Interpretation: In 2020, Huawei Data Management Department published "Huawei Data Road", which systematically expounded the main work content and current progress of Huawei Data Management Department.

As an internationally renowned telecom equipment and mobile phone manufacturer, Huawei's disclosure of its internal data flow and data architecture in such a big way seems a bit unusual compared with Huawei's cautious style in security and confidentiality. However, we can get some inspiration from the recommender of this book. Huawei hopes to find some development and breakthroughs in the two weak business areas of cloud and enterprise services, taking its own digital work as a case.

Interpretation: Huawei's data management began in 2007, when there was no digital transformation. The goal at that time: introduce IBM data management framework, start the construction of information architecture and data quality, and incubate data institutions in leading cities. The contents include:

1) Establish a data management framework under the guidance of IBM consultants.

2) The data organization in the business process is gradually established.

3) Initially start the information architecture construction of core data.

How is the data management organization established? This is related to IBM again. Huawei is the boss's study of IBM enterprise management. There are many introductions on the Internet, so I won't mention them here. In order to standardize the internal information construction, IBM introduced the concept of enterprise architecture EA to Huawei. Organizationally, the Enterprise Architecture Department was established. The IBM enterprise architecture is divided into four parts:

Business architecture: defines the business capabilities that an enterprise hopes to achieve under the guidance of the overall strategy of the enterprise and the relationship between them, which can help the enterprise develop its business and realize efficient operation.

Application architecture: it is the high-level application division of information system, which guides the construction and implementation of the whole information system. The application architecture is based on business architecture and industry best practices.

Data architecture refers to the organization and management of data from the perspective of cross-organizational application systems, including the strategies, models and processes for processing, storing, transforming, integrating and distributing data in the whole data life cycle, as well as the architecture schemes supporting these strategies, models and processes.

Technical architecture: it is a technical platform architecture based on the idea of service-oriented architecture, which realizes the horizontal connection of information, applications and processes and supports the optimization and promotion of application architecture; Define the relationship between various information infrastructures, analyze the development process and technical requirements of information systems from macro and micro perspectives, and provide an achievable basis for safeguarding and supporting applications and data; Define the technical standard system to support business operation; Establish the relationship between business security requirements and security requirements according to the security capabilities and functions defined by enterprise or organization requirements; Using various mature technologies, we can realize the visual display of all kinds of data in enterprises, thus effectively supporting intelligent decision-making.

There are four small departments to undertake these four modules: the establishment of data management department to undertake data architecture construction and care responsibilities.

These four organizations are the departments that provide capabilities internally, and any internal IT project construction (also known as change project) needs four teams to provide human participation together.

In addition to the data architecture, the responsibilities of Huawei's data management department have also expanded. From the current point of view, the it department is responsible for data governance (the data analysis function has been expanded during the digital transformation):

Huawei's data governance system framework is as follows:

The above is policy guidance, and the following is IT, organizational and process support. The core in the middle is data architecture and data quality.

Among them, the main business process data access is four horizontal lines (representing business processes): from strategy to implementation; Transfer of commercial transactions to accounting; Product life cycle; Problem solved. Vertical access depends on master data (customer master data, supplier master data, product master data, financial account master data, etc. ) and dimension data (in the data warehouse).

In order to support the company to implement data governance, Huawei has established a company-level data management department within the enterprise scope to formulate policies, processes, methods and support systems related to data management on behalf of the company, formulate strategic plans and annual plans for data management of the company and supervise their implementation. Establish and maintain enterprise information architecture, monitor data quality, expose major data problems, establish a professional qualification management system, improve the company's data management capabilities, and promote the establishment and dissemination of enterprise data culture.

Explanation: Responsibilities of the Group Data Management Department

In order to implement the data management objectives set by the company, all business areas should establish substantive data management professional institutions, which report to GPO (the global process leader of all business areas, usually the business director) in solid line, assume the data management responsibility of GPO, and report to the company's data management department in dotted line. Comply with the company's unified data management policies, processes and rules.

Interpretation: The data management departments of each subsidiary are administratively subordinate to each subsidiary, reporting to the leaders of the subsidiary, and the dotted line is connected with the data management department of the group, so that the data management systems of each company are unified in standards and languages.

Huawei's data organization mode of combining reality with reality is the key to ensure that data work is fully involved in business and can be effectively implemented in application systems.

Interpretation: The data management department of subsidiaries is closer to the construction of business and application systems.

Summary: the responsibilities of the data management department

System establishment program

Responsible for formulating strategies, plans, policies and rules for data management; Responsible for the construction of data management system; Data architecture and core data asset management; Ensure the data quality level of the company.

Interpretation: Policy formulation, systematic construction of data specialty

Competency center

Constructing methods, tools and platforms for data management; Responsible for the development and construction of professional competence, including data architecture, data analysis, information management and data quality management.

Interpretation: Competence center, many enterprise data departments can already do it. After all, this is the professional ability needed for data work.

Business data partner

Business-oriented, providing data solutions to solve the pain points of business data; Support business data requirements; Provide standardized master data/basic data services for business.

Interpretation: Data representation has penetrated into all transformation projects to support business changes.

Cultural advocate

In the company, the pursuit of Excellence, "who creates (inputs) data, who is responsible for data quality"; A culture that supports business decisions with data.

Interpretation: In traditional enterprises, data needs long-term publicity through cultural work, so that the value of data can penetrate into everyone's mind.

In different construction stages of data work, different virtual data teams are set up according to different scenarios, such as information architecture construction working group, data quality implementation working group and metadata working group. To ensure the orderly development of cross-domain data work.