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1
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An organization has a new application, and user subscriptions are growing faster than on-premises infrastructure can handle. What benefit of the cloud might help them in this situation?
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- It's scalable, so the organization could shorten their infrastructure deployment time.
- It's secure, so the organization won't have to worry about the new subscribers data.
- It's cost effective, so the organization will no longer have to pay for computing once the app is in the cloud
- It provides physical access, so the organization can deploy servers faster.
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2
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As the world and business changes, organizations have to decide between embracing new technology and transforming, or keeping their technology and approaches the same. What risks might an organization face by not transforming as their market evolves?
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- Focusing on ‘how’ they operate can prevent organizations from seeing transformation opportunities
- Embracing new technology can cause organizations to overspend on innovation.
- Organizations risk losing market leadership if they spend too much time on digital transformation.
- Focusing on ‘why’ they operate can lead to inefficient use of resources and disruption.
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3
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An organization has made significant investments in their own infrastructure and has regulatory requirements for their data to be hosted on-premises. Which cloud implementation would best suit their needs?
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4
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Select the two capabilities that form the basis of a transformation cloud? Select two correct answers
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- Collaboration cloud ensures that the device a user connects with only works on the corporate network.
- A trusted cloud gives control of all resources to the user to ensure high availability at all times.
- Data cloud provides a unified solution to manage data across the entire data lifecycle
- Sustainable cloud ensures the costs of cloud resources are controlled to prevent budget overrun
- Open infrastructure gives the freedom to innovate by running applications in the place that makes the most sense.
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5
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What is the definition of digital transformation.
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- When an organization uses new digital technologies to create or modify technology infrastructure to focus on cost saving.
- When an organization uses new digital technologies to create or modify on-premises business processes
- When an organization uses new digital technologies to create or modify business processes, culture, and customer experiences
- When an organization uses new digital technologies to create or modify financial models for how a business is run
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6
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Which item describes a goal of an organization seeking digital transformation?
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- Reduce emissions by using faster networks in their on-premises workloads
- Break down data silos and generate real time insights.
- Ensure better security by decoupling teams and their data.
- Streamline their hardware procurement process to forecast at least a quarter into the future.
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7
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What is the benefit of implementing a transformation cloud that is based on open infrastructure?
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- Open source software makes it easier to patent proprietary software.
- On-premises software isn't open source, so cloud applications are more portable.
- Open standards make it easier to hire more developers
- Open source software reduces the chance of vendor lock-in.
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8
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What is seen as a limitation of on-premises infrastructure, when compared to cloud infrastructure?
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- Maintenance workers do not have physical access to the servers.
- The on-premises hardware procurement process can take a long time.
- The on-premises networking is more complicated
- Scaling processing is too difficult due to power consumption.
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9
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What is the cloud?
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- A Google product made up of on-premises IT infrastructure
- A metaphor for the networking capability of internet providers.
- A Google product for computing large amounts of data
- A metaphor for a network of data centers
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10
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Which network performance metric describes the amount of data a network can transfer in a given amount of time?
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11
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An organization wants to innovate using the latest technologies, but also has compliance needs that specify data must be stored in specific locations. Which cloud approach would best suit their needs?
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- On-premises infrastructure
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12
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An organization has shifted from a CapEx to OpEx based spending model. Which of these statements is true?
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- Hardware procurement is done by a centralized team
- They will only pay for what they use.
- They will only pay for what they forecast.
- Budgeting will only happen on an annual basis.
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13
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A financial services organization has bank branches in a number of countries, and has built an application that needs to run in different configurations based on the local regulations of each country. How can cloud infrastructure help achieve this goal?
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- Scalability of infrastructure to needs.
- Reliability of the infrastructure availability.
- Flexibility of infrastructure configuration.
- Total cost of ownership of the infrastructure
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14
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An organization wants to ensure they have redundancy of their resources so their application remains available in the event of a disaster. How can they ensure this happens?
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- By assigning a different IP address to each resource.
- Using the edge network to cache the whole application image in a backup.
- By putting resources in different zones.
- By putting resources in the Domain Name System (DNS)
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15
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Which option best describes a benefit of Infrastructure as a Service (IaaS)?
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- It's cost-effective, as all infrastructure costs are handled under a single monthly or annual subscription fee.
- It has low management overhead, as all administration and management tasks for data, servers, storage, and updates are handled by the cloud vendor.
- It reduces development time, as developers can go straight to coding instead of spending time setting up and maintaining a development environment.
- It’s efficient, as IaaS resources are available when needed and resources aren’t wasted by overbuilding capacity.
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16
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An organization wants to move their collaboration software to the cloud, but due to limited IT staff one of their main drivers is having low maintenance needs. Which cloud computing model would best suit their requirements?
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- Platform as a Service (PaaS)
- Infrastructure as a Service (IaaS)
- Software as a Service (SaaS)
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17
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In the cloud computing shared responsibility model, what types of content are customers always responsible for, regardless of the computing model chosen?
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- The customer is not responsible for any of the data in the cloud, as data management is the responsibility of the cloud provider who is hosting the data.
- The customer is responsible for securing anything that they create within the cloud, such as the configurations, access policies, and user data. That is the correct
- The customer is responsible for security of the operating system, software stack required to run their applications and any hardware, networks, and physical security.
- The customer is responsible for all infrastructure decisions, server configurations and database monitoring.
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18
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Which cloud computing service model offers a develop-and-deploy environment to build cloud applications?
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- Platform as a Service (PaaS)
- Software as a Service (SaaS)
- Function as a Service (FaaS)
- Infrastructure as a Service (IaaS)
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19
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Which represents the proprietary customer datasets that a business collects from customer or audience transactions and interactions?
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20
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Which is a repository designed to ingest, store, explore, process, and analyze any type or volume of raw data, regardless of the source?
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21
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New cloud tools make it possible to harness the potential of unstructured data. Which of these use cases best demonstrates this?
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- Analyzing social media posts to identify sentiment toward a brand
- Analyzing historical sales figures to predict future trends
- Creating visualizations from seasonal weather data
- Using GPS coordinates to power a ride-sharing app
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22
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Which step in the data value chain is where collected raw data is transformed into a form that’s ready to derive insights from?
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23
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What is Google Cloud’s modern and serverless data warehousing solution?
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24
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What is data governance?
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- The process of collecting and storing data for future use
- The process of deleting unnecessary data to save storage space
- The process of analyzing data to gain insights and make informed decisions
- The process of setting internal data policies and ensuring compliance with external standards
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25
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A solar energy company wants to analyze weather data to better understand the seasonal impact on their business. On which platform could they find free-to-use weather datasets?
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26
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An online retailer uses a smart analytics tool to ingest real-time customer behavior data to surface the best suggestions for particular users. How can machine learning guide this activity?
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- Machine learning can be used to make all users see the same product recommendations, regardless of their preferences or behavior.
- Through machine learning, with every click that the user makes, their website experience becomes increasingly personalized.
- Through machine learning, a user’s credit card transactions can be analyzed to determine regular purchases.
- Machine learning can help identify user behavior in real time, but cannot make personalized suggestions based on the data.
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27
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A car insurance company has a large database that stores customer details, including the vehicles they own and past claims. The structure of the database means that information is stored in tables, rows, and columns. What type of database is this?
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- A non-relational database
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28
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Which data type is highly organized and well-defined?
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- A hybrid of structured, semi-structured, and unstructured data
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29
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Data in the form of video, pictures, and audio recordings is well suited to object storage. Which product is best for storing this kind of data?
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30
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Which would be the best SQL-based storage option for a transactional workload that requires global scalability?
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31
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A data analyst for an online retailer must produce a sales report at the end of each quarter. Which Cloud Storage class should the retailer use for data accessed every 90 days?
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32
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Which is the best SQL-based storage option for a transactional workload that requires local or regional scalability?
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33
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BigQuery works in a multicloud environment. How do organizations benefit from this feature?
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- Data teams can eradicate data silos by analyzing data across multiple cloud providers.
- Security is more effective when BigQuery is run in on-premises environments.
- Multicloud support in BigQuery is only intended for use in disaster recovery scenarios.
- BigQuery lets organizations save costs by limiting the number of cloud providers they use.
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34
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Which Google Cloud product can be used to synchronize data across databases, storage systems, and applications?
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35
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Which strategy describes when databases are migrated from on-premises and private cloud environments to the same type of database hosted by a public cloud provider?
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- Managed database migration
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36
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What is Google's big data database service that powers many core Google services, including Google Search, Google Analytics, Google Maps Platform, and Gmail?
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37
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Which characteristic is true for all Cloud Storage classes?
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- Accessibility only within one region
- High latency and low durability
- Geo-redundancy if data is stored in a multi-region or dual-region
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38
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What are the two services that BigQuery provides?
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39
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What is Google Cloud’s distributed messaging service that can receive messages from various device streams such as gaming events, Internet of Things (IoT) devices, and application streams?
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40
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Streaming analytics is the processing and analyzing of data records continuously instead of in batches. Which option is a source of streaming data?
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41
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What does ETL stand for in the context of data processing?
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- Extract, transform, and load
- Enrichment, tagging, and labeling
- Enhanced transaction logic
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42
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Which statement is true about Dataflow?
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- It’s a messaging service for receiving messages from various device streams.
- It handles infrastructure setup and maintenance for processing pipelines.
- It’s a cloud-based data warehouse for storing and analyzing streaming and batch data.
- It allows easy data cleaning and transformation through visual tools and machine learning-based suggestions.
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43
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What feature of Looker makes it easy to integrate into existing workflows and share with multiple teams at an organization?
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- It supports over 60 different SQL databases.
- It creates easy to understand visualizations.
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44
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What Google Cloud business intelligence platform is designed to help individuals and teams analyze, visualize, and share data?
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45
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Which feature of Vertex AI lets users build and train end-to-end machine learning models by using a GUI (graphical user interface), without writing a line of code
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46
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An online retailer wants to help users find specific products faster on their website. One idea is to allow shoppers to upload an image of the product they’re looking to purchase. Which of Google’s pre-trained APIs could the retailer use to expand this functionality?
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47
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A large media company wants to improve how they moderate online content. Currently, they have a team of human moderators that review content for appropriateness, but are looking to leverage artificial intelligence to improve efficiency. Which of Google’s pre-trained APIs could they use to identify and remove inappropriate content from the media company's website and social media platforms.
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48
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Which Google Cloud AI solution is designed to help businesses automate document processing?
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49
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Which Google Cloud AI solution is designed to help businesses improve their customer service?
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50
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Google Cloud offers four options for building machine learning models. Which is best when a business wants to code their own machine learning environment, the training, and the deployment?
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51
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BigQuery ML is a machine learning service that lets users:
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- Build and evaluate machine learning models in BigQuery by using Python and Java.
- Export small amounts of data to spreadsheets or other applications.
- Build and evaluate machine learning models in BigQuery by using SQL.
- Seamlessly connect with a data science team to create an ML model.
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52
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What’s the name of Google’s application-specific integrated circuit (ASIC) that is used to accelerate machine learning workloads?
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- Central Processing Unit (CPU)
- Graphic Processing Unit (GPU)
- Tensor Processing Unit (TPU
- Vertex Processing Unit (VPU)
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53
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Which dimension for measuring data quality means that the data conforms to a set of predefined standards and definitions such as type and format?
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54
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Which use case demonstrates ML’s ability to process natural language?
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- Identifying the artist, title, or genre of a song to create playlists based on the user's listening habits.
- Segmenting images into different parts or regions to extract information, such as the text on a sign.
- Detecting people and objects in surveillance footage to use as evidence in criminal cases.
- Identifying the topic and sentiment of customer email messages so that they can be routed to the relevant department.
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55
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Which option refers to the use of technologies to build machines and computers that can mimic cognitive functions associated with human intelligence?
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- Natural language processing
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56
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What does the consistency dimension refer to when data quality is being measured?
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- Whether the data is up-to-date and reflects the current state of the phenomenon that is being modeled.
- Whether all the required information is present.
- Whether a dataset is free from duplicate values that could prevent an ML model from learning accurately.
- Whether the data is uniform and doesn’t contain any contradictory information.
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57
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You’re watching a video on YouTube and are shown a list of videos that YouTube thinks you are interested in. What ML solution powers this feature?
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- Personalized recommendations
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58
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Google applies generative AI to products like Google Workspace, but what is generative AI?
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- A type of artificial intelligence that can make decisions and take actions.
- A type of artificial intelligence that can create and sustain its own consciousness.
- A type of artificial intelligence that can understand and respond to human emotions
- A type of artificial intelligence that can produce new content, including text, images, audio, and synthetic data.
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59
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Which technology relies on models to analyze large amounts of data, learn from the insights, and then make predictions and informed decisions?
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- Natural language processing
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60
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How do data analytics and business intelligence differ from AI and ML?
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- Data analytics and business intelligence identify trends from historical data, whereas AI and ML use data to make decisions for future business.
- Data analytics and business intelligence are used only in small businesses, whereas AI and ML are used exclusively by large corporations.
- Data analytics and business intelligence use automated decision-making processes, whereas AI and ML require human intervention and interpretation of data.
- Data analytics and business intelligence involve advanced algorithms for predicting future trends, whereas AI and ML focus on processing historical data.
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61
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Google's AI principles are a set of guiding values that help develop and use artificial intelligence responsibly. Which of these is one of Google’s AI principles?
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- AI should create or reinforce unfair bias.
- AI should be socially beneficial.
- AI should be accountable to other machines.
- AI should be made available for any use.
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62
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Artificial intelligence is best suited for replacing or simplifying rule-based systems. Which is an example of this in action?
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- Using AI to replace a human decision-maker in complex situations, such as those involving life-or-death choices.
- Using a reinforcement learning algorithm to train autonomous drones for package delivery.
- Implementing AI to develop a new product or service that has never been seen before.
- Training a machine learning model to predict a search result ranking.
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