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云计算和大数据哪个更难(大数据和云计算哪个更有前景一些)

云计算
2023-12-23 11:01:27
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Is big data cloud computing easy to learn?

The technical thresholds for big data and cloud computing majors are very high, and the content is very high. Of course, it is not something that can be easily learned by just casual people.

What is the difference between big data and cloud computing, which one is better to learn

1. The definition of big data
The definition given by the famous McKinsey Global Institute is: a A data collection that is so large that its acquisition, storage, management, and analysis greatly exceed the capabilities of traditional database software tools. It has four major characteristics: massive data scale, rapid data flow, diverse data types, and low value density.
The definition given by research organization Gartner is that "big data" requires new processing models to have stronger decision-making power, insight discovery and process optimization capabilities to adapt to massive volume, high growth rate and diversification. information assets.
Big data refers to a collection of data that cannot be captured, managed and processed within a certain time range using conventional software tools. It requires new processing models to have stronger decision-making power and insight discovery. massive, high growth rate and diversified information assets with strong capabilities and process optimization capabilities.
The strategic significance of big data technology lies not in mastering huge data information, but in professional processing of these meaningful data. In other words, if big data is compared to an industry, then the key to making this industry profitable is to improve the "processing capabilities" of data and achieve the "value-added" of data through "processing".
2. Definition of cloud computing
The National Institute of Standards and Technology (NIST) defines cloud computing as a pay-per-use model that provides Available, convenient, on-demand network access into a configurable shared pool of computing resources (resources include networks, servers, storage, application software, and services) that can be quickly provided with little management effort , or minimal interaction with service providers.
Cloud computing (cloud computing) is the addition, use and delivery model of Internet-based related services, which usually involves providing dynamic, easily scalable and often virtualized resources through the Internet.
To put it simply: Cloud computing is the virtualization of hardware resources, while big data is the efficient processing of massive data. Although this explanation is not entirely appropriate, it can help people who don't understand the two names quickly understand the difference. Of course, if the explanation is more vivid, cloud computing is equivalent to our computers and operating systems, which virtualize a large number of hardware resources and then allocate them for use.
When in Xuanzhou District, you can choose according to your personal preferences and difficulty level (big data is slightly more complicated than cloud computing)

Which one is better to learn, big data or cloud computing? What are the prospects?

At present, the demand for big data and cloud computing talents in the entire IT industry is still relatively large. In recent years, the employment situation of graduate students in related fields is still relatively good. On the one hand, the job level is relatively high. On the other hand, the salary and benefits are also quite considerable, and the salary and benefits are showing an increasing trend year by year.

The demand for talents in the field of big data mainly revolves around the industrial chain of big data, involving data collection, organization, storage, security, analysis, presentation and application. The positions are mostly concentrated in big data platform research and development, big data Several positions include data application development, big data analysis, and big data operation and maintenance.

The application of cloud computing is currently undergoing development from IaaS to PaaS and SaaS, and the user distribution is gradually beginning to transition from Internet enterprises to traditional enterprises. The future market space is still very large.

Big data and cloud computing each have different concerns, but in terms of technical architecture, they are both based on distributed storage and distributed computing, so the connection between the two is relatively close.

Is big data cloud computing easy to learn?

Big data and cloud computing are actually not difficult to learn. Learning cloud computing and big data requires basic knowledge of java, linux, mysql, python, etc. Generally, you can find a job after 4 to 5 months of training.
The core idea of cloud computing is to uniformly manage and schedule a large number of computing resources connected by the network to form a computing resource pool to provide on-demand services to users. The basic principle of cloud computing is to complete the target tasks by distributing the calculations on a large number of distributed computers rather than on local computers or remote servers. Enterprise data centers will operate more like the Internet. This enables enterprises to switch resources to needed applications and access computers and storage systems on demand.
The so-called big data is composed of many small data. We ourselves are a piece of data, such as our communication information, our route information, our web browsing information, etc., they are all living data. , and it is this precise data that constitutes the big data we call it.

Which one is better, cloud computing or big data?

From a theoretical point of view, big data and cloud computing belong to different levels. Cloud computing studies computing problems, big data studies huge data processing problems, and huge data processing problems. Mass data processing still belongs to the research scope of computing problems. Therefore, from this perspective, big data is a subfield of cloud computing. From an application perspective, big data is one of the application cases of cloud computing, and cloud computing is one of the application cases of cloud computing. One of the data implementation tools.

Big data and cloud computing are both different and related. However, in reality, in order to obtain good efficiency and quality when processing big data, cloud computing technology is often used. Therefore, big data and cloud computing They often appear in front of people at the same time, causing people's confusion.

Big data technology is a new generation of technology and architecture that uses low-cost, fast collection, processing and analysis technology to extract value from various ultra-large-scale data. Big data technology continues to emerge and develop, making it easier, cheaper and faster for us to process massive amounts of data. It has become a good assistant in utilizing data and can even change the business models of many industries.

Big data (bigdata) is a collection of data: the amount of data is growing extremely fast, and it is impossible to collect, process, store and calculate it within a certain period of time using conventional data tools. Cloud computing is a super computing model based on the Internet. In a remote data center, thousands of computers and servers are connected to form a computer cloud. Therefore, cloud computing can even allow you to experience 10 trillion calculations per second. With such powerful computing power, you can simulate nuclear explosions, predict climate change and market development trends. Users access the data center through computers, laptops, mobile phones, etc., and perform calculations according to their own needs.

The employment prospects of cloud computing can also be understood in a sense as the services that cloud computing provides us. There is a certain degree of inevitability. In other words, what are the advantages of cloud computing for society and cloud computing users? It can also be understood that the advantage of cloud computing is the employment advantage of cloud computing.

Technically, the relationship between big data and cloud computing is as inseparable as the two sides of the same coin. Big data cannot be processed by a single computer and must use a distributed architecture. Its characteristic lies in distributed data mining of massive data. But it must rely on distributed processing, distributed database and cloud storage, and virtualization technology of cloud computing.

With the advent of the cloud era, big data (Bigdata) has also attracted more and more attention. The analyst team believes that big data (Bigdata) is usually used to describe the large amount of unstructured and semi-structured data created by a company, which would take too much time and money to download to a relational database for analysis. Big data analytics is often associated with cloud computing because real-time analysis of large data sets requires frameworks like MapReduce to distribute work to tens, hundreds, or even thousands of computers.

Big data requires special technologies to efficiently process large amounts of data over a tolerable amount of time. Technologies applicable to big data include massively parallel processing (MPP) databases, data mining, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems. Big data and cloud computing are required for future development trends, and their functions are powerful enough. Do you think the future of this industry is good? Of course it is, so learning quickly is the right start.