Big data has grown from a concept and a bright term into a set of technologies, architectures, and applications, which, combined with modern analytics, provide practically unlimited opportunities for optimizing processes, and business and also open up new opportunities for scientific research. Check what to do if Big Data needs a new big data architecture in the article below.
What is Big Data: everything you need to know about Big Data?
It is believed that “skills” make it possible to reveal hidden patterns that escape limited human perception. This provides unprecedented opportunities to optimize many areas of our life: public administration, medicine, telecommunications, finance, transport, production, and so on. It is not surprising that journalists and marketers have used the phrase Big Data so often that many experts consider this term discredited and suggest abandoning it.
The broad development of Big Data, and the introduction of computer technology into various spheres of human activity cannot help but lead to the emergence of new tasks for software developers. The essence of any crisis in programming is a contradiction between the needs of information systems and the capabilities of technologies for their creation and support. There comes a time when the technical capabilities of developing and supporting application systems become insufficient to solve problems of the level of complexity allowed by the hardware, and the requirements for the quality of the software also increase as the complexity and responsibility of the functions performed by them increase.
To automate work with data belonging to different types, it is very important to unify their presentation form – for this, the coding method is used, that is, the expression of data of one type through data of another type. An open software-defined storage platform for working with unstructured data in physical, virtual, and cloud environments is used to store such types of unstructured data as:
- Multimedia files (images, video, audio).
- Backup images and operational archives.
- Big data (log files, RFID data, and other data generated by machines).
- Images of virtual machines.
The importance of new backup architecture and its layers
In the context of the development of the digital environment, the role of information has changed significantly. If, before the development of computer technologies, the speed of creating and distributing information made it possible to designate it as a source of necessary information and knowledge (regardless of the purpose of use), then in modern realities, we can safely say that information is gradually acquiring the status of an independent resource with its own value.
Data backup architecture is one of the domains of enterprise architecture, connecting business strategy and technical implementation, i.e., the company’s activities in the form of a business process system and the IT infrastructure for its support in the form of applications and information systems. For example, in the ARIS (Architecture of Integrated Information System) methodology used to model corporate architecture, there is a separate representation of data in the form of information models (data models) that reflect the structure of information for the implementation of all functions of an enterprise as a system.
Typically, a big data backup architecture consists of four different layers:
- Big Data Sources: All Locations That Produce Big Data.
- Messaging and Storage: Big Data Storage Tool.
- Big data analytics: tools that enable big data analytics.
- Consumption/use of big data: users/services using the analyzed data.