Large data leads logistics informatization

Source: Internet
Author: User
Keywords Large data constantly
Tags analysis analysis technology applications based big data business business applications change

Large data is affecting the way in which people know and understand society, and promote social development and change of management mode. Victor Maire-Schoenberg, an American scientist known as "the first man of large data business applications", points out that "the essence of the world is data, and big data will usher in a major transformation of the Times." It is of great theoretical and practical value to study the influence of large data on the trend of information construction of military logistics, and to promote better and faster development of logistics informatization.

The era of logistical data has come quietly

The content and standard of large data are constantly changing. At present, large data refers to the size of a single dataset over conventional processing techniques and capabilities, "a vast collection of complex data that cannot be extracted, stored, searched, shared, analyzed, and processed with existing software tools". The significance of large data is not the "big" of data scale, but the new change of thinking, technology and method, which can "discover big benefits, big technology, realize big development" through large data.

The view that the importance of large data to the development of logistics is questionable. "Logistics" from Latin, the intention is to calculate, of course, the calculation is inseparable from the data, if said "the essence of the world is data", then the essence of logistics is data. Bin Pangjuan in Marling Road, Zhuge Liang's Wood Marue cattle cheong in Shu Road, Iraq war in the comprehensive three-dimensional, modern, long-distance logistics support, no need for a large number of accurate calculations. Under the condition of informatization, the data acquisition technology and equipment develop continuously, the record, collection and processing scope of the logistic data are enlarged, the accumulated data scale is bigger, the relationship becomes more complicated, the typical characteristic of large data is more obvious, so the data value of large data should be used to solve the problems in the logistics construction

Big data is an effective way to break the fog of logistics

The logistics fog, which consists of uncertainty of demand and uncertainty of resources, can easily cause problems such as duplicate application, repetitive purchase, overstock of stock, invalid transportation and low efficiency, which is the bottleneck of the formation and promotion of logistic support ability. Through the ages, to solve the logistics fog to achieve "demand real-time known, resources visible Control" of the free realm, is the tireless pursuit of military strategist.

To observe the causes of the logistics fog, we can conclude that its essence is the data fog. With the evolution of the war form from cold weapon and hot weapon to informatization, the logistic data scale is increasing, the category is increasing and the relationship is more complicated. The collection, transmission, processing and analysis of these data have constantly challenged the level of science and technology at that time. 20th century the end of the United States, 6 combat groups of ships for a fiscal year demand replenishment please receive up to 132,000, data size and processing difficult to imagine. However, the development of large data theory and its technology provides an unprecedented opportunity to solve the fog of logistics and realize the visual controllability of logistics. The rapid development and application of sensor technology constantly break through the range and limit of the data collected by people. Cloud computing and cloud storage technology have cracked the computational, management, and storage challenges of large scale data, and have found a place for large data. The large data processing technology, which is based on the distributed file system and large scale data parallel algorithm, realizes the automatic searching in the Mass datum, discovers the new knowledge and explores the new law through the time and space. From the database to the Data mart, from the local visual to the full range perception, from the data sampling to the full sample analysis, from the causal analysis to the correlation analysis, the environment, conditions and technical methods to solve the logistics fog are gradually possessed.

Large data makes logistical forecasting decisions more scientific

"The core of big data is forecasting." Large data prediction is no longer based on the traditional causal relationship theory, but on the correlation between different things or different attributes of things, so as to predict the future. Correlation refers to the degree of variation of other data when a data is changed, often by identifying useful correlations. Various activities, equipment, personnel and materials in the field of logistics are intertwined and affect each other, and the related relationship is more complicated. The search for certain correlations can predict material consumption, machine failure, equipment status, and prevent equipment failure. Before attacking Iraq, the U.S. military can forecast the 48-hour equipment support demand through the networked forecasting system. The combination of large data prediction technology and traditional data analysis technology will greatly improve the accuracy, efficiency and timeliness of prediction.

One of the important changes brought about by large data is the change of thinking, mode and method of decision making. In a large data age, decisions are increasingly determined by data and analysis, rather than experience and intuition, and the decision based on the sample will give way to the full sample decision, the empirical decision will be changed to the positive decision, the decision more timely and accurate. A consulting firm in the United States conducted a study and analysis of data from 20 engine status monitoring sensors in Missouri State Lewis City, which accurately determined the best time for vehicle maintenance. The cycle of replacement of vehicles from 300,000 kilometres to 500,000 km has saved 600,000 dollars for the city. The analysis and research of all the data is a microcosm of the decision behavior of large data.

With the acceleration of the information construction of our army, the data from the sensor and other facilities and equipment converge continuously, the record, measurement and analysis scope of the logistics activities is expanding, and the logistic data is surging. In the logistics management and decision-making, we can analyze more data, sometimes even all the logistics needs, logistics resources of all the data, with the change is logistics knowledge, logistics rules, logistics support methods of the cognitive mode, logistics decision-making behavior patterns and methods. The new thinking, new models and methods brought by large data will have a far-reaching impact on logistics construction and management.

Data will become the main body of logistics informatization construction

"The data is valuable and its vitality is longer than the software system that collects it." "Programs can be constantly updated, upgraded, and replaced, but the value of the data is growing and lasting." With the development of mining technology and artificial intelligence technology, the value of data is more prominent, and the data with sufficient scale and its processing and analysis technology are becoming the core of competitive advantage of various activities.

With the acceleration of our military logistics informationization construction process, the lack of data acquisition technology, the weakness of the processing ability and the weakness of data use, it will gradually become the bottleneck of the system deployment and efficiency, and it is urgent to plan and construct the logistics informatization with the data as the main body. At present, although a large number of business record data are stored at various levels, the data sources are complex and different in structure, and many are isolated, fragmented and without vigor and need to be sorted out and integrated urgently. With the increase of data type and the growth of data scale, the traditional centralized warehouse and data warehouse system can not meet the needs of large data storage and analysis, so it is urgent to transform the distributed processing. Logistics data computing capacity is weak, and urgent need to update data calculation models and methods. These problems are not only the realistic problems faced by logistics informatization, but also the technical problems that must be solved in the development of large data. Not only need the breakthrough of technology, but also need to break through the concept of information construction, thinking and model resistance.

Discovering the value of large data will become the core function of logistics information system

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Information system includes two parts of program and data, the program can realize specific business management function, which has been universally understood and valued. In the large data age, the information system has gone beyond the general stage of business function realization, and the discovery of data value will become the core function and ultimate pursuit of information system. Sensors and data-gathering and analysis equipment, which are full of battlefield, have brought about a sharp rise. It is necessary for the information system to have strong data processing ability to quickly collect valuable information for logistic decision service in these massive data. At present, the military logistics information system is still to achieve business and process management, heavy procedures, light strategy, heavy flow, light data phenomenon still exist, and the requirements of the era of large data there is a certain gap. How to reasonably plan and scientifically distribute at all stages and levels of logistics, efficiently collect, process and share exponential growth data, and how to obtain effective information and discover value in the large amount of data, which is the important challenge to the information system planning and design.

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