Data Middle Office refers to the data technology that collects, calculates, stores, and processes massive data while unifying the standard and caliber.

After unifying the data, the data middle office will form standard data, which will then be stored to form a big data asset layer, and then provide efficient services for customers. These services have a strong correlation with the business of the enterprise, is unique to the enterprise and can be reused, it is the precipitation of the enterprise's business and data, which not only reduces the duplication of construction, reduces the cost of chimney collaboration, but also is the competitive advantage of differentiation.

The goal of the middle office is to improve performance, data-enabled operations, and better support business development and innovation, and it is responsible for collaboration across multiple domains, BUs, and systems. The middle office is a natural evolution of platformization, which brings about a "decentralized" organizational model, highlighting the ability to reuse capabilities, coordination and control, as well as the ability to build differentiated business innovation.

Expanded Information

1, return to the essence of the service - data reuse

Zhejiang Mobile has 2000 basic models as the basis for all data service development, these basic models to achieve the "book with the same text, the same track".

Zhejiang Mobile has made 2000 base models as the basis of all data service development, which can make "books and vehicles have the same text and the same track", and no matter how complicated the data model of the application is, it can always be traced back to the 2000 base tables, which lays the foundation of data verification and cognition, and avoids the cost waste of "duplicate data extraction and maintenance to the greatest extent."

2, the data center needs constant business nourishment

In the enterprise, whether it is thematic, reporting or fetching, the current basic chimney data production mode or project-based construction method, which inevitably leads to the data knowledge is not precipitated and sustained development, resulting in the model can not really become a reusable component, can not support data analysis of the rapid response and innovation. In fact, the last thing the business needs is the stability of the model, a data model if the pursuit of stability and unchanged, to a certain extent, is the same, such an approach will inevitably lead to the emergence of other new similar data model.

Data models do not need to be "stable", but need to be constantly nourished, only in the nourishment from the initial single field to gradually grow into the most valuable model of the enterprise assets.

3, data center is to cultivate the soil of business innovation

Enterprise data innovation must stand on the shoulders of giants, that is, from the data center to start, can not always start from the foundation, the data center is the guarantee of the efficiency of data innovation. Studied machine learning know that there is no good regulation of data, data preparation process is extremely long, which is also a core value of the data warehouse model, such as operators to obtain three months of ARPU data, if there is no fusion model support, you have to own from the bill layer by layer aggregation and correlation, the speed can be imagined.

4, data center is the cradle of talent growth

Originally, new employees to get growth, one is to rely on people to bring, two is to find people to ask, three is to log on to various systems to see the source code, so the learning is more fragmented, in fact, it is difficult to understand the whole picture, can not know what is the most important thing for the enterprise, access to the documentation is also often also out of date.

Now with the data center, a lot of growth problems can be solved, with the basic model, newcomers can systematically learn what the enterprise has the basic data capabilities, the increase in O-domain data is more so that it has a broader vision, with the fusion model, the newcomers can know what the subject domains, from the subject domains into a global understanding of the company's business concepts, with a tag library, the newcomers can get the previous With the data management platform, newcomers can clearly trace the ins and outs of data, labels, and applications. All the knowledge is online and up-to-date, which means a high starting point for newcomers.