When the enterprise informatization develops to a certain extent, data management will inevitably be promoted as an important management field of the enterprise. The quality of data management greatly affects the process of enterprise informatization and determines the final effect of enterprise informatization.
The construction of enterprise informatization basically starts at the department level, and independently builds information systems starting from the actual business needs of the department. With the construction and application of these information systems, each business system has experienced from scratch, from simple to The complex process has also formed enterprise "information islands" one after another. In order to solve the problems of multiple data entry and inconsistency caused by "information islands", and ensure the global consistency of enterprise data, the concept of master data and master data management is proposed .
In general, master data is high-value data that is repeated and shared across the entire value chain of an enterprise and applied to multiple business processes. The basis for information exchange, such as suppliers, accounts, customers, projects, etc., is relatively stable and slow to change, and is a single, accurate, and authoritative source of data.
Based on the previous foreshadowing, we can also answer the question of the subject: the concept of master data is not outdated, and we also need master data in the context of the emergence of new technologies. So Xiaoyi wants to talk about this topic with you.
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1. What is master data?
Master data (MD Master Data) refers to data shared between systems (for example, data related to customers, suppliers, accounts, and organizational departments). Compared with transaction data that records business activities and fluctuates greatly, master data (also called benchmark data) changes slowly. In a formal relational data model , transaction records (for example, order line items) call out master data by keys (for example, order header or invoice number and product code). Master data must exist and be properly maintained to guarantee the referential integrity of the transactional system .
From a reporting or dimensional modeling perspective, master data refers to dimensions or hierarchies based on their organizational or configuration metrics, rather than actual conditions or their own measurements. For example, revenue, cost, and profit are facts, while time, location, customer, and supplier are dimensions.
Second, what is the use of master data management?
For enterprises, the system is built more from the bottom up than from the top down, and there must be a lack of unified planning within the entire enterprise. It is precisely because of the above phenomenon that there are often mentioned information islands and process fragmentation, and master data management is the prerequisite for enterprises to realize internal decision analysis and business process reengineering, and it is naturally indispensable, so take the initiative Data management has the following three benefits:
1. Help cross-departmental collaboration
The maintenance of data assets needs to stand at the height of the company and cooperate with various departments to complete. Master data is data that is reused in various business departments. Its management has both technical and business factors. Therefore, good master data management can help cross-border Departmental coordination.
2. Facilitate data governance work
The initial stage of the master data management project does not involve the transformation of the transaction system. Once the master data problem is solved, the company's data asset framework will be straightened out, and data quality and timeliness will be significantly improved, making it easier to continue to carry out other data governance, informatization, and digitization work.
3. Enabling the needs of digital transformation
Digital transformation requires customer needs as the starting point, and all departments work together. However, the current technology and business division of the industry is obvious, and the master data management process also tempers cross-departmental collaboration. By accelerating the integration of technology and business, a common master data within the company is established. Specifications to ensure data consistency and the consolidation of management reports, which is one of the foundations for the company to make other successful business changes.
3. How to do a good job in master data management?
Master data management refers to a set of constraints and methods used to ensure the timeliness, meaning and quality of data in a subject area within the enterprise in various systems. Enterprise master data management is not only the maintenance of the basic attributes of master data, but also the management of the entire life cycle of master data, including early business data research, master data confirmation, master data modeling, master data system construction and later maintenance Management requirements and a series of management processes. A complete set of master data management methods is conducive to the overall control of master data by the enterprise, and it can also be more efficiently applied to the construction of enterprise informatization.
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1. Master data identification
Master data identification is the premise and basis for the implementation of master data management. Only by identifying the master data of the enterprise can the implementation scope of the enterprise's master data be more accurately confirmed. In the process of identifying master data, it is often necessary to conduct business analysis in combination with the actual situation of the enterprise , and at the same time identify the business data and basic data within the enterprise on the basis of considering the definition and characteristics of master data. Business data usually has high requirements for real-time performance and changes frequently, so most business data cannot be managed as master data. Therefore, the basic data of enterprises and a small part of business data are the main body of master data identification. This paper establishes three analysis indicators to identify enterprise master data.
- sharing . Sharing means that this type of data not only exists in one business system, but exists in multiple systems at the same time, and different systems have businesses that interact based on this data, that is, this type of data is shared in multiple business systems ;
- consistency . Consistency means that the key attributes of this type of data have the same meaning in different business systems. For example, in customer master data, the attribute of customer name should represent the name of the company to which the customer belongs in different business systems;
- stability. Stability refers to the low change frequency of this type of data. In other words, once the data is generated in the system until it is discarded, there is almost no need to modify it during this period. For example, personnel master data, which records a person's basic information, including ID number, name, gender, etc. If such data is not discarded, it does not need to be modified.
By matching enterprise data with the above three indicators, master data managers can initially identify enterprise-wide master data. For the identification of which attribute fields should be included in various types of master data, that is, the identification of metadata, it can still be identified by matching the above three indicators. So far, master data managers can form the first draft of master data categories and metadata categories in the enterprise according to the identification results, and provide a data basis for subsequent master data confirmation.
2. Master data confirmation
At present, the informatization construction of most enterprises has built various business systems, and then the construction of master data, so there is such a situation: most of the business systems that have been built can still run stably without the construction of master data, while Participating in the construction of master data may affect the normal operation of the system due to the transformation of the system. This makes the promotion of master data construction exist the problem that various business departments do not cooperate actively. Therefore, the construction of master data needs strong support from superior leaders, unified coordination and planning, and coordination of various business departments to actively participate in the construction of master data.
After master data managers form the first draft of master data categories and metadata categories, since many business departments are involved, superior leaders need to coordinate all business departments to participate in the confirmation of master data categories and metadata categories. Each business department gives feedback on the first draft based on the needs of the department and the system construction situation. Through repeated communication and confirmation with various business departments, the master data management personnel form the final master data category and metadata category modeling documents according to the feedback and master data management requirements.
3. Master data management system construction and master data modeling
To manage enterprise master data, the construction of a master data management platform is essential. The master data management platform plays the role of data bus in the enterprise, and the architecture of the master data management platform is shown in Figure 1.
This architecture includes data resource layer, data processing layer and application layer. The data resource layer stores the data resources of the entire enterprise. The business database and the main data database are the main carriers for storing enterprise data resources. At the same time, the data resources of the enterprise may also come from the distribution of other data sources. The data resource layer is the foundation of the enterprise. All business development and daily work in the enterprise depend on the stable operation of the data resource layer; the data processing layer is the data bus formed by the master data management platform, which should include data modeling, data integration, data distribution, data maintenance and Core functions such as data quality management play a central role in enterprise informatization. The master data management platform provides operational support for the upper application system by integrating different data resources; the uppermost application layer is the various application systems of the enterprise, responsible for daily business processing.
After the construction of the master data management platform is completed, the enterprise master data managers can conduct platform-based operations on various master data in the enterprise. The master data management platform is mainly composed of four core links of modeling, integration, governance and sharing. It is the data center of the enterprise-wide information environment and provides unique, complete and accurate master data for other heterogeneous application systems in the enterprise. information.
- Master data modeling. Enterprise master data managers model metadata and master data according to the previously confirmed metadata and master data category modeling documents, realize the definition and management of metadata and master data, and generate corresponding database tables in the database at the same time. For subsequent master data management and maintenance;
- Master data integration. Master data integration mainly involves confirmation of data sources of each type of master data, determination of data extraction methods, etc. In order to ensure the accuracy and uniqueness of enterprise master data, each type of master data is required to have only one data source system, and only the data source system can manage this type of master data;
- Master Data Governance . In the early stage of modeling, enterprise master data managers should formulate specifications for each type of master data according to the requirements of enterprise informatization. The specifications must strictly stipulate the meaning of each attribute field of each type of master data and the corresponding field requirements. In the data governance stage, the enterprise master data manager should standardize the data extracted into the master data management platform according to each type of master data specification, so as to ensure that the master data used by the upper application system is accurate, consistent and complete;
- Master data sharing . The master data management platform synchronizes the modeled and organized master data to various heterogeneous application systems of the enterprise for application. This step is often implemented through the interface between application systems.
By building a master data management platform, enterprise master data managers can standardize the management and operation of master data within the enterprise, ensuring the integration and application of enterprise internal data resources.
4. Master data interface specification writing
By modeling master data on the master data management platform, master data integration and master data governance are completed, and finally the master data in the master data management platform is synchronized to other application systems in the enterprise to realize the application of master data. Since it involves data interaction between the master data management platform and various heterogeneous systems in the enterprise, in order to ensure the smooth joint debugging of the data interaction interface between different application systems, it is necessary for the enterprise master data manager to formulate various master data standard interface specifications , to form a standard interface specification document for system developers to use in interface development. The master data standard interface document needs to clarify a series of interface-related information such as the interface format between systems, the type of protocol used, and the format of the interface transfer data file, so as to ensure that the developers of various heterogeneous application systems in the enterprise can smoothly implement the interface code according to the interface specification document. Writing and joint debugging of the interface with the master data management platform.
5. Formulation of master data management requirements
To ensure the reasonable and efficient use of enterprise master data, management requirements for master data are essential. At the management level, it is necessary to establish a master data responsible person system, and assign dedicated personnel for each type of master data to manage and maintain them. Each type of master data manager needs to ensure the accuracy, consistency, uniqueness and integrity of master data within their jurisdiction. Only when there are clear requirements for the management of each type of master data at the management level, can the management of master data within the entire enterprise be carried out in an orderly manner.
4. Cases of enterprise master data management
So many theories and methods about master data have been shared earlier, Xiaoyi would like to help you understand with examples of master data management in enterprises.
The master data management platform EsMDM developed by Yixin Huachen can ensure the consistency, integrity, controllability, versatility and correctness of shared data among various systems, and help enterprises create and maintain a single view of master data, thereby improving data quality , Unify the definition of business entities, simplify and improve business processes and improve business response speed.
For example, it has been applied in the material master data management platform of Nanshan Group to standardize the management of master data such as human resources, finance, materials, sales, equipment, design, technology, production and logistics transportation, and establish Nanshan's own data The management and control team standardizes the data management system and process.
Help complete the construction of six major categories of master data, including human resources, finance, procurement, marketing, indicators and other foundations, including material master data, involving 40+ major categories, 3000+ subcategories, 100,000+ entity data, and realize supply chain, etc. Data docking and sharing of other operating systems.
Another example is the master data management platform that Yixin Huachen helped Chuchang Group build . It mainly builds four types of master data, namely, personnel master data, organization master data, expense master data, and subject master data, to ensure that the business meaning of master data is clear and technical The standards are unified and the management caliber is consistent, so as to realize the sharing and exchange of these four types of master data in various business systems within the group.
A standardized group master data management system has been formed to provide guarantee for master data management; a master data management platform has been built to lay the foundation for the implementation of the master data of the group's secondary companies; centralized management and control of the only data sources such as personnel and organizations has provided the group Further data development and sharing provide the basic conditions.
According to the survey, the master data system construction of most enterprises in China is still in its infancy, and there are still many problems in master data management in China. For example, the importance and complexity of master data are insufficiently understood, and the enterprise's management mechanism for master data is not perfect. From the analysis of the status quo of master data construction in various enterprises, the imperfect master data management methods make the master data management of many enterprises useless. Therefore, master data is still not outdated in the current background of emerging new technologies, and still plays an important role in enterprise digitalization.