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Cloud Computing

Using remote servers to store and process data

5 minutes 5 Questions

Cloud Computing provides data scientists powerful, scalable infrastructure for handling big data workloads. It delivers computing resources (storage, processing power, analytics tools) over the internet on a pay-as-you-go model, eliminating the need for organizations to build and maintain expensive…

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Big Data Scientist - Cloud Computing Example Questions

Test your knowledge of Cloud Computing

Question 1

What is multi-tenancy in cloud computing?

Multi-tenancy is a cloud computing model in which a single instance of a software application serves multiple customers or tenants, with each tenant securely partitioned from the others to ensure maximum security and privacy. Multi-tenancy is a cloud computing model that is primarily useful for small businesses or startups, but which is not well-suited for larger enterprises or complex applications. Multi-tenancy is a cloud computing model that is not scalable and cannot be used to serve large numbers of customers or tenants. Multi-tenancy is a cloud computing model in which each customer or tenant is allocated their own discrete instance of a software application, leading to inefficient use of resources and increased costs. Multi-tenancy is a cloud computing model that is not widely adopted or used in the industry, and is mostly a theoretical concept rather than a practical tool. Multi-tenancy is a cloud computing model in which each customer or tenant shares the same set of resources, leading to security and privacy concerns.

Correct Answer: Multi-tenancy is a cloud computing model in which a single instance of a software application serves multiple customers or tenants, with each tenant securely partitioned from the others to ensure maximum security and privacy.

Multi-tenancy is an important cloud computing model that allows businesses to share resources and realize economies of scale while also maintaining high levels of security and privacy. By partitioning each tenant from the others, businesses can ensure that sensitive data is kept private and that there is no risk of data leakage between tenants. Additionally, because resources are shared across many tenants, businesses can enjoy cost savings and improved performance compared to traditional on-premise solutions.

Question 2

What is a data warehouse in big data processing?

A distributed file system for unstructured data processing A web service for querying social media data A centralized repository for structured data from multiple sources A database engine for transactional data processing A cloud service for backing up data to a remote location A tool for streaming real-time data from IoT devices

Correct Answer: A centralized repository for structured data from multiple sources

A data warehouse is a centralized repository for structured data from multiple sources, such as databases, ERP systems, CRM systems, and so on. It is designed to support complex queries, data analysis, and reporting, and can store historical and aggregated data. The data is organized according to a schema and is optimized for read-intensive workloads. In contrast, a data lake is a repository for unstructured, semi-structured or structured data that allows fast ingest and processing of large volumes of data.

Question 3

What is the main drawback of using cloud computing compared to on-premise computing?

Less control over infrastructure Less customization options Performance issues Higher costs Data transfer challenges Security concerns

Correct Answer: Less control over infrastructure

When using cloud computing, the infrastructure is managed by a third party, leaving the user with less control over their environment compared to on-premise computing.

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