Large data solution providers face three major challenges in 2014

Source: Internet
Author: User
Keywords Large data solutions providers

As large numbers become more widely known at home, many vendors are offering solutions for big data, including IBM, EMC, and Oracle, among other top vendors. CCW Information Forecast, 3721.html ">2014 year, China's big data market will reach 870 million yuan, a 64.2% increase from 2013."

In such a high-growth situation, it should also be seen that most of the solutions are still only for large data applications to provide storage, processing, mining platform technology, and on these platforms, for different industries, different scenarios of the development of applications, is still at a very early stage. Large data in spite of the new business breach for domestic solution providers, many solution providers are still weak in the development of large data applications.

CCW, director of the Research Department of Information Systems, Dingshen that on the one hand, this is due to the large domestic data development environment is not perfect, on the other hand, large data solution providers in the face of the arrival of large data era, the preparation is still insufficient, in the technical innovation, target industry, business value and other aspects of the thinking is not clear, Still face many challenges.

First, for large data solution providers, large data means a fundamental change in the way that data is analyzed and mined, and in response to this change, large data solution providers must change their mindset on existing software architectures, and the most important difference between large data and traditional data analysis is unstructured data and Internet applications , so the biggest challenge for big data solution providers comes from both, and they have to deal with scenarios that optimize themselves for both trends. However, at present, most large data solution providers are based on traditional structure, so it is a great technical challenge to optimize the new architectures.

Industry insiders generally believe that in the large data trend, future industry applications will form a closer ecological chain. In this eco-chain, large data solution providers are highly articulate in their roles, supporting each other, relying on each other, and working closely together to provide higher quality services to the enterprise. Through further division of work, platform operators assume the task of data storage and processing, and large data solution providers provide service performance and reliability assurance to solve problems such as data mining, rapid response, analysis and application, decision support and so on, which are high technology content and cost input. This is a challenge for the financial and technical strength of large data solution providers.

Second, in the context of large data, solution providers face the challenge of changing business models. In the next few years, in the face of the complex diversity of large data structures, industry users have new requirements for large data business model, they would like to use the cloud model to achieve more flexible, more scalable large data solutions, while ensuring the accuracy of data processing, timeliness and other high-quality factors. Therefore, scenarios that require large data solution providers can be flexibly converted between public, private, and mixed clouds without the need to select specific cloud vendors. Today, for more large data solution providers with in-house deployment applications, they still maintain the traditional business model, and the user procurement of a single solution to deploy, if converted to cloud services, then require large data solution providers to significantly increase the application of different industries to different types of cloud architecture input, This also poses a level of challenge to the solution provider in the development of large data areas.

Third, most of the current large data solution providers have their own specific target industry customers, while the storage architecture changes in the large data era, industry users in order to save costs, reduce energy consumption, more need to solve the problem of industry characteristics, have products. Technology-adaptable solutions to simplify storage architecture, reduce management difficulty, and risk. This requires large data solution providers not only to be able to launch industry-specific products and solutions, but also to combine the characteristics of large data storage architecture, combined with IBM, EMC, Oracle and other large data platform providers to provide a technical platform to launch a common solution, Large data Solution provider not only to maintain in the original industry user groups, but also for more industries to expand business, in order to win in the competition.

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