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本篇paper代写- Big data principle讨论了大数据原理。大数据从诞生至今，在很大方面上起着非常重要的作用，并且在如今人们对大数据的关注越来越高。数据采集方面，大数据主要以批数据采集方式，此方式的实际工作意义就是每天定时对数据库进行数据快照，并且大数据能够根据不同的需求，来对数据库进行备份快照，设置数据源以及如何设计出错等工作。其次是离线批处理方式，这种大数据的工作方式主要具有快速与完全托管的优势，能够设置实现任务的执行时间以及任务的执行条件。最后是实时处理，对于这种大数据的采集方式更为简便，只需要启动storm之后大数据就会自动不停的对数据库中读取数据源。本篇paper代写由51due代写平台整理，供大家参考阅读。

Since its birth, big data has played a very important role in many aspects, and people are paying more and more attention to it nowadays. However, the term big data is often mentioned, but few people really know the real meaning. People are more familiar with the term big data, but have little understanding of the real meaning.

Big data was first proposed by the famous American scholar alvin toffler in 1980. After a long period of development, in 2001, the American gertner company gave a clear and detailed definition of the definition and characteristics of big data for the first time, and gertner repeatedly stressed that big data must have 3V characteristics, namely, diversity, fast speed and large capacity.

Collection and organization of big data. In fact, data collection is to realize the call flow data of the log through the front end, and use the interface log to capture the data in the database. In addition, big data can also perform simple automatic processing, such as converting IP to address, and automatic filtering of dirty data and useless data.

In terms of data collection, data basically has the following several ways: first is the number of data collection way, the way the practical work of significance is that every time to data snapshot of the database, and big data can according to different needs, to back up the database snapshot, set up the data source and how to design error, etc. The second is offline batch processing. This kind of big data working mode mainly has the advantage of fast and complete hosting, which can set the execution time and execution conditions of tasks. The last step is real-time processing. For this kind of big data collection method, it is more convenient. After launching storm, the big data will automatically read data sources in the database continuously.

Big data sorting mainly includes data preprocessing. In the process of data collection by big data, data is often collected from at least one data source. Since these data sources have their own different interfaces, they are vulnerable to data loss, data conflict, noise data and other problems in the actual collection process. Therefore, big data will first be preprocessed for all kinds of data collected, so as to ensure the high accuracy of big data analysis and prediction results to a large extent.

Data analysis of big data. Major technologies in the actual data analysis process of big data include distributed statistics of existing data, deep learning technology of unknown data and distributed mining technology, etc. Distributed statistical analysis is mainly completed by data processing technology. Data analysis of big data can form description patterns or rule attributes of things, build machine learning models and analyze massive training data to improve the accuracy of big data prediction.

Big data application industry. Make full use of the measurement of big data information to accurately analyze the needs of customers. In fact, the current development of big data is like a microscope, which can observe a series of things that people cannot see through data. And through this microscope to fully analyze the customer, to provide customers with the most consistent business model. Change the original business model of manufacturing before sales to sales before manufacturing, so as to reduce inventory and capital risk, and finally play a very positive role in promoting the whole supply chain. In today through the data business is no longer used to purchase a large amount of raw materials and production last in sales business model, there are many shortcomings, this business model now has the support of big data, can through online data for sales after the first manufacturing behavior, which to a great extent, avoids the pressure because of the cash flow and stock up goods and so on a series of influence.

At present, big data has gradually changed the traditional business logic. For traditional business thinking or any decision made by an enterprise is actually dominated by logical forces. However, in the context of big data, it is able to conduct research and collection of massive data, and ultimately summarize them to form more optimized decisions and inferential opinions, which plays a very important role in the development and improvement of business. In this process, big data can be used to complete the business logic process of observation, reasoning, thinking and final decision. And in this process, it will consume a lot of resources and cost a lot if it is to cultivate talents. However, if it can be achieved through big data, this process will be very simple. Nowadays, when we look at the application of big data from different perspectives, it is not difficult to find that big data is a very important opportunity for the current business development and also an ultimately important driving force for the reconstruction of new business models.

Through the specific analysis of the principle of big data and practical commercial application, it is concluded that big data is a new challenge and opportunity for the current business. Only by grasping the development of big data and actively referring to big data can the business achieve further development.

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