大数据与云计算之间的区别

1.大数据：
大数据是指规模巨大且随时间而迅速增加的数据。大数据包括结构化数据，非结构化数据以及半结构化数据。大数据无法在传统的数据管理工具中存储和处理，因此需要专门的大数据管理工具。它是指具有5 V的体积，速度，准确性，价值和种类信息资产的复杂和大型数据集。它包括数据存储，数据分析，数据挖掘和数据可视化。

生成大数据的来源示例包括社交媒体数据，电子商务数据，气象站数据，IoT传感器数据等。

大数据的特点：

• 各种大数据–结构化，非结构化和半结构化数据
• 大数据的速度–数据生成的速度
• 大数据量–正在生成的海量数据
• 大数据的价值–提取有用的信息并使之有价值
• 大数据的可变性–数据有时可能会显示出不一致之处。

大数据的优势：

• 节约成本
• 更好的决策
• 更好的销售见解
• 生产力提高
• 改善了客户服务。

大数据的缺点：

• 不兼容的工具
• 安全和隐私问题
• 需要文化变革
• 技术日新月异
• 特定的硬件需求。

2.云计算：
云计算是指互联网上计算资源的按需可用性。这些资源包括Internet上的服务器，存储，数据库，软件，分析，网络和智能，并且所有这些资源都可以根据客户的要求使用。在云计算中，客户必须按使用付费。它非常灵活，可以根据需要轻松扩展资源。无需物理购买任何IT资源，而是可以根据云供应商的要求来使用所有资源。云计算具有三种服务模型，即基础架构即服务(IaaS)，平台即服务(PaaS)和软件即服务(SaaS)。

提供云计算服务的云计算供应商的示例包括Amazon Web Service(AWS)，Microsoft Azure，Google Cloud Platform，IBM Cloud Services等。

云计算的特点：

• 按需可用性
• 可通过网络访问
• 弹性可伸缩性
• 随用随付模型
• 多租户和资源池。

云计算的优势：

• 备份和还原数据
• 改善协作
• 出色的可及性
• 维护成本低
• 按需自助服务。

云计算的缺点：

• 供应商锁定
• 有限的控制
• 安全问题
• 由于各种原因导致停机
• 需要良好的Internet连接。

大数据与云计算之间的区别：

S.No.	BIG DATA	CLOUD COMPUTING
01.	Big data refers to the data which is huge in size and also increasing rapidly with respect to time.	Cloud computing refers to the on demand availability of computing resources over internet.
02.	Big data includes structured data, unstructured data as well as semi-structured data.	Cloud Computing Services includes Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
03.	Volume of data, Velocity of data, Variety of data, Veracity of data, and Value of data are considered as the 5 most important characteristics of Big data.	On-Demand availability of IT resources, broad network access, resource pooling, elasticity and measured service are considered as the main characteristics of cloud computing.
04.	The purpose of big data is to organizing the large volume of data and extracting the useful information from it and using that information for the improvement of business.	The purpose of cloud computing is to store and process data in cloud or availing remote IT services without physically installing any IT resources.
05.	Distributed computing is used for analyzing the data and extracting the useful information.	Internet is used to get the cloud based services from different cloud vendors.
06.	Big data management allows centralized platform, provision for backup and recovery and low maintenance cost.	Cloud computing services are cost effective, scalable and robust.
07.	Some of the challenges of big data are variety of data, data storage and integration, data processing and resource management.	Some of the challenges of cloud computing are availability, transformation, security concern, charging model.
08.	Big data refers to huge volume of data, its management, and useful information extraction.	Cloud computing refers to remote IT resources and different internet service models.
09.	Big data is used to describe huge volume of data and information.	Cloud computing is used to store data and information on remote servers and also processing the data using remote infrastructure.
10.	Some of the sources where big data is generated includes social media data, e-commerce data, weather station data, IoT Sensor data etc.	Some of the cloud computing vendors who provides cloud computing services are Amazon Web Service (AWS), Microsoft Azure, Google Cloud Platform, IBM Cloud Services etc.