Data processing integration

Following the development of the data center architecture of the old, the underlying resource structure is gradually consistent into a compatibility and acceptance of the large pathway to eliminate the information silos, and then to meet the rapid development of the business system of the various needs. In order to adapt to this change, data processing software vendors have begun to turn to the integrated data processing path, including the use of load integration processing, data processing scenarios integration and resource processing integration of three major aspects.

Storage Resource Pooling

Following the gradual aging of distributed and hyper-intergrated technologies, the data storage methodology has shifted from the traditional scale-up architecture to the scale-out architecture that opens the pathway. Therefore, to open the hardware path to build a distributed storage resource pool will become the direction of data processing, IT processors can use distributed storage resource pool to integrate hardware resources, open the data island, eliminate the data shaft, and then make the data processing become more efficient, sensitive and simple, and reduce costs.

Data processing to data service transformation

In recent years, large financial institutions have been utilizing cloud technology to gain planning advantages and reduce total cost of ownership, and the traditional IT operation and maintenance processing has begun to evolve into a service-oriented processing method, and as an important part of IT operation and maintenance processing, data processing is also the same. Facing the transformation of the service method. In the cloud environment, data processing will be transformed from a passive, centralized operation and maintenance method to a user self-service method, and daily data processing scenarios such as backup, disaster recovery and rehabilitation will be completed by the users themselves.

Using open interfaces to satisfy customization needs

Because of the financial work of the data processing has a very high demand, any one of the standardized commercial software can not fully satisfy the needs of enterprises. The traditional software development process is often too time-consuming and difficult to keep up with the changing needs of the enterprise. In order to adapt to the rapid changes and more personalized data processing needs, data processing pathway development trend will be to provide open API interface, data processors can use the open interface in their data processing pathway for rapid customization development, and then meet their own needs.

On how to manage data in the financial industry, Aoto Xiaobo will share with you here. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to know more about data analysts, big data engineers tips and materials, you can click on other articles on this site to learn.