Big Data

Big data, or huge amount of data, refers to information that is too large to be retrieved, managed, processed, and sorted out in a reasonable time through mainstream software tools to help enterprises make more active business decisions. 5V features of big data (proposed by IBM): Volume, Velocity, Variety, Value, Veracity.

Definition of Big Data
Gartner, a "big data" research institution, has given such a definition. "Big data" requires a new processing mode to have stronger decision-making power, insight and discovery power and process optimization ability to adapt to massive, high growth rate and diversified information assets. The strategic significance of big data technology is not to master huge data information, but to professionally process these meaningful data. In other words, if big data is compared to an industry, the key to the profitability of this industry lies in improving the "processing capacity" of data and realizing the "value-added" of data through "processing".

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

Structure of Big Data
Big data includes structured, semi-structured and unstructured data. Unstructured data has increasingly become the main part of data. According to IDC's survey report, 80% of the data in enterprises are unstructured data, and these data increase by 60% every year. Big data is just an appearance or feature of the Internet at its current stage of development. There is no need to mythologize it or keep in awe of it. Against the backdrop of technological innovation represented by cloud computing, these data that originally seemed difficult to collect and use began to be easily used. Through continuous innovation in all walks of life, big data will gradually create more value for mankind.

Significance of Big Data
(1) Enterprises that provide products or services to a large number of consumers can use big data for precision marketing;

(2) Small, medium and micro enterprises with a small and beautiful model can use big data for service transformation;

(3) Traditional enterprises that have to transform under the pressure of the Internet need to keep pace with the times and make full use of the value of big data.

Characteristics of Big Data
Volume: the size of the data determines the value and potential information of the data under consideration;

Variety: the diversity of data types;

Velocity: refers to the speed at which data is obtained;

Variability: hinders the process of processing and effectively managing data.

Authenticity: the quality of data.

Complexity: a huge amount of data comes from multiple channels.

Value: make rational use of big data to create high value at low cost.

Promoting Development of Big Data
China will promote the development and application of big data, create a new model of social governance with precise governance and multi-party collaboration in the next 5 to 10 years, establish a new mechanism for stable, safe and efficient economic operation, build a new people-oriented and people-oriented livelihood service system, open a new innovation driven pattern of mass Entrepreneurship and innovation, and cultivate a new ecosystem of high-end intelligent, emerging and prosperous industrial development.

IT Analysis Tools
The concept of big data is applied to the data generated by it operation tools. Big data can enable it management software suppliers to solve a wide range of business decisions. It systems, applications and technology infrastructure generate data every second of the day. Big data unstructured or structured data represent the absolute record of "all users' behavior, service level, security, risk, fraud and other operations".

The purpose of big data analysis lies in IT management. Enterprises can combine real-time data flow analysis with historical related data, and then analyze big data and find the models they need. In turn, it helps predict and prevent future outages and performance problems. Further, they can use big data to understand usage models and geographical trends, so as to deepen the insight of big data to important users. They can also track and record network behavior, and big data can easily identify business impact; Accelerate profit growth with a deep understanding of service utilization; At the same time, collect data across multiple systems to develop it service catalog.

The idea of big data analysis, especially in terms of IT operations, has little effect on our invention, but we have been involved in it. Gartner has been concerned about this topic for many years. Basically, they have emphasized that if it is introducing fresh ideas, they will throw away the old-fashioned big data methods and develop a new IT operation analysis platform.