Interpretation of the definition, operation and analysis of big data

With the rapid development of information intelligence technologies such as the Internet of Things, cloud computing, and mobile Internet, big data has penetrated into every industry and business field today.

Today we talk about the concept and theory of big data. First of all, we must understand big data. Nowadays, people are talking about big data, and they feel that they are not familiar with big data. Now Alibaba, Tencent and other big companies are developing towards big data. The era of big data is a symbol of the era and a normal state that changes people's lives. Big data is not only an era of data analysis, but also a kind of data analysis that is convenient for people to choose. For example, for the products we saw today, big data will analyze your needs and push you better products, giving you more choices. It embodies an intelligence, convenience, and efficiency.

The literal understanding of big data refers to a data set whose size exceeds the ability of commonly used software tools to collect, manage and process data during runtime; big data is the current storage mode and capacity, computing mode and capacity cannot meet storage and Dealing with the relative concepts arising from the scale of existing data sets.

Big data must first be preprocessed during operation

It mainly completes operations such as discrimination, capture, and classification of received data.

(1) Identification: Identify products or data by receiving input requirements.

(2) Grabbing: As the acquired data may have multiple structures and types, the process of data extraction can help us transform these complex data into a single or easy-to-process configuration to achieve the purpose of rapid analysis and processing.

(3) Classification: Not all the data received by big data is valuable. Some data is something we don’t care about, and some data is completely wrong interference items. Therefore, the data should be filtered to extract more information. valid data.

First of all, if we want to understand big data systematically, we analyze it from the three most basic aspects.

The first is theory. Theory is the necessary way of cognition and the baseline for being widely recognized and disseminated. I will understand the industry's overall description and qualitativeness of big data from the definition of big data; from the discussion of the value of big data to in-depth analysis of the preciousness of big data; from the present and future of big data to understand the development trend of big data ; Examine the long-term game between people and data from the special and important perspective of big data privacy.

The second is technology, which is the means and the cornerstone of the advancement of the value of big data. I will illustrate the entire process of big data from collection, processing, storage to the formation of results from the development of cloud computing, distributed processing technology, storage technology, and perception technology.

The third is practice. Practice is the ultimate value of big data. I will describe the beautiful scene of big data and the blueprint to be realized from four aspects: big data of the Internet, big data of the government, big data of enterprises, and big data of individuals.

Regarding the enterprise data market, the development of business naturally relies on a large amount of data analysis to make decisions. For enterprise users, it is more relevant to decision-making needs, as well as corporate marketing needs.

For end consumers, the demand for big data is mainly reflected in the ability to search for information on demand, and provide friendly and credible information recommendations, followed by the provision of high-level services.

Big data optimizes resource allocation, big data improves decision-making capabilities, and a harmonious society driven by wisdom.

1. Big data optimizes resource allocation

Individuals can choose their own work, comfortable living conditions, and convenient travel methods based on various data;

Companies choose their own production experience directions based on various types of data, fine-tuned division of labor, tailor-made products for empty tenants, and maximize benefits.

2. Big data improves decision-making ability

The characteristics of this decision-making based on big data are:

Quantitative changes to qualitative changes. As data is extensively mined, the completeness of the information on which decision-making is based is getting higher and higher, rational decision-making with information is rapidly expanding, and blind decision-making is shrinking sharply;

The content of decision-making technology and knowledge is greatly improved;

Big data decision-making has spawned many major solutions that were unimaginable in the past.

Macro level: Big data enables economic decision-making departments to more sensitively grasp economic trends, formulate and implement scientific economic policies;

At the micro level: Big data can improve the level and efficiency of business decision-making, promote innovation, and bring value to companies and industries.

3. Harmonious society driven by wisdom, big data brings a new way of life

City management is a complex subject, and smart city construction is a complex system engineering. The construction of a smart city should focus on the whole of the three spaces at the same time. Big data will provide data support for the construction of smart cities.

With the rapid progress of smart city construction, big data applications have entered the realm of substantial borrowing, which has effectively stimulated the big data market demand and promoted the development of the local big data industry. The application value of big data in various fields has begun to show.

Information is a description of people and things in the world. We generate information all the time and obtain information through our senses, but it is more abstract than data. Information is the law hidden behind the data. Although different people have different preferences, personalities, births, where they have been, and so on, there are always points that intersect. We discover, categorize this information, and compose data.

From data to information to the knowledge we have, we must clearly know the scope of the concept, which will help us learn big data in the future. From data to information, different processing methods are involved, which involves machine learning processing technology. Different technical processing may result in different information. From information to knowledge, a person's ability to generalize and summarize is more reflected, which directly leads to the application scenarios and use value of later data. The last to reach the highest level is to have wisdom.