What the government did for the big data era

Source: Internet
Author: User
Keywords Big Data
Tags analysis analyzing applications beginning big data big data era big data industry business

At present, big data has gradually become a powerful force for promoting enterprise efficiency improvement and management change. Some enterprises are gaining advantage by mining, analyzing and using business applications with massive data brought by the Internet and the Internet of Things. It is beginning to make society more prosperous. In the United States and in many other countries, big data has been mentioned at the height of its national strategy. But how to develop big data? This is also a thorny issue. From the experience of Singapore, the government has taken a very important position in making big data.

Infrastructure, Industry Chain, Talent, Technology and Legislation are the five key elements of Singapore's government's grasp of big data growth. It has played a key role in this. It is particularly worth noting that these five elements can not be achieved by ordinary businesses, and the Singapore government has just filled in the shortcomings of the enterprises.

Big data infrastructure

The infrastructure of a country in terms of information and storage determines whether large amounts of data in the big data age can be aggregated, communicated, stored and applied. In order to provide a good foundation for the development of big data, Singapore is not mean to invest in infrastructure. Singapore is one of the top 10 high-speed network architectures in the world and hosts more than half of all third-party data center storage in Southeast Asia. Singapore has established its position as a global data management hub that brings together more than 50% of commercial data hosting and neutral carrier data centers in Southeast Asia.

Big data industry chain:

In the big data industry chain, including data providers, storage providers, analysts and miner, as well as application enterprises. For businesses, they often have only application capabilities but lack the ability to acquire, store, analyze and mine big data. In this regard, of course, we must rely on the corresponding service providers in the industrial chain, but the Singapore government has played a key role in the construction of the industrial chain.

In data mining, Singapore encouraged universities to set up data mining and analysis platforms. In 2012, the "Livelabs" Innovation Platform from Singapore Management University (SMU) was designed to enhance Singapore's data analytics capabilities in consumer and social behavior. Singapore also encourages companies to set up data analysis centers. Some enterprises have succeeded in expanding their business in the regional market by establishing a data analysis center in Singapore to gain insight into the needs of the Asian market. In 2011 Rolls-Royce partnered with the Institute for High Performance Computing under the Singapore Institute of Technology and Research (A * STAR) to set up a computational engineering lab to collaborate in the field of intelligent data analysis. The Singapore Institute of Information and Communication (I2R) currently has one of the largest data mining teams in Asia.

The Singapore government also assumes the role of data provider and voluntarily discloses data held by the government. In big data construction, this is crucial because, after all, the government is the largest data owner. But letting the government take the initiative to open up its own data is not an easy task, and the Singapore government has done that. OneMap, developed by the Singapore Land Authority, provides an open data platform for companies that provide location-based services (LBS).

The Land Transport Authority of Singapore, on the other hand, has opened up Singapore's traffic data through the Public Data Open Plan to encourage businesses and even individuals to develop applications that enhance the efficiency of public transport.

The National Environment Agency of Singapore (NEA) works with a number of companies to study how rainfall can be collected and to predict which areas are likely to erupt following the onset of possible diseases in the tropics by capturing data on different areas of the environment.

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