1. The background, definition and characteristics of the
data center stage 1. The background of the data center stage generation
After 2010, with the rapid development of the mobile Internet and the Internet of Things, data has exploded and demands for various data services continue to emerge. However, under the traditional IT construction method, most of the various information systems and databases of the enterprise are independently purchased or constructed independently, and it is difficult to connect the data deposited in the old and new IT systems, resulting in the formation of "data islands" and "data chimneys" within the enterprise "It is not easy to form shared data services that are fragmented and fragmented, and cannot meet the demands of enterprises for cost reduction and efficiency enhancement and high-quality development. Therefore, it has become one of the biggest pain points for enterprises in the process of digital transformation. Under the increasingly urgent needs of enterprises for data services and sharing, the data center, which focuses on building a data asset system and releasing the value of data assets, has been pushed to a broad stage. Therefore, the data center is the result of the natural evolution of the digital transformation process. .
2 Definition and characteristics of data center
In today's increasingly complex enterprise IT architecture, how to quickly integrate data assets, discover the value of data, and form diversified data service capabilities to provide support for enterprise production management, refined operations, and efficient decision-making. We urgently need a set of data management and service mechanisms. The data center is a set of sustainable "use the data of the enterprise" mechanism. It is based on the company's unique business model and organizational structure, supported by tangible products and methodology, to build a set of continuous data into assets and A mechanism that serves business, operation, and management decision-making. With its diversified data service capabilities, unified data standards, and process specifications, the data center accelerates the process of business digitization, data assetization, and asset servicing, and helps companies realize data interconnection, resource coordination, data management, and data Integration and sharing.
The characteristics of the data center: full, unified, and connected, as shown in Figure 1 below. 
Global data refers to the collection of all the data resources of the enterprise and the complete presentation of all data resources. The goal of global data integration is to provide users with one-stop data synchronization and data processing capabilities, allowing users to pass simple and efficient data integration interfaces The one-stop operation to complete data development and operation and maintenance work, and can effectively reduce operating costs, global data is the basis for building data applications; unified specification is to make data follow the same standard, and provide a unified and open data service interface, Let more front-end applications share the standardized data capabilities provided by the middle station (such as data APIs, data tags, data monitoring, etc.); the connection is to integrate all the data of the entire enterprise, open up island data, and eliminate inconsistencies in data standards and calibers The problem. Through the connection, the integration of different technical architectures, IT systems and data of the enterprise not only protects existing investments, helps enterprises to mine the value of historical massive data, and at the same time integrates advanced digital technology with enterprise agile operation and lean management to reduce the enterprise The complexity of data management and operation realizes future-oriented common value creation.
2. The main value of
the data center In the customer-centric era, the data center plays an important role in digital transformation, bringing huge value to enterprises in terms of customer insight, business innovation, and efficiency improvement. Specifically, the main value of the data center includes the following three levels:
1. Customer-centric and insight-driven firm action
In the era of customer-centric, customer concepts and behaviors are fundamentally changing the way companies operate and how they interact with customers. The core goal of the construction of the data center is the continuous and large-scale innovation with customers as the center. The emergence of the data center will greatly enhance the application capabilities of enterprise data, transform massive data into high-quality data assets, and provide enterprises with more Deep customer insight to provide customers with more personalized and intelligent products and services.
2. Based on data, quickly build services and accelerate business innovation. There is a huge amount of data in an enterprise. Only by relying on algorithms and data analysis can accurate insights be generated from the huge amount of data and applied to production and operations, thereby accelerating business innovation. In addition, the data center provides standard data access capabilities, simplifies integration complexity, promotes interoperability, and quickly builds data service capabilities, accelerates business innovation, and improves business adaptation. The data center also plays an important role.
3. With efficiency as the goal, full-factor data-based operations, to achieve continuous value-added enterprise data assets. The goal of the data center is to continuously meet the rapidly changing user needs of the front-end, and to better support business development and innovation through data-based operations, continuous delivery, and efficiency improvements, and to drive the digital transformation of enterprises. In the face of the complex and fragmented massive data, the data center can not only help enterprises aggregate internal and external data, revitalize the full amount of data, but also quickly build a variety of data services, create continuous value-added data assets, and realize data To drive decision-making and operations, and continuously deepen the digital transformation of enterprises.
3. The overall structure of the
data center The overall structure of the data center is shown in Figure 2 below. The data center is a complete system between the data base cloud platform and the upper data application. The data center shields the technical complexity of the underlying cloud platform, reduces the demand for technical personnel, and makes the cost of data use lower. Through the data aggregation and data development of the data center, the establishment of enterprise data assets and the formation of a data system. Through data asset management and data service management, data assets are transformed into different data service capabilities to serve various businesses of enterprises. Data security management and data operation systems ensure that the data center can operate in a healthy and continuous manner for a long time. The data center connects internal and external users through various data applications, providing them with rapid decision-making response, refined operation and service support, etc., making data business-oriented and better driving business development and innovation. 
1) The data base is an important foundation for the birth of the data center. Digital transformation is the use of digital technology to digitize all aspects of the enterprise
The process of optimizing the allocation of prime resources and reorganizing and reforming business processes and production methods to improve the economic efficiency of enterprises, in which digital infrastructure is the production tool, and data is the means of production. Taking cloud computing as the core, integrating artificial intelligence, big data and other technologies, innovating application development and deployment tools, can accelerate the circulation, collection, processing and value mining of data, and effectively improve the productivity of enterprise applications. Nowadays, it is a general trend for enterprises to go to the cloud. However, due to the complexity and diversified needs of the business, enterprises often have different cloud environments such as private cloud, public cloud, and hybrid cloud, and multi-cloud management has emerged. On the basis of multi-cloud management, it can not only gather internal and external data resources of the enterprise, but also integrate with the existing business process, operation management, security management and control systems of the enterprise, and achieve the best through unified standard data services and resource allocation , The safest configuration and efficient operation, improve performance and availability 3.
2) The data center is to make the data continue to be used, and through various tools, methods and operating mechanisms, the data is transformed into a service capability to serve the business of the enterprise. Data aggregation is the entrance of various data resources in the data center. The data center itself does not generate any data. All data comes from business systems, logs, files, networks, etc. These data are scattered in different network environments and storage platforms, which are difficult to use and generate business value. Data aggregation is the core tool that the data center must provide. The data of various heterogeneous data sources can be conveniently collected into the data center for centralized storage to prepare for subsequent processing modeling; data development is through a complete set of data development And modeling tools, provide different models and service functions, quickly process data into a form that is valuable to the business, and provide it for business use; the data system is the flesh and blood of the data center, with data aggregation and data development modules, the center Once you have the basic capabilities of traditional data warehouses, you can do data aggregation and various data development, and establish an enterprise data system. In the era of big data, the amount of data is large and the growth is fast, and the business's dependence on data will become higher and higher. Data consistency and reusability must be considered. Vertical and chimney-like data and data service construction methods are bound to be impossible Exist for a long time. Different companies have different data due to different businesses, and the content of data system construction is also different, but they are generally similar. They are generally constructed in accordance with the standards of source data, unified data warehouse, label data, and application data; data asset management is established through the data system The data assets that come up are more technical and difficult for business personnel to understand. Asset management is best to show the company’s data assets to all employees in a way that all employees of the company can better understand (of course, permissions and security control must be considered), and data asset management shows the company’s data assets in a more intuitive way , To enhance the company’s data awareness; the data service system is to turn data into a service capability, through data services to let data participate in the business, and activate the entire data center. The data service system is the value of the data center. Most data services can be quickly customized through the capabilities of the middle station, such as service management and control, authentication, measurement, scheduling and other functions; the operation system and safety management are the foundation for the healthy, safe and continuous operation of the data middle station.
3) The important focus of the data center is on the enterprise data application scenarios. Data application scenarios are not only the starting point of the data center, but also the cornerstone of innovation. Different companies in different industries have different data application requirements at different stages of development. The priorities of specific application scenarios are also different, and the scenario data supported at different stages also require constant iteration. The data center has various interactions with users inside and outside the enterprise through scenarios such as data collection, development and modeling, data asset transactions, data services, data operations, etc., to achieve the integration of enterprise data center services, and drive capacity building for refined business operations. Consolidating the data foundation and forming a positive self-circulation promotion relationship between data and business will not only comprehensively promote the flourishing business innovation within the enterprise, but also provide better external services and drive the digital transformation of the entire enterprise.
4. Challenges in the construction of data centers and countermeasures
The challenges faced by data centers include: 1) Sort out business scenarios: figure out how data centers generate value for the business. 2) The priority strategy for building a data center: The demand may be large and complete, but we cannot directly build a large and complete data center. The priority should be prioritized according to business importance. 3) Data governance issues: Data governance that is independent of business is rarely successful. Big data standards must have (data asset catalog). The common latitude and common business models are extracted through the data asset catalog. Data governance needs to be closely integrated with business scenarios.
The construction of the data center faces many challenges, and the road is difficult and long-term cannot be achieved overnight. Here we need to grasp the following countermeasures:
(1) The attention and support of top leaders are needed. First leaders need to recognize the value of data in the platform. Data is an important support for business, an important driving force, and can lead the development of business. In addition, the construction of the data center must have a strategic plan, and the corresponding organization, system, process, and resources must be guaranteed. Therefore, only the support of the top leader of the enterprise can promote the continuous construction of the data center.
(2) Data ecological construction thinking is needed. The construction of the data ecosystem can provide a better competitive environment and resource allocation efficiency for the management, talents, sales and partners of the enterprise, and realize the strategic transition of sustainable development. And through open data ecological cooperation, innovatively connect the upstream and downstream industrial chains, maintain the stock market, and expand the incremental market;
(3) The concept of a data lake needs to be established to promote the integration of data, business and technology, and realize cross-regional, cross-system, cross-level, cross-department, and cross-business collaborative management and services.
(4) Pay attention to data governance. Data governance is a key link in the construction of data center. Data governance must not only solve the problem of incomplete, inaccurate, and useful data, but also let the business team know the company's data capabilities and data asset standards, so that everyone can reach a consensus concept of co-construction, sharing, and standardization, and ensure data flow And applications are based on the same standards and foundations, and truly use data well, accurately, and thoroughly, so that data can continue to empower businesses and help enterprises' digital transformation.
5. Six-step approach to the implementation of
data center. Data center technology is highly integrated, difficult to construct, and there are certain construction risks. How to successfully land requires efforts from the following six aspects: (1) Establishing a clear data strategy is data centering The first step of construction (2) Data technology and platform capabilities (including artificial intelligence) are the basis for large-scale application of data (3) Finding valuable business scenarios and use cases, and applying data is the key (4) Establishing enterprise data Awareness and cognition, building a data culture is the soil (5) Let the data team and the business be closely integrated, value-driven (6) Continuous operation, rapid iteration, and continuous intelligence.
The data center can help companies integrate internal and external data resources and platform capabilities, open up corporate data, and provide data service capabilities that previously cannot be provided by a single department or single business unit, so as to realize greater value for data.
Conclusion
In the customer-centric era, the data center plays an important role in digital transformation. The data system based on the data center will be at the core of enterprise applications, and it will help companies in the aspects of cost reduction and efficiency increase, and refined management. Come huge gains. The future application trend of the data center is to empower small and medium-sized enterprises, reduce their construction costs, give play to the value of data-driven business innovation, and drive the digital transformation of the entire industry.