The rapid development of information technology and the explosive growth of data have changed the traditional way of working for the entire society. Many changes have taken place in the relationship between people and information technology.
The traditional mode of sharing limited information resources among several people has changed with the fall in equipment prices. Everyone’s information resources have grown dramatically, and access to information has become easier. This process is also a process in which the volume of data increases dramatically. Of course, the demand driven by the volume of information data also increases dramatically, beyond individuals. For example, supercomputers, secure storage of large amounts of data, etc. At the same time, Moore’s Law also encountered a bottleneck, and the increased computing speed of personal computers also encountered a bottleneck. In this case, we need a mode of centralized management of information resources (compute, storage, collaboration) and on-demand distribution to solve the problems caused by the information society – this is a mode of operation in the cloud. In cloud mode, compute and storage resources are centrally managed, provisioned on demand, and dynamically balanced.
Cloud technologies are applied to all aspects of human society, including the infrastructure industry, which is closely related to our human life. Big data and artificial intelligence technologies are also increasingly being used at all stages of the entire infrastructure lifecycle.
It turns out that inanimate things are endowed with the life force “information” for “communication” with other objects, which should mean “Internet of Things”. It is a big data source of information that uses artificial intelligence technology to extract and organize data for greater value.
The process of generating, validating, transferring, applying and updating data has undergone many changes in the context of cloud technologies, and also provided many opportunities for infrastructure infrastructure. This is a digital workflow.
We have entered the era of Big Data (Big Data development services by Data-Science UA). CCTV cameras, information about flights and relocations of people, medical history, transactions, cellular communications, purchases in stores – all this and much more forms databases that are constantly replenishing and growing rapidly. All this data is of great value, a resource for analysis and predictions, food for machine learning algorithms. Today, it is no longer possible to build a system with truly high accuracy without them.
BigData research is at the intersection of the most in-demand areas; it can be said to be the heart of interdisciplinary research. Here we have artificial intelligence, machine learning, and neural networks in the service of medicine, biology, economics, sociology, logistics, physics, genetics, finance; as well as complex semantic algorithms for finding information on the Internet and non-standard approaches to ensuring the security of software and hardware infrastructure.
If we talk about successful cases, then in this regard, the experience of using Big Data technologies at Dunkin`Donuts, which uses real-time data to sell products, is interesting. Digital displays in stores display offers that alternate every minute, depending on the time of day and product availability. The company receives data from the cashier’s receipts which offers have received the greatest response from buyers. This approach to data processing allowed to increase profits and turnover of goods in the warehouse.
As the experience of implementing Big Data projects shows, this area is designed to successfully solve modern business problems.
At the same time, an important factor in achieving commercial goals when working with big data is choosing the right strategy, which includes analytics that identify consumer demands, as well as the use of innovative technologies in the field of Big Data.
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