Fujitsu launches large Data Services cloud

Just being online to serve your customers is far from enough. You also have to look at your customers and prospects, and anyone else you can get data from, and mix the data together for large data analysis to dig out more revenue and profit.

It's a big job, not all companies--well, very few companies--that have the skills to do this kind of work. Fujitsu is smelling the business. The company has launched a large data cloud service that allows you to offload all or part of this work to the Japanese it giant.

Fujitsu launches today's data utilization Platform Services (http://www.aliyun.com/zixun/aggregation/12239.html) > Platform Service Perhaps the dullest name in it history, but they are part of Fujitsu's overall cloud strategy. Fujitsu's cloud strategy spans all of the cloud: a private cloud running Microsoft's Azure platform, a service-including its own COBOL and Java extensions, running on x86 and using CentOS and KVM Linux and Windows Fragments, and SaaS (Storage-as-service) and PAAs ( Platform as a service) selected engineering cloud for remote computer-aided design software operation. Last year, these cloud services and products emerged.

Instead of using Fujitsu's hardware to analyze data, Fujitsu's big Data cloud service today is using Fujitsu's software and systems to collect data from sensors, application transactions, click Streams, logs, multimedia files, and other data formats, and then conduct large data analysis, Use streamlined information results to drive improvements in Web sites, transactions, or other corporate behavior to make more profit through better customer service.

These large data cloud services are part of Fujitsu's converged services strategy. Fujitsu's converged services strategy is designed to drive the IT-driven "people-oriented intelligence community", similar to IBM's Intelligent Earth strategy in various advertisements.

Fujitsu: Big Data is big trouble, so unload the cloud for us

Fujitsu's large data service is a menu-style service, and company users can choose to use Fujitsu to manage data collection, processing, or the integration of these data on existing systems.

The large data cloud has four service sets. Fujitsu says the company has created systems to manage "large amounts of decentralized data in different formats" and has packaged these systems as data management and consolidation services. As for communications and control services, these services can be used to communicate the various types of equipment-from mobile phones and tablets to industrial equipment and other consumer electronics-to remotely control these devices from anywhere.

The data collection and detection service performs a real-time sorting of the data flow into the system, determining which data needs to be performed immediately and which data should be merged into larger blocks for further analysis. Finally, the data analysis Service makes a practical analysis of large data and streamlines the data to excavate useful information.

These are the big data services. Fujitsu does not disclose the underlying software it uses. The Reg is more certain that Fujitsu uses Hadoop, open source MapReduce Data Analyzer, and associated Hadoop distributed file systems in some places. However, Fujitsu can also use other data analysis techniques and nosql data warehouses. The company says its Spatiowl location information service (launched last June) can be used for large data services.

Data Utilization Platform Services is now available to customers. Fujitsu plans to add two services in April this year. One is the data Exchange service, which allows the processed data to be available to multiple applications as needed in a variety of formats. One is the information application Support Service, which obtains the analysis result from the data processing and uses this result to promote the Network Service application.

Fujitsu also expects to provide some artificial intelligence under some form of data repair services, which means it will use its own experience in large data processing to help customers determine what data is important and which data can be temporarily unhandled.

Given the complexity of the service itself, the pricing of large data services can only be achieved through the bidding process.