Large data after mixing it

In the 2011, for many companies, cloud computing was only half the business, or even less.

But it is clear that the business uses cloud-based applications-including customer relationship management, sales force automation, human resources, cost management, and more-than ever before. Mixed it will become a new normal, which may not be obvious in the early days of cloud adoption. But the expectations and needs of the business for large data require IT organizations to accept mixed it and to integrate data into services for the enterprise on an as-needed basis.

When it comes to the relationship between big data and cloud computing, Informatica, China's chief product advisor, says the challenges of big data will be even more severe in 2012 as the deployment of cloud computing applications accelerates.

Big data means big resources, this is the intersection of cloud computing and big data, which means that cloud computing has two directions in relation to large data, cloud computing can host large data, and large data can provide solutions through cloud computing architectures and models. In this way, we can clearly know that large data in the direction of management and application, through cloud computing resources sharing, high scalability, service characteristics to build and operate.

Now, the volume of data in various institutions is growing rapidly, and the data is flowing daily within its systems, and the amount of data in the cloud is increasing. As the volume of data increases, the ability to process these data in real time has become one of the major challenges of large data. With the rapid deployment of cloud computing applications in the 2012, the challenge of big data will be even more severe.

With the development of cloud computing, cloud data integration will become the focus. As more and more enterprise organizations turn to hybrid it architectures, and the business criticality and complexity of cloud integration tasks increase, the enterprise-level characteristics of cloud data integration are of great significance to customer success.

Since last year, many manufacturers have begun to tap into big data and hope to get the Nuggets however, from the current situation, due to the high technical threshold of large data, it companies that compete in large data fields still have traditional advantages in the fields of data storage and analysis, such as IBM, Oracle, EMC and so on.

But bin is confident in the company, he said, Informatica a set of sophisticated technology to support a number of complex enterprise-level data integration plans, including: Enterprise data integration, data quality control, master data management, B2bdataexchange, information lifecycle management, complex event processing, Super Messaging and cloud data integration. By Informatica a single, complete, open and economical data integration platform, enterprise organizations can improve operational efficiency and reduce operating costs while improving data quality while accessing, discovering, cleaning, integrating and delivering data.

In the field of large data, Informatica also launched the 9.1 version, which is the first unified data integration platform specially built for large data.

Finally, turning to the framework of user-focused Hadoop, bin says that Hadoop has two important characteristics, economy and scalability. In 2008, a telecoms operator tried to build a cloud computing platform based on x86 architecture and Hadoop architecture with 360,000 yuan. Compared with the existing 2.7 million-dollar commercial system running the same application performance comparison, they are pleasantly surprised to find that the Hadoop platform data processing performance increased by about 30 times times, mining performance increased by about 9 times times, and the cost advantage will be increased with the size of the data processing more advantages.

As companies continue to seek higher data returns, there will be a higher demand for Hadoop developers, and skills shortages will continue and are likely to intensify. Hadoop will continue to gain traction in the 2012, but will not be a real mainstream 2015 years ago.

(Responsible editor: The good of the Legacy)