32 Questions
What does the tool provide for preparing data for visualization?
World-class SQL IDE
Which feature empowers data analysts to define custom dimensions and metrics quickly?
Lightweight semantic layer
What is the primary purpose of the API provided by the tool?
Programmatic customization
The tool provides a code-free visualization builder.
True
The tool does not support in-memory asynchronous caching and queries.
False
The API provided by the tool is not designed for programmatic customization.
False
Match the following features with their descriptions:
Intuitive interface for visualizing datasets and crafting interactive dashboards = User-friendly interface for creating visual representations of data Wide array of beautiful visualizations to showcase your metadata = Diverse collection of visually appealing displays to present metadata Seamless, in-memory asynchronous caching and queries = Effortless, real-time caching and data retrieval Cloud-native architecture designed from the ground up for scale = Architecture built for scalability and optimized for cloud environments
Match the following capabilities with their descriptions:
Code-free visualization builder to extract and present datasets = Tool for creating visual representations of data without writing code World-class SQL IDE for preparing data for visualization, including a rich metadata browser = High-quality SQL Integrated Development Environment for data preparation and metadata exploration Lightweight semantic layer which empowers data analysts to quickly define custom dimensions and metrics = Efficient layer enabling rapid creation of custom data metrics and dimensions An API for programmatic customization = Interface allowing programmatic customization of the tool's functionality
Match the following features with their purposes:
API for programmatic customization = Customizing tool's functionality through programming A wide array of beautiful visualizations to showcase your metadata = Displaying diverse visually appealing representations of metadata Seamless, in-memory asynchronous caching and queries = Efficient real-time caching and data retrieval Cloud-native architecture designed from the ground up for scale = Architecture optimized for scalability in cloud environments
What is the primary purpose of a cloud-native architecture?
To utilize cloud services for application development
Which principle is commonly used to break down cloud-native applications into small, independent services?
Microservices
What technology is often used to deploy cloud-native applications in isolation?
Docker containers
Which practice automates the building, testing, and deployment of software in cloud-native architectures?
Continuous integration and continuous delivery (CI/CD)
What is a key benefit of cloud-native applications in terms of scalability?
Highly scalable and easily adaptable to changing demand
In terms of reliability, cloud-native applications are typically designed to be:
Designed to be reliable
What aspect do cloud-native applications emphasize in terms of resilience?
Quick recovery from failures
Which architecture methodology utilizes cloud services for building and running applications?
'Cloud-native' architecture
What technology allows applications to be packaged and run in isolation within cloud-native architectures?
'Lightweight' containerization technology
Which set of practices automates the building, testing, and deployment of software within cloud-native architectures?
Continuous integration and continuous delivery (CI/CD)
Cloud-native architectures typically emphasize reliability over scalability.
False
Containers are a heavy virtualization technology that allows applications to be packaged and run in isolation.
False
CI/CD is often used to deploy cloud-native applications, but it does not automate the building and testing of software.
False
Cloud-native architectures do not offer any benefits in terms of scalability.
False
Microservices are often used to deploy cloud-native applications as large, dependent services.
False
Cloud-native applications are typically designed to be unreliable, meaning they cannot continue to operate in the event of failures.
False
Cloud-native architectures do not utilize cloud services such as elastic computing, storage, and networking to build and run applications.
False
Resilience is not a key focus in cloud-native architectures; they do not aim to recover from failures quickly.
False
Containers are never used to deploy cloud-native applications within cloud-native architectures.
False
CI/CD does not automate the building, testing, and deployment of software within cloud-native architectures.
False
Match the following cloud-native architecture principles with their descriptions:
Microservices = Cloud-native applications are typically broken down into small, independent services that can be developed, deployed, and scaled independently. Containers = Containers are a lightweight virtualization technology that allows applications to be packaged and run in isolation. Continuous integration and continuous delivery (CI/CD) = CI/CD is a set of practices that automates the building, testing, and deployment of software. Scalability = Cloud-native applications are typically highly scalable, meaning that they can be easily scaled up or down to meet changing demand.
Match the following benefits of cloud-native architectures with their descriptions:
Reliability = Cloud-native applications are typically designed to be reliable, meaning that they can continue to operate even in the event of failures. Resilience = Cloud-native applications are typically designed to be resilient, meaning that they can recover from failures quickly. Scalability = Cloud-native applications are typically highly scalable, meaning that they can be easily scaled up or down to meet changing demand. Microservices = Cloud-native applications are typically broken down into small, independent services that can be developed, deployed, and scaled independently.
Match the following cloud-native architecture technologies with their primary usage:
Containers = To package and run applications in isolation within cloud-native architectures. Microservices = To break down cloud-native applications into small, independent services. Continuous integration and continuous delivery (CI/CD) = To automate the building, testing, and deployment of software within cloud-native architectures. Scalability = To easily scale cloud-native applications up or down to meet changing demand.
Explore the features of intuitive data visualization and analysis tools, including an interface for crafting interactive dashboards, a variety of beautiful visualizations, code-free visualization builder, SQL IDE for data preparation, and more.
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