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Big Data Analysis

Big Data Analysis

V&G big data integrated organization and management adopt own solid-state storage products together with data organization and management system to quickly and in-depth data mining and analysis to meet user needs.

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Big Data Analysis

With the extensive application and in-depth development of technologies such as big data, cloud computing, and the Internet of Things, the scale of information data has exploded, data structure characteristics and storage forms have become increasingly diversified, and the importance of data assets in business systems has greatly increased. Data storage systems put forward higher requirements in terms of capacity, performance, and reliability.

V&G Information has the solutions of all-in-one data management platform and Distributed Storage System for big data analysis applications.


• The all-in-one data management platform provides a good data ecological environment for the development of big data analysis applications to fully tap the value of the data, so that the data can not only play its traditional efficiency, but also realize data sharing and data value for the construction of business systems, based on this goal , Build a distributed big data basic support environment, build big data storage, processing, mining, analysis, visualization and other platforms on the basic support environment, and provide corresponding big data service applications on these platforms.


• V&G Information distributed storage system VGStor is based on the software-defined storage concept and adopts a distributed unified storage architecture design. It supports object, file, and block storage protocols in the same system, and supports multiple data center enterprise-level storage features. VGStor provides the visual operation and maintenance management function, based on the WEB architecture, realizes the deployment, configuration, management, operation and maintenance, and operation control of the storage system under the browser interface. At the same time, it provides intelligent operation and maintenance tool software and rich Restful interfaces.


Features:

Huge Volume Data

Data collection, calculation, and storage all are huge.

Diverse and scattered

Diversified types and sources. Types with structured, semi-structured and unstructured data, etc. Common sources are: web logs, audio, video, pictures, etc.

Fast

The data growth, the processing speed and the speed of data acquisition are all fast.

Data filtering

The data value density is relatively low, the valuable information needs to be filtered from a large amount of data.

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Application Cases:

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