Four parts of enterprise building large data

In the traditional consumption age, the merchant's purchase behavior analysis stops at the purchase. When the mobile internet appeared, consumers bought another action, that is, to share, resulting in changes in consumption habits. The consumer market determines the product and the overall strategy of the merchant, therefore, in the age of the social big data explosion, the industry enterprises have to pay attention to these big data, and increase its utilization rate.

How to analyze these data? To get the real voice of the market, to understand the actual needs of customers. Enterprises can not help but be troubled. "Imagine it" recently organized on the big Data online discussion, Ufida UAP data Platform Product Department senior software engineer Zhang Xin from his project experience to share, how enterprises build large data, processing large data, and how to apply large data, so that the use of large data to bring commercial value.

Zhang's share comes from his technical and project experience in the development of the UAP UDH large data processing platform. UAP Udh can quickly consolidate, store, and centralize the management of different types of massive data, such as unstructured, semi-structured, or structured data. To provide bulk and real-time data processing, data analysis and other services.

Ufida UAP UDH Large data processing platform work flow

Many companies do not know much about big data and how to build large data platforms. For traditional companies, there should be a concrete plan, step-by-step, for the big data, Ms Zhang said. Generally can be divided into four steps:

First, the establishment of a data program to achieve data entry and storage. The first thing the enterprise needs to consider is what kind of data to keep. Different companies, depending on the business model, need to be involved in different data, is more concerned about the product or enterprise operations or the human data resources, these issues need to set up a data plan at the beginning of the consideration. But the data related to customer experience, such as the retail stores of home appliances, the means of transportation used by customers, the accompanying of elderly children, what products to see and what to buy, etc., this kind of customer sketch form of the data needs the enterprise special attention. Perhaps the current data is not yet included in the business system audit, but in the traditional enterprise competition customer experience and service awareness of the future, these data after mining and analysis will produce great value.

Second, the establishment of data management and application platform. On the one hand is to establish good data processing structure on IT infrastructure, such as data distributed storage, Hadoop, etc. On the other hand, enterprises should establish their own data management and application platform, including data collection, database structure, analysis module, API export, etc. It should be noted that the establishment of data management and application platform must start from the company's business and build a suitable platform.

In the area of data center construction, with the advent of cloud computing and data centers, the cost of external data centers has dropped dramatically, and the cost of data storage is no longer an obstacle, and it is not necessary for many companies to build their own data centers.

Third, tailor-build data team. For large enterprises, the team of data mining is relatively advantageous both in cost control and business response mechanism. However, for small and medium-sized enterprises, the self-construction team is sometimes unnecessary, the most important for this type of enterprise is to integrate large data thinking into the day-to-day operation of the enterprise.

In addition, Ms Zhang says companies should develop the right data concepts for the team, such as the diversity of data forms, the role of data in forecasting, the use of distributed storage computing to build data-processing structures, the external impact of data, or the search for external data that affects enterprise development.

Four, customize the external data strategy. What external data can affect the business development of an enterprise, such as the price of a competitive brand, sales strategy, etc. these need to be searched and precipitated in advance. The establishment of external data plans, enterprises can be through public channels or data exchange methods to carry out.

Construction of large data processing platform for Ufida UAP Udh

When the enterprise's large data base work is ready, the data can be targeted management. In the order of data collection, storage, data processing and presentation.

First, data collection. To the data from the network, including the Internet and the organization of the information system to attach the space-time logo, Quweicunzhen, as far as possible to collect heterogeneous or even heterogeneous data, if necessary, can be compared with historical data, multi-angle verify the comprehensiveness and credibility of the data.

Second, data storage. To achieve low cost, low energy consumption, high reliability objectives, usually using redundant configuration, distribution and cloud computing technology, in the storage of the data according to a certain rules of classification, through filtering and to the weight, reduce storage, and add a tag for later retrieval.

Then, data processing. Some industries have data that involves hundreds of parameters, its complexity is embodied not only in the data sample itself, but also in the interaction dynamics between multi-source heterogeneous, multiple entities and multiple spaces, it is difficult to describe and measure the traditional methods, the complexity of processing is very large, and it is necessary to measure and process the dimension of multimedia data such as High-dimensional image. Semantic analysis using contextual associations, synthesizing information from a large number of dynamic and possibly ambiguous data, and exporting comprehensible content.

Finally, the visual presentation of the results makes the results more intuitive to facilitate insight. At present, although the computer intelligence has made great progress, but only for small-scale, structured or class structure of the data analysis, not deep data mining, the existing data mining algorithms in different industries are difficult to general.

Ufida UAP Udh Function--system monitoring

There are a lot of large data platforms in accordance with the above four steps in order to carry out large enterprise data processing work. For example, Ufida UAP Udh, it can quickly integrate, storage, centralized management of different types of massive data, provide batch and real-time data processing services, and data integration and other products to build enterprise-class data warehouse to provide large data platform support, combining business intelligence products and mining visualization products, provide data Analysis Services; Provide the service components management and system operation monitoring in the platform. Built on the udh of reliable storage and data volume and real-time processing capabilities, but also to provide enterprises based on search engines, semantic analysis of accurate, comprehensive, automated monitoring and analysis.

Zhang Xin introduced, Ufida UAP Udh has made an application-public opinion information management system. Through the system can monitor various dimensions of the public opinion information of the enterprise, collect the competitor's intelligence, the industry development dynamic and so on to become own report. It is understood that the current Ufida group UAP Center has used the independent research and development of the public opinion information system to replace the previous Third-party platform services. Zhang Xin told reporters, UAP Udh will also be public opinion information management as a service to provide external.