1. The volume of data is huge
In the era of big data, data is generated quickly and in large quantities. Traditional information processing units can no longer meet actual needs. The starting unit of measurement for big data is at least P (1000 T), E (1 million T), or Z (1 billion T).
2. Various data types
Data is no longer confined to traditional structured data, but to unstructured data models such as text, audio, video, social networks, microblogs, and e-mail. The channels for data sources have also been greatly expanded, such as from social networks, e-commerce, and e-commerce. Location information and more.
3. Low value density
With the widespread use of the Internet and the Internet of Things, information is ubiquitous and information is vast, but the value density is low, and the accuracy of data is also reduced.
4. Fast processing
Relying on distributed computing, distributed database, cloud storage, and virtualization technology of cloud computing, distributed data mining for massive data has become more and more powerful.
With the development of smart city construction in China, the security field has become increasingly concerned about cloud computing and big data. For the field of alarm operation services, the profound changes brought about by an industrial upgrade are coming.
Application of Big Data in Alarm Operation Service
After more than 20 years of development in the field of alarm operation services in China, enterprises engaged in alarm operation services have already reached a certain scale. However, the current domestic alarm operation service providers are mostly small-scale companies operating locally, and their service targets include major key public security units such as banks, postal services, substations, and schools, as well as chain stores such as supermarkets and convenience stores, with strong regional dependence. More fixed. The business mode of the alarm service is also based on wired telephone network alarming. The front end is the telephone line alarm host, and the back end uses the telephone to answer the host. The alarm signal is transmitted from the front end to the back end through the CID protocol, and the alarming personnel at the alarm center then go through the phone. Ways to inform customers and mobile members, review the police situation, distinguish between true and false.
The above operating model has resulted in the maintenance of a small number of customers for most alarm operation service providers. At the same time, fewer alarms are handled, and only a few alarm personnel are required to complete the alarm work every day. User-related data analysis is also available. Only a small number of simple data analysis, such as false positive analysis and no time-out analysis, are available. With the passage of time, these alarm data have basically become cold data that will no longer be accessed, far from the standard of huge data referred to by big data, and have not been realized through data processing. Data appreciation.
However, many alarm service providers do not realize that with the development of mobile Internet and social media, people’s lives are increasingly inseparable from the Internet. Each of us will leave more or less of our own data on the Internet. . For companies, how to seize the clues they are interested in through the analysis of big data is the key. Because in the Internet age, whoever has data and powerful computing power on big data, whoever has the winning weight. The core of any company or any system is data. The analysis and prediction of consumer behaviors in various ways can allow enterprises to more actively understand and perceive consumers, help companies improve marketing targeting, and reduce investment risks.
Big Data Application Trends in Alarm Operation Services
The rapid development of Internet technology has provided strong technical support for the construction of a large national professional alarm operation service platform. Through this alarm platform, alarm operators will accumulate massive amounts of user data, such as user's identity information, alert data, consumption records, maintenance records, etc., which are invaluable resources. On this basis, the alarm operation service provider can apply big data technology to analyze and mine, and give full play to the commercial value of big data.
1. Segmentation to customer groups
Through big data analysis and mining of the cultural concept of user groups, consumer income, consumption habits, lifestyle, and other data, the user groups are divided into more subtle categories. Alarm operation service providers can develop different brand promotion strategies based on the user groups. Marketing strategies, improve user loyalty, cultivate potential customers that can bring high value to the company, and increase the market share of alarm operation service providers.
2. Discover new needs and users
Use big data to simulate reality, discover new requirements and increase the return on investment. In the era of rapid development of mobile Internet, most of the data are widely found in social networks, e-commerce, and so on. In these data, relying solely on the presence of social networking data to open up new market demands for enterprises is a great opportunity. Every day, we place a comment on the Internet, or feel free to express a sentiment. In the eyes of ordinary people, the value it conveys is limited, but from the perspective of big data analysis, the value it brings will be greatly enhanced. Imagine that if we can be authorized to mine the words we are interested in from Weibo's data, and when someone issues a 'poor cell security' on Tweet, it will be analyzed and refined through data analysis. People and even households in this community can be potential users of alarm operation services.
3. Improve the return on investment of enterprises
With the increase in the ability of alarm operation service providers to handle big data, the platform can effectively analyze and deal with the large number of reported alarms, avoiding the inefficiency of manual processing and the small amount of concurrent processing. The problem of poor filterability of different types of police situations. At the same time, relying on the platform's powerful data processing capabilities, people can access the alarm operation service through any device such as a computer, mobile phone, or tablet, and receive alarm data at any time and any place. Data improves user stickiness and reduces the risk of user churn.
4. Conduct business model, product and service innovation
By relying on big data analytics, the alarm operation service provider can dig out useful information from a vast amount of police intelligence data and promote the transition of the alarm operation service from 'post-viewing' to 'pre-reporting'. Through correlation analysis, we will expand our products and tap the value of our products to improve the core competitiveness of our service providers. According to the analysis of the police data, it is possible to provide forecast of the police situation in a certain area so that enterprises, governments, and consumers can adjust their own security measures in a timely manner. Based on the analysis of the consumer records, it is possible to identify potential user groups or customers who are about to lose. According to the analysis of maintenance records, more comprehensive monitoring and active maintenance can be performed on the equipment to reduce the false alarm rate of the equipment. Based on the analysis of overdue time, it can be identified which users need early reminder of arming and disarming.
The Difficulties of Applying Big Data in Alarm Service
The application of big data in the field of alarm operation services is limited by the development status of the domestic alarm operation service industry, and it is difficult to make use of the advantages of big data in data mining and analysis. Mainly in the following areas:
1. Lack of standardization in the industry
As China's alarm service industry still does not have uniform alarm operation service standards, alarm networking technology standards, etc., the services provided by the various alarm service providers are also uneven, and service standards, fee standards, and service quality are usually provided by the alarm service providers. Unilaterally, there are no uniform standards for the functions and technical indicators of the alarm networking system. Business processes, construction procedures, charging standards, and police procedures for service providers in different regions and different alarms are not the same. How to integrate the data between different alarm operation service providers is a big challenge for big data in the field of alarm operation services.
2. Overall scale has not been formed
Compared with the alarm operation service industry in developed countries, China’s alarm operation service companies still have a large gap in the scale of operations. Most alarm operation networks have not yet completed large-scale construction, and users have large-scale operations and few networks operate across provinces and cities. Home alarm service providers have a small amount of warnings, and there are widespread islands of information between alarm service providers. This makes the data quality of each alarm service provider greatly reduced, making it difficult to achieve value-added data through big data analysis. .
3. Larger initial investment
The storage and analysis of big data must rely on the investment in hardware and software of a large scale, which places higher requirements on the R&D capabilities of alarm service providers. Alarm operations service providers need to build a strong network infrastructure to aggregate, store, process, and distribute data analysis results. Moreover, the mining of big data is a long-term process that requires companies to make continuous attempts to dig out meaningful information or laws and bring the results to the market for inspection.
4. Big Data itself faces challenges
As an emerging field, big data represents a huge opportunity, but also accompanied by challenges, such as the use of big data is still faced with a variety of technical difficulties, lack of talent in big data, big data products are not yet mature Problems such as these restrict the development of big data in the field of alarm operation services.
summary
In short, with the development of cloud computing and big data technologies, how to use the mobile Internet wave to expand service content, enhance user experience, improve the company's core competitiveness, and achieve more efficient, intelligent, and convenient alarm operation services also require various alarms. Operating service providers to think about it.
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