Three major technologies needed by enterprises in large data age

As the key word in the IT field, the "Big Data" is always in the spotlight, and the analysis and utilization of it has attracted much attention. On the other hand, problems that cannot be solved by IT technology, existing organization and talent skills are gradually surfacing. This requires "the analysis of data and its integration with the business technology."

This paper summarizes the technologies needed to apply data analysis to the business and how to implement effective information applications in the enterprise. At the same time, it also lists the advanced examples of Japan and abroad.

Three major technologies

Now, let's take a look at the technologies that companies need in the big data age.

Business Skills

The business skills here are not the ability to improve performance, but the ability to standardize business processes, to master what information in each process needs to be entered, recorded, and so on.

Take business activities as an example. Usually, the survey of some promotional activities is expected to become the customer information input CRM (Customer management System) system, sales leader in this information on the basis of marketing, customers are interested in products, services, etc. will be as data input CRM system. Next, if the customer buys the product, enter the settlement information in the settlement system, if the goods are in http://www.aliyun.com/zixun/aggregation/6512.html "> logistics system Input, generate logistics information." In this way, it is important to know which data is generated in the process and in what activities.

In addition, which process, or in which process generated data will have a greater impact on the business results, and its perceptual estimates, rather than the relevant data analysis, form a pattern. For example, compared with the age and sex of the customer, what kind of occupation has a greater impact on the probability of purchase.

Mathematical skills (patterned, sampled)

The second is the mathematical skills needed to analyze the data. Previously, when it comes to analyzing the skills of business data, it is a simple statistical knowledge of total, average and standard deviation, but later, through the analysis of data to study the regularity of the business, the formation of "model", "sample" technology is very necessary. This is a common tactic in the scientific community. For example, the ideal gas state equation "PV=NRT" means that the state of the gas is expressed in a modal formula.

Similarly, in the industry, the state of business activity is also required to form a formulaic analytical technique. For example, chain supermarkets can be based on the location of the store, calculated under various conditions (sales performance, weather, temperature, days, etc.) of the passenger flow and the sales of each commodity, to find the law, you can make more appropriate adjustments, can reduce losses, improve profitability.

IT technology

It technology is also indispensable. First, the database-related technologies. The data that needs to be analyzed, where the items involved in databases such as age and job are combined with the actual business terminology, can now be implemented through it. However, at present, most enterprises are confronted with the business terminology is not uniform, database fragmentation and other problems, there are still a lot to rely on people to solve things.

In the future, the ability to solve formulas through it technology will become increasingly important. For example, if the relationship between the sales of a product and the age of the customer is expressed by the formula "sales =ax Age", factor A can be obtained through it technology. This is a very simple linear regression problem, the small amount of data can be used in Excel spreadsheet software to find a. In addition, can also use SPSS and R and other professional statistical analysis software. More complex situation, you need to create a program to find the coefficient, the technology of the IT engineer can be said to be a treasure!

It's important to keep people.

The above three kinds of technology are introduced, but unfortunately, there is no Superman with all the above technology in Japanese enterprises. So how do you nurture people with these skills?

No matter what kind of technology is very professional, is not able to master overnight. But in fact, the person who grasps the business technology is in each business department, the talent that grasps it technology is in information System department.

Mathematics, which seems difficult to learn, is often nothing to graduate students in the science department. In physics, chemistry and other fields, there are also many people who have formulated natural science and studied how to get a more accurate formula, which has a lot of experienced talent, it is not impossible to apply natural science to business activities.

Is it possible to bring these people together from various departments and to form a team of professional data analysis that is not something that can be started right now? Then, the team will be placed in business planning and business planning, such as the establishment of enterprise development strategy departments, to support the competitive advantage of the key force.

Start with the little things

It may be difficult to master mathematical knowledge, but the application of software to solve the problem is not to solve mathematical problems. All the spreadsheet software on hand can do simple regression analysis, and there are many more advanced analysis software that can help you solve more complex problems, which make up for the lack of mathematical knowledge.

In fact, there are companies that have invested and succeeded in analytical technology. Denmark Vestas Wind Bae, is engaged in the design, manufacture, sales company, it will use large data analysis in the business, through continuous, the company all organized work to harvest success. By increasing sustainability on the basis of organization, analysis can be used more effectively.

In Japan, several IT engineers have made large data analysis projects and have continued to achieve results. In this process, the lack of mathematical knowledge related to analysis has the same analytical team as IBM and the support of large data analysis software vendors to make up for the shortcomings of the three technologies mentioned previously, and succeeded in achieving results.

At the same time, there are also enterprises set up more than 100 professional analysis team. Set up an analysis team of both it and business personnel, through the actual operation repeats "test-error" process. Through this process, the enterprise continuously obtains the small success experience, the analysis level also gradually enhances. And enterprises should be the first to develop the necessary knowledge and technology talents.

At present, there is a large and diverse range of information in the business environment, no matter which enterprise has analysis requirements. and skilled application of the latest it tools, with better insight will become the key to the gap between enterprises.

This paper sums up the knowledge and organization necessary to apply data analysis to the business, and it is not rare to re-examine the data analysis with the popularization of large data as the opportunity. Even if the whole company can not be carried out on a large scale, we should start as soon as possible from the place to do, from the small start is the key.

April 12, 2012: "Japan" Itmedia compilation: China ccpit Electronic Information Industry branch of the morning king

(Responsible editor: Lu Guang)