these statements best describes the kinds of transforms a Cloud Dataflow pipeline can do?
A) Cloud Dataflow takes a query and runs information from the database through it to produce tables of data organized according to the requirements of the original query.
(B) Cloud Dataflow reads data in and can apply filtering, grouping, comparing, joining, or aggregation
C) Cloud Dataflow relies on a large database to store and analyze data processing pipelines, performing transforms resulting in predictive analytics that can be leveraged to optimize business decisions.
D) Cloud Dataflow relies on training data to enable machine learning that can then read multiple streams of data and perform transforms that produce resulting output data.
17 – For organizations that want a large-scale machine learning service, select the value ML provides.
(A) Cloud Machine Learning Engine makes it easy to build sophisticated, large-scale machine learning models across a broad set of scenarios.
B) Cloud Video Intelligence API makes videos searchable and discoverable by extracting metadata, identifying key nouns, and annotating the content of the video.
C) Cloud Translation API provides a simple programmatic interface for translating an arbitrary string into any supported language.
D) Cloud Job Discovery provides a highly intuitive job search that anticipates what job seekers are looking for and surfaces targeted recommendations that help them discover new opportunities.
(A) Cloud Dataproc runs clusters ephemerally; in other words, only when needed.
B) Cloud Dataproc runs clusters indefinitely, cutting down on wasted time typically spent on spinning up resources.
C) Cloud Dataproc charges at a per-minute rate for each cluster, reducing costs.
D) Cloud Dataproc attaches storage or hard drives to each node of the cluster.
A) BigQuery isolates data for machine learning.
B) BigQuery connects globally distributed industrial devices into a single network that can be managed efficiently.
C) BigQuery lets data analysts run data processsing pipelines to do transforms on incoming streaming data.
(D) BigQuery improves analytics, lowers warehousing costs, and includes connectivity to other GCP products.
(A) “I need access to near real-time reports, even if the data is speculative or sampled.”
B) “I need to know what customers are doing right now, and I need to find out using my existing Hadoop tools.”
C) “I need to transfer my data from my on-premises solutions to the cloud.”
D) “I wish I could run queries to organize my batch data.”
21 – An organization’s analysts use Spark Shell. However, their IT department is concerned about the increase in usage and how to scale their cluster, which is running in Standalone mode. How does Cloud Dataproc help?
A) Cloud Dataproc consolidates data marts into datasets and provides the ability to simply manage all datasets.
B) Cloud Dataproc can act as a landing zone for log data at a low cost.
(C) Cloud Dataproc supports Spark and can create clusters that scale for speed and mitigate any single point of failure.
D) Cloud Dataproc enables you to convert audio to text by applying neural network models in an easy-to-use API.
22 – BigQuery has the ability to scale seamlessly; what is another benefit when it comes to infrastructure?
(A) Almost NoOps, with downtime-free upgrades and maintenance
B) ZeroOps, with governance or maintenance required
C) No queries
D) Empty space storage
A) Queries, machine learning, and compute
B) VMs, network, and Non-SQL
(C) Availability, throughput, and latency
D) Sources, sinks, and transforms
(A) Is focused on enabling computers to recognize patterns in data—without humans telling the computer how to recognize the patterns.
B) Is how you retrieve information from a database.
C) Is a service to help capture data and rapidly pass massive numbers of messages between other big data tools.
D) Is a tool for developing and executing a wide range of data processing patterns on very large datasets.
25 – Which of these statements about the Publisher-Subscriber pattern utilized by Cloud Pub/Sub is TRUE?
A) Publisher applications can send messages to a subscriber.
(B) Subscriber applications can subscribe to a topic to receive the message when the subscriber is ready.
C) Publisher applications can receive messages from a topic.
D) Subscriber applications can send messages on a topic directly to publisher applications.
(A) Cloud Pub/Sub helps capture data and rapidly pass massive numbers of messages securely between other Google Cloud Platform big data tools and other software applications.
B) Cloud Pub/Sub offers a solution for analyzing big data and can open the door for other Google Cloud Platform big data tools.
C) Cloud Pub/Sub allows organizations to access their data anywhere, anytime as an innovative storage solution in the cloud, acting as a repository of data collected by other Google Cloud Platform big data tools.
D) Cloud Pub/Sub takes the existing data processing pipeline and processes it alongside an incoming stream of input data, performs transforms on that data to gain useful or actionable insights, and produces resulting output data.
27 – How does Cloud IoT help organizations unlock business insights in real time from data across globally dispersed devices?
(A) It connects globally distributed industrial devices into a single network that can be managed efficiently and serves as a new data source for an organization’s analytic systems to support improved operational efficiency.
B) It has a deep interoperability with business intelligence (BI) tools, allowing it to connect multiple devices around the globe through the tools themselves.
C) It is fully managed, with downtime-free upgrades and maintenance and seamless scaling, and it provides the benefits of operating on almost NoOps.
D) It uses the Spark Machine Learning Libraries (MLlib) to run classification algorithms on very large datasets, relying on cloud-based machines where Spark can be installed and customized.
(A) Cloud IoT enables growth through a better user experience that can increase usage and adoption of a product.
B) Cloud IoT facilitates machine learning with actionable insights by processing and analyzing data in real time.
C) Cloud IoT provides compute power across the globe at nearline locations.
D) Cloud IoT scales with big data workloads so that organizations can collect more data from more devices.
(A) Reduces risk
B) Massively parallel databases
(C) Optimizes cost
30 – Within the big data processing model, which description defines where Cloud Pub/Sub falls and the role it plays?
A) Cloud Pub/Sub stores data and ensures accessibility without compromising security.
B) Cloud Pub/Sub analyzes data to capture insights to be used for more informed decision making.
C) Cloud Pub/Sub processes queries, running them against a database of data to produce tables of the results.
(D) Cloud Pub/Sub ingests event streams from anywhere, at any scale, for simple, reliable, real-time stream analytics.
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