Present situation analysis and future trend of large-size Chinese data

Has the "Big data" era come?

The trend is a ridiculous and respectable force: today, if you open any media, if not mention "big data", I am afraid to be embarrassed to publish. This trend is so overwhelming that even state leaders are no exception. The question is: Why does everybody say Pro data?

The value of data, with the exponential growth of data volume, has no longer been able to show through the traditional charts, which is why business intelligence has not yet become popular, has been "data analysis" to squeeze the stage. Because value is hidden in data, data analysis is needed to release these values.

The level of data analysis ability determines the quality and success of the value discovery process. It can be said that no data analysis, "Big Data" is just a pile of it inventory, high cost and zero yield. But the "big data" concept of the domestic boom is still in the early stages of data collection, collation, storage and simple reporting. Only a handful of businesses in a few industries can make basic analysis and application of large data. In this regard, we can use Google search results to briefly reveal this situation:

Select four keywords and search separately, and use JMP data analysis software to map the search results:

Obviously, the English world, "big data" search results count more than the Chinese world "large" search results count more than a lot; and "analytics" (analysis) of the search volume is not only higher than "big data", is far higher than "analysis" in the Chinese World search results, is about 169 times times!

This result, although not 100%, can restore the emphasis on "big data" and "analysis" in the Chinese industry, but still reveal a minimum fact: the emphasis on "analysis" by Western countries, especially in the US, as the source of large data concepts, is much greater than the Chinese industry's focus on analysis.

This simple analysis of Google's search results coincides with our understanding of the current state of implementation of China's large data companies.

2 China-style large data and analysis of the status quo

The status quo of large-size data and analysis in China

The only difference between the so-called "big Data analysis" and the "Small Data analysis" is the amount of data and the amount of data required to store, query, and analyze throughput. In essence, "large data analysis" still needs data analysis to find out the status quo, to find the root causes of the status quo, and through the model and prediction analysis technology to improve the prediction and optimization, and to achieve business operations in all areas of continuous improvement and innovation. To discuss the current situation of "large data analysis", we must first understand the application of "data analysis" in China.

Domestic enterprises, whether they are state-owned companies or private enterprises, really in the business decision based on data analysis results, mainly in the banking, insurance, telecommunications and electrical business and several other industries. For example, with the most abundant it budgets and the most powerful people, the main banks are currently importing data analysis. Small and medium-sized banks are still in the waiting and learning stage, personnel and capacity building is starting stage. The application scope of the data analysis mainly concentrates on the credit risk, the process optimization, the marketing, the cost and the budget and so on several aspects, the depth is fair, but the breadth is general, has not expanded to the operation management all areas.

When it comes to "big data" or data warehouses, the vast majority of companies in these industries have already implemented various data warehouses to manage data. The model of buying medicine and then seeing the doctor completely reversed the cart. The Data warehouse is different from the database, and its mission is to analyze it. Without analysis, what is the use of the warehouse? One of the big four banks, a large state-owned bank, began to spend hundreds of millions of yuan in the late 90 's IT budget, the construction of "large data Concentration" project, affected by the bank, other domestic banks set off a wave of data concentration. Even business intelligence was not yet introduced into China's it concept, not to mention data analysis. 15 years later, are these data in the center still there?

As for the manufacturing, construction and trading industries that support the country's huge GDP, they have not yet seen a scale in the use of data analysis for business decisions. Its IT spending is still focused on infrastructure and the process of software suite areas (such as ERP,CRM,HRM, SCM, etc.), some enterprises began to import business intelligence (reporting, mapping, management cockpit), and data analysis application is far from the stage of scale development. For example, China's manufacturing enterprises, starting from five or six years ago, "Six Sigma", "Total Quality Management", "lean production", although these initiatives on China's manufacturing, China's creation and other essential changes will take some time, but in terms of improving corporate decision-making capacity and management level, these initiatives have indeed played a role, For Chinese companies from the brain to the use of data decision-making, the essential change laid a foundation.

The reasons for this situation are as follows:

1. Sources of power of enterprises

Data analysis is the real number one project. The mission of analysis is to improve decision-making. The first person responsible for the decision is the top management of the enterprise. State-owned enterprises, especially large and central enterprise, professional managers system is not perfect, the Chairman, general manager of the level of appointment by the department door rather than economic departments to decide. The personnel appointment system of "speaking politics" determines the complexity and particularity of enterprise decision making, and the popularization of scientific management method and decision means depends entirely on the degree of recognition of these means by the highest leaders of the enterprise.

In addition, the data analysis brings not only analysis software and analytic methodology, but also needs the decision, the operation carries on the corresponding improvement and the adjustment, we commonly call it "the change". Any change will bring about the matching risks and benefits. The power structure of state-owned enterprises and private enterprises, foreign companies are very different, even if the general manager decided to change, but also to solicit the authority of the internal departments of the recognition and acceptance, the difficulty of change caused us to see and hear the "transformation is extremely difficult", "as big parents to hundreds of thousands of mouth responsible" and other sensational grievances of the ego vindicate. Do not say data analysis, even expelled a few performance poor staff, accidentally will offend people, serious also endanger wushamao, reform is difficult.

In contrast, private enterprises and foreign companies in this area of change to be agile, a lot faster. For example, Apple, many years ago began to import the JMP data analysis platform, with the help of our multinational team from the building of data analysis capabilities, normative data analysis process, the introduction of advanced data analysis methods, until the production and development of the data analysis of global standardization and other work. The whole process, for several years, involves the transformation of large institutions, people, methods and processes, but is smooth and orderly. There was also the death of Steve Jobs, the inauguration of the new CEO, and all the big business events that were enough to disrupt everything, but the process of importing data analysis was unaffected.

2. The operational capacity of the Enterprise reserves

Capacity reserves are also a key element. Even if management is determined to be consistent, ambition, a major change can fall, depends on whether the team can be upgraded and changed. Although willpower is important, physical strength is the key. Data analysis has a high requirement for participants in several aspects such as statistics, probability, mathematics, computer, business understanding and so on. Although "ability can be cultivated", but our many years in the domestic data analysis to import the project, the most challenge is the personnel training and process change.

Taking the telecom operation industry as an example, boss system, various business systems and data warehouses for many years, data analysis for customer behavior understanding and promotional products have also made the industry's data analysis applications far more than most other industries. However, the primary problem that the telecom industry faces in the large-scale data analysis is still the establishment of the professional Talent Reserve and the regulations, decision-making process and cultural system related to the data analysis.

We see more in the market, is the IT department-led data analysis project. The project name is the data analysis, but the content is careful to understand, often is the Data Warehouse + Enterprise report. is not a traditional financial three-table, but a chart for displaying core KPIs. "Data analysis" is not understood, the report and mapping as "analysis" is the root of this situation.

3. Market segments and competitive pressures

The changes in the market competition between different enterprises are very different and interesting. For example, three barrels of oil, to establish a competitive approach, is to find oil fields, the acquisition of gas stations, the use of monopolistic policy advantages to elevate the industry entry threshold. The three telecom operators, some years ago, had subsidiaries attacking each other, or even developing a fight to cut the light network. And Huawei and ZTE's competition, some years ago in addition to the saliva war, but also each other to dig each other technical team.

The policy monopoly industry, despite the pressure, has been slow and inefficient in terms of improving productivity and production efficiency. Highly marketable areas, such as home appliances, automobiles, consumer electronics, Chinese laborers, medicine and other fields, to the data analysis as the representative of the "advanced ability" of the acceptance of a lot higher.

To sum up, the application of data analysis in business circles of our country still stays in individual industry and individual application stage. However, while the process of importing data analysis is so difficult and frustrating, I still think that with the promotion of the marketization process of various industries in China, as the Internet and data analysis technology constantly subvert the traditional industries, "data analysis" or "Large data analysis" will become the key means for Chinese enterprises to break through the barriers.

3 data size is not really important.

The data is not big, but it doesn't matter.

As long as the data, there must be a story. Rather than pursuing large data unilaterally without matching ability, it is better to act immediately and extract value from the small data held at hand and around it, thus laying the foundation for a digital decision in the real big data age.

From the microscopic point of view, we take the Chinese retail and consumer goods industry as an example to see the application of data analysis in this area:

1. The analytical tools used within the enterprise are non-standard, scattered —--such as the analysis of the chart;

2. Focus more on data acquisition and management than on customer-oriented predictive modeling and data mining. The former is it work, the latter is the process of obtaining value from the data

3. The business and management decision-making mechanisms that have not yet been truly operational or have been built in the company to sustain analytical capabilities, analytical processes, and data analysis.

And based on our years of experience in providing JMP data analysis strategy development and project support for Chinese enterprises, our suggestions are:

1. Beginning with the application of project-level data analysis, the standardization analysis process and business decision system of the project group level are gradually ready. Develop a team with basic analysis and application ability through the project;

2. Extend project analysis experience to the departmental level and expand the value chain of data analysis-value acquisition-business decision making. Data acquisition and management is carried out according to the needs of departmental data analysis applications. Develop the process of data analysis and business decision with the help of departmental reference, and unify and advanced data analysis platform and business Practice database

3. From the departmental level to the enterprise-level application, the vertical and horizontal two dimensions are expanding, requiring the high participation and institutional support of the enterprise management, promoting the transformation of culture and mode based on data analysis, and establishing a long-term data analysis strategy to support these changes.

4. As for the data is not big enough, is not the need for "cloud computing", all look at the business needs and set!