What is the relationship between cloud computing and big data?

Cloud computing is the growth, usage, and delivery of Internet-based services, typically involving the provision of dynamically scalable and often virtualized resources over the Internet. Cloud is a metaphor for the network, the Internet. In the past, clouds were often used to represent telecommunication networks in diagrams, and later they were also used to represent the abstraction of the Internet and the underlying infrastructure.

Cloud computing in the narrow sense refers to the delivery and use mode of IT infrastructure, which refers to obtaining the required resources in an on-demand and easily scalable manner through the network. Cloud computing in a broad sense refers to the delivery and consumption model of services, which refers to obtaining the required services in an on-demand and easily scalable manner through the network. Such services can be IT and software, Internet-related, or other services. It means that computing power can also be circulated as a commodity through the Internet.

Big data, or massive data, refers to the amount of data involved that is so large that it cannot be captured, managed, processed, and organized into more positive business decisions through current mainstream software tools in a reasonable time. The 4V characteristics of big data: volume, velocity, variety, and veracity.

From a technical point of view, the relationship between big data and cloud computing is as inseparable as the heads and tails of the same coin. Big data cannot necessarily be processed by a single computer, and a distributed computing architecture must be adopted. It is characterized by the mining of massive amounts of data, but it must rely on the distributed processing, distributed database, cloud storage and virtualization technology of cloud computing.

Big data management, distributed file systems, such as Hadoop and MapReduce, data segmentation and access execution; At the same time, SQL support, represented by Hive+Hadoop, and the use of cloud computing to build a next-generation data warehouse on big data technology have become hot topics. From the perspective of system requirements, the architecture of big data poses new challenges to the system:

1. Higher integration. A standard chassis maximizes specific tasks.

2. The configuration is more reasonable and faster. The balanced design of storage, controller, IO channel, memory, CPU, and network is optimized for data warehouse access, which is more than an order of magnitude higher than that of traditional similar platforms.

3. The overall energy consumption is lower. Lowest energy consumption for the same computing task.

4. The system is more stable and reliable. It can eliminate various single points of failure and unify the quality and standards of a component and device.

5. Low management and maintenance costs. The general management of the data collection is fully integrated.

6. Planable and predictable system expansion and upgrade roadmap.

The essence of big world potato data is to use computer clusters to process large amounts of data, and the technical focus of big data is how to distribute data to different computers for storage and processing.

The essence of cloud computing is to provide computing power to users as a smaller-grained service, using and paying for it on demand, which reflects:

Affordability: No need to buy the entire server.

Speed: Use it immediately, no need for a long time to purchase, install and deploy.

Automation, no need to use people to complete the allocation and deployment of resources, through the API can automatically create cloud hosts and other services.

In terms of the relationship between big data and cloud computing, both focus on resource scheduling.

Big data processing can be based on cloud computing platforms.; Big data processing can also be used as a cloud computing service, its essence is data processing technology, there are many tools used, and the cost performance is relatively simple, such as tableau, finebi, etc.

Generally speaking, when talking about cloud computing, when talking about big data artificial intelligence, improving data, and when talking about artificial intelligence, when talking about artificial intelligence, when talking about cloud computing. The three complement each other and are inseparable. What is the relationship between cloud computing and big data?

1. Cloud computing is to provide global users with computing power and storage services through the Internet, and provide hardware foundation for Internet information processing.

2. Big data uses more and more mature cloud computing technology to obtain valuable information from the vast network information ocean for information summary, search and integration, and provides a software foundation for network information processing.

3. Their relationship:

Cloud computing is the foundation, and without cloud computing, the storage and computing of big data cannot be realized.

Big data is an application, and without big data, cloud computing lacks purpose and value.

4. Both require the participation of artificial intelligence, which is the commercial application of the Internet information system in an orderly manner. This is the real export of cloud computing and big data.

5. Where does the intelligence in business intelligence come from?

One way to do this is to use big data as a tool to process large amounts of data, draw relevant conclusions, and get answers from these correlations, so big data is a tool for business intelligence. Big data needs to analyze a large amount of data, which requires the computing power and processing power of the system to be very high, the traditional way needs supercomputer processing, but the computing power is idle, busy when the problem is insufficient, the elastic expansion and horizontal expansion mode of cloud computing is suitable for the needs of computing power.