Best Data Governance Tools

It leaks have raised public concerns about cloud security. To limit potential problems, enterprises must consider governance requirements, tools, providers, and more. The security of applications and data is critical to any enterprise, but responsibility is not evenly distributed. As a result, it organizations need to develop a cloud security strategy that will identify compliance policies or principles that the rest of the enterprise needs to comply with. The public cloud eliminates part of the infrastructure and management overhead of traditional data centers, but the burden of meeting cloud governance needs rests with the IT department. In the changing ...

As with all enterprise data, large data can only be used to project users through applications. For architects who design or redesign http://www.aliyun.com/zixun/aggregation/8213.html "> Large data applications, a key question is whether to use object-oriented architecture (SOA) or restful The API connects large data components and services to other parts of the application. Start with an interface that is exposed by a large data product and then define a large data interface on the application side. Connect with ...

Recently, I returned to attend some university seminars, government departments of the symposium and the training activities of enterprises, the theme is large data, nowadays, the major domestic newspapers and magazines are also discussing this hot topic, but I found that the Chinese society on the "big data" concept still some inaccurate understanding or even the concept of misunderstanding, In particular, the strategic significance of large data at the national level is underestimated and needs to be deepened. Small data to large data "big data" is a new wave of technology, but also gradually formed a historical phenomenon, its specific refers to the increase in the amount of information storage, the human in practice gradually recognized ...

Today, big data technologies, especially big data analytics, have evolved into an important part of most corporate strategies, and companies are under intense pressure to keep up with the rapid growth of big data.

Telecom operators are increasingly aware of the importance of treating customers, products, and network data as business assets. In addition, these companies face the dilemma of dealing with large data-related issues such as Call detail Records (CDR), billing and data-use event records, social media and geo-positioning information. This paper discusses best practices for managing different types of information in the telecommunications industry. Improve the overall customer experience by building a single customer view across multiple islands the cost of developing new customers is high, so most telecom companies are extremely concerned about retaining existing customer base and reducing customer churn rate. ...

December 2014 12-14th, as the most influential and largest it event in the field of data--2014 China large Data technology conference and the second CCF large data academic conference in Beijing new Yunnan Crowne Plaza Hotel successfully ended. The conference lasted three days, with an international perspective, the paper shares the development trend of large data technology at home and abroad, and probes into the application and practical experience of "large data ecosystem", "Big Data Technology", "large Data Application" and "large data infrastructure" from the angle of technology and practice, and through innovative competitions and training courses Decryption Big Data startup heat ...

December 2014 12-14th, as the most influential and largest it event in the field of data--2014 China large Data technology conference and the second CCF large data academic conference in Beijing new Yunnan Crowne Plaza Hotel successfully ended. The conference lasted three days, with an international perspective, the paper shares the development trend of large data technology at home and abroad, and probes into the application and practical experience of "large data ecosystem", "Big Data Technology", "large Data Application" and "large data infrastructure" from the angle of technology and practice, and through innovative competitions and training courses Decryption Big Data startup heat ...

Infrastructure-as-a-service (IaaS) products are often easier to use to meet the computing needs of enterprises because only providing virtual machines can add some database features. Unfortunately, IaaS users are finding themselves facing new operational challenges in deploying and integrating their cloud applications and their in-house IT, with very few expecting to move everything to the cloud. Now that the new Private Platform as a Service (PaaS) tool appears, it's an effective solution to this problem. In addition to providing the tools needed for all operating systems and middleware, these tools also provide a "...

Recently, two things about large data are worthy of attention: first, in the middle of May, our school set up a large agricultural data research center. The second is the middle of June, the first domestic agricultural data industry technology Innovation Strategic Alliance was established in our school. 　　These two events will have an important impact on the next development of the school, and also bring new opportunities for the development of the subject. At present, large data research and application in the domestic just started, the agricultural data related research has not been deeply involved, it should be said that our school in this area to grab the first mover. 　　We must cherish and grasp this opportunity, and actively carry out relevant research, as soon as possible to achieve results. ...

In the era of "big Data", modern information technology represented by Internet will fundamentally change the mode of modern financial operation. The characteristics of data magnanimity, diversification, rapid transmission and value will bring new challenge to commercial bank market competition. In the face of this "data earthquake", how is the banking industry changing and homeopathy? How to use high-quality data and strong and stable data analysis capabilities to develop a wealth of data applications to provide customers with intelligent and targeted services? How to deepen the application of large scale financial data and transform it into industrial competitiveness from two levels of strategy and implementation? Recently, Beijing ...