Abstract
Owing to the growing volumes of mobile telecommunications customers, Internet websites, and digital services, there are more and more big data styles and types around the world. With the help of big data technology with high semantic information, this paper focuses on exploring the value and corresponding application of big data in finance. By comparing with the existing methods in terms of search speed and data volume, we can effectively see the effectiveness and superiority of the algorithm proposed in this paper. Furthermore, the algorithm proposed in this paper can provide some reference ideas for the follow-up-related research work.
Highlights
Systems produce bandwidth in a variety of methods, resulting in an estimated 17.5 exabyte of data generated each week
It is true that the Internet of Things (IoT) has played a role towards the massive extraction of information via the advancement and proliferation of linked mobile devices, detectors, as well as other gadgets, in conjunction with quickly changing information and communication technologies (ICTs) such as artificial intelligence (AI)
When big data analysis is used in commodity design, it allows the developer to be continually conscious of the interests and desires of the client, allowing them to create an item that meets their wants and inclinations [11]
Summary
Systems produce bandwidth in a variety of methods, resulting in an estimated 17.5 exabyte of data generated each week. Around June 1986, Teradata Corporation utilized the foremost concurrent database framework with just 1-terabyte memory volume in the Kmart data center to preserve and make accessible everything about their company information for interactional inquiries and organizational evaluation (Table 2). Big data is a phrase applied to define massive database volumes which are very huge that storing them in memory is almost impossible. Such data can be collected, saved, shared, processed, and consolidated. With the omission of big data, analytics is just a set of arithmetic and statistical techniques and methods Such massive quantities of information can be used to derive knowledge by companies. This is achieved by nowadays huge processing capacity that is further reasonably priced than earlier [1]
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