Eight industry CIO talk about cloud computing big data Landing truth

Assuming that the Internet can provide students with quality free education resources, then all universities have to answer parents a question--what is the cost to students and what is the best resource?

On the evening of May 22, 2014, Xu, director of the Information Office of Shanghai University, threw out such a sharp topic on the "CIO Salon for cloud computing Big Data Industry". Indeed, with the development and popularization of MOOC (massive open online courses, a large-scale web-based open course), the traditional teaching model is being broken. Using cloud computing and large data, MOOC can have 1 million students in one semester and a networked learning model. This new mode of knowledge dissemination and learning methods may lead to a "tsunami" for global higher education.

Renhua, Deputy Secretary-General of China Electronic Society

Undeniably, this is the cloud computing and large data and education after the combination of a very real problem. This problem, although there are different appearances in all walks of life, but the essence is the same-that is, subversion, revolution, innovation.

Looks very beautiful very lively cloud computing large data, in concrete landing but had to face a series of such realistic problems. As Renhua, Deputy secretary of the China Electronic Society, said: "Industry does think that this is a big development direction, but also a very good transition opportunities, but users are very cautious attitude." ”

At the CIO Salon dinner hosted by the China Electronics Society and Itvalue, nearly hundreds of participating CIOs have focused on the current needs and confusions of cloud computing and large data applications, as well as industry best practices, through workshop discussions. Through the field group interactive discussion, we can basically think: Although the CIO generally think that large data cloud computing will be promising, but its current development is not very healthy and optimistic, whether it is the user's understanding, or practical application, there are many problems.

Value is the primary concern of any enterprise. Cloud Computing's big data is either a destructive subversion or a fleeting opportunity. This makes the enterprise's attitude very cautious, even on thin ice. The message that this pressure transmits to the CIO is to ask value before action. "When it comes to big data on cloud computing, the first reflection is how to maximise sales and profits for the company." "China Gold Group Gold Jewellery Co., Ltd. Information department head Zhou Hanlin said. Li Hong, general manager of China Steel Group Information Management Center, also said: "It project bosses will ask where the value is." If the value is not clear, no one dares to do it. "And the CIO from the airline industry has thrown out an example that can be used by the industry: to find out where the different companies and peers are likely to be, rather than to compete at low prices for homogenization."

Safety is an unavoidable problem. On the one hand is the public cloud itself security, on the other hand is the data itself security. Data recognition can remove sensitive information and provide integrated data. But now there is the technique of "recognizing and then recognizing", which can still be aggregated to reflect sensitive information that is hidden or deleted. So security is still a huge challenge for CIOs. Zheng, chief it expert of Shenzhou Digital (China) Co., Ltd., for example, said: "Some manufacturers to make large data, the probe directly to the export of data, you can take away the data, such a problem how do we face?" ”

Difficulties may also be opportunities for CIOs and IT departments. Data sources are not fixed, data flow, data analysis capacity, etc., so that CIOs in the cloud computing large data encountered more difficulties, but this also means that data collection model innovation, data management innovation, business model building and analysis innovation ... This allows it to usher in a new development opportunity, across departments, across the enterprise, upstream and downstream of the business cooperation, it will gain more power of discourse.

Of course, the prerequisite is for the IT department to achieve self change. Cloud computing's large data subversion of the business model of the enterprise will also subvert it's own mode of change. Technology and business need to be upgraded, and future it construction ideas need to be improved. "The original talk about all the systems are process-centric, with large data, it can be in turn from the data angle to build IT system?" "Itvalue, the publisher of business Value magazine Liu Jinming, gave his own advice.

In the present situation, due to different industry characteristics, cloud computing and large data in different industries have different landing depth and dimension. For example, the financial industry has a relatively deep application, while the real estate industry is relatively weak. But the traditional industry of cloud computing large data landing path is not clear, is a common confusion among the CIO.

Specific to different industries, dinner salon through the form of workshop, the group discusses the various industries in the cloud computing large data landing process of major concerns and confusion. The following is the Itvalue editorial department according to the meeting discussion sorted out the eight major industry CIO concerns.

8 industry CIOs in China how to see "The opportunities and challenges of cloud computing and big Data"

Large Diversified Group

1. Cloud computing is the trend, it is urgent to solve large enterprises in the original data center large, complex operation and maintenance problems, as well as equipment aging problem; But how to adopt cloud computing still have no mature practice, whether should "public cloud + Private cloud" one, namely mixed cloud way?

2. Cloud computing challenges and opportunities for large enterprises are mainly due to the natural disregard of new technologies and business models by traditional business decision-makers and managers.

3. Public cloud in large enterprises landing difficult, cloud security and data security issues highlighted, mainly for the security of distrust, public cloud operators can have a certification system to ensure security?

4. Large Enterprise OA, training, sales management, etc. more suitable for the adoption of public cloud, ERP and other core applications more suitable for the adoption of public cloud, CIOs need to see more industry in the cloud application case and the need for mature private cloud, hybrid cloud construction program.

5. A large number of enterprises under the diversified enterprise, many systems are fragmented, cloud and large data from the overall is to do "resource integration", it governance, data governance for the implementation of large data is a key step.

Transportation industry

1. The volume of traffic enterprises is usually too large, information construction has become mature, and then the way to cloud computing is difficult, currently only a few small applications using the SaaS model.

2. Big companies and small companies are very different when it comes to cloud computing, and small companies favor SaaS models because of cost issues, but big companies are wary of cloud computing because of security and compliance requirements.

3. How to collect useful data is a difficult problem, including the establishment of data collection standards and the definition of the range.

4. How to open the data in the material chain to the upstream and downstream users, because only data integration can show real data value.

Manufacturing

1. The correlation of data sparse density to enterprise application.

2. Standards for data acquisition and collation in the manufacturing industry.

Retail and services

1. Is there conflict between the promotion of cloud-based services and the enterprise's own informatization strategy? or complementary?

2. The visible demand in the retail industry is more outstanding, but how to achieve a balance between the common service and individual enterprise's individuality demand?

3. Retail companies have a particularly high annual sales demand, how can the cloud to the company to bring sales and profits?

4. Data collection, collation, how to better guide the operation to win the market?

5. Cross-sectoral data exchange issues.

6. The retail industry for upstream and downstream access and platform integration, can be directly extracted to the end of the data, but how can these data collected after the use of it?

7. More data, but how many enterprises really spend their energy in data analysis, mining, based on large data to make business decisions?

8. How big is the difference between the big data in different industries? How to distinguish between commonness and individuality? How does the enterprise's personality data be satisfied?

Education industry

1. Security and auditing of the public cloud.

2. Large data talent is particularly difficult to find, especially in many educational institutions not in the first-tier cities, what is the general recruitment strategy?

3. With the use of large data user Behavior Analysis Management tool (DMP), the industry has sophisticated tools and use cases?

4. Large data How to make the design works of the whole process analysis.

5. How to solve the problem of internal data collection and analysis in enterprises?

6. Large data how to analyze student needs, including growth process, personality development.

7. How to solve the problem of education equity by means of the Internet, so that the allocation of educational resources can be solved.

8. How to realize the exchange of information between parents, schools, students and other people through large data platform?

Internet finance

1. Who will make the rules for cloud computing in the financial sector, the SFC, the CBRC, or the operators, or some strong institutions?

2. Cloud computing in the Internet finance, the emergence of risk, the main compensation and responsibility of the subject is who?

3. What is the financial industry cloud operating standard?

4. The impact of the financial industry on the general population through cloud transition?

5. Large data generated financial business innovation?

6. Large data face the data risk and business risk effective prevention.

7. How does the financial industry's cloud computing and large data security rules be established?

8. Future financial industry opening-up strategy.

Medical industry

1. Cloud platform and large data generate Internet health industry. For example, starting with wearable equipment, many people will take their own data to the Yunping platform, or to the health data, movement data synchronized on the cloud platforms. These data include the age of these people, basic physical indicators, exercise habits, consumer behavior, where they often go, and so on. The future of health and medical institutions to collect data effectively, and let this data accumulation, adhere to the user to use the platform, then its future value is limitless, this is a very large potential business model.

2. How do pharmaceutical companies use large data? Now in clinical trials to screen patients, in fact, through a lot of large data analysis to complete. Gene analysis is a very important indicator, and through the analysis of the population, age analysis, to determine what kind of people to do this experiment. Also, after the clinical trial, the drug market to do a lot of statistical analysis, through a variety of models to find out what kind of people, what kind of disease, what the number of effective results. The product manual will see what dosage and patient needs to be halved, all of which are calculated by clinical analysis.

Real estate industry

1. Real estate Industry It informatization started relatively late, the boss of it's attention is limited, but the real estate industry, large data applications, there is a lot of space and the future.

2. How can large data help real estate companies do accurate marketing?

3. Large data will be well applied in commercial real estate. How to get the physical platform data of shopping center? According to the daily sales flow data to get the real business of the merchant, so that the entire shopping mall merchants structure, location to make some adjustments.

4. The real estate industry big data talent lacks.

5. Real estate industry for large data application is relatively late, but the space is broad. According to customer demand data mining, but also can extend the customer's needs to other industries, such as customer value-added requirements mining, through the use of data mining and analysis to achieve value-added services.