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This article will explain in detail how CTO/CIO manages data. The content of the article is of high quality, so the editor will share it for you as a reference. I hope you will have some understanding of the relevant knowledge after reading this article.

In the process of digital transformation, the first thing enterprises need to do is to break through the data chimney, which involves specific data governance. The purpose of data governance is to provide guidance for the business. Mature data intelligent managers will start from the perspective of application, think about the dimension of data governance from the overall perspective, and complete the data governance work in stages in the form of a project. Integrate multiple application requirements into data governance. At the same time, it is also necessary to control the changes of business scenarios and IT systems.

Whether they are enterprise technicians, business personnel, middle and senior managers or data service providers, they should be aware that data governance is a continuous and long-term work. The initial data governance is to solve the pain point of an application, but in the long-term process of data governance, we need to examine whether the technical architecture can remain stable and whether it can run stably in accordance with the original intention of architecture construction. At the same time, the results of data output should be tested by the application scenario, and it can not be considered that data governance is invalid or effective through a single result in the process of governance. Data governance is a systematic project, which requires participants to have a deep understanding and participate in it.

I. steps of data governance

In essence, data governance is a systematic process, and the work should be carried out on the premise of service application scenarios. In the governance process, CTO/CIO needs to plan in advance the scenarios that may be applied, and use these business scenarios to constantly verify and guide the data governance work of technical departments, so as to ensure that the results of data governance are effective.

Data governance is generally carried out in four steps.

1. Data integration

The first step of data governance is data integration, that is, according to business needs and characteristics, the enterprise internal management system and external data fusion. Data fusion should completely cover the business scenario. The working principle of data integration is to integrate business data from different channels through a variety of data tools and maintain long-term stable operation.

In the case of unmaintained data fusion caused by personnel changes or business adjustment, on the one hand, data fusion needs to be carried out in a standardized way, and on the other hand, the missing data in the business scenario can be supplemented by professional data tools. to ensure a comprehensive connection of the data, and provide a solid guarantee for later business changes and system maintenance.

two。 Data governance

After the fusion of the internal and external global data of the enterprise, the data needs to be managed next. First of all, you need to design a data governance model, including the establishment of data standards. The establishment of data standards should go deep into the product and business system, in order to provide a stable foundation for later intelligent data management. Data standards include different aspects, such as data application standards, business data standards, data practice standards.

3. Data service

Data services are prepared for usage scenarios. The construction data center will go through the process of integration from local data to global data, and covers all business systems of the enterprise. On the basis of huge data, specific data services will be formed according to different business scenarios and product categories. These data services can provide business units with user portraits, group tags and other content to help marketing. In addition, analysis methods, algorithm models and data capabilities of user clustering and clustering are also included in the data service.

4. Data security

The data should not only meet the internal use of the enterprise, but also have contact with the outside because of business cooperation. Therefore, it is very important to ensure data security. Based on the data center architecture, different forms of security settings can be made for different data types. The data security service center constructed by the hierarchical data protection mechanism of the data center can protect the data from different systems. When cooperating with external data, the secure interaction of private data can be completed through the public space built by the data center.

In a word, data security is guaranteed through the specific mechanism of the data center. Through the data center, we build an external output platform, formulate relevant measures according to different types of data and the degree of privacy, and save the data in a relatively safe and controllable environment. Personnel of different departments can share and interact with internal and external data on this platform.

II. Construction of data governance standards

The formulation and introduction of data governance standards will help enterprises to better carry out data governance.

1. Data governance regulations issued

Whether it is the financial industry, retail or traditional industries, these mature industries will have a relatively complete set of data standards, and define the data from the business characteristics of the industry. This set of data standards is common to the industry, and enterprises can also use industry standards as a reference for data governance.

two。 Data governance advice and guidance

With the advance of the digital wave, the relevant standards of data governance are also constantly improving. For data governance, the state has also issued some guidance, which can be used as an important reference for enterprises to carry out data governance.

3. Full data coverage

Full data coverage includes three aspects: full coverage of data governance, full coverage of data architecture and full coverage of business areas.

Full coverage of data governance means to build systematic data governance tools when thinking about data governance. The data governance model built by the data governance team should not only conform to the functions of the platform, but also take into account the way of data acquisition, data type and content, and the way of data application, which can provide ideas for improving the data governance model and adjusting the direction of data governance.

The full coverage of data architecture includes not only the traditional data warehouse, but also the processing of relational database. The source of thinking of data governance should be considered from the application direction, the architecture of data governance will be more and more complex, and the coverage will be wider and wider.

Full coverage of business areas means that data governance should cover all business scenarios, including routine business data, such as bank loans, savings, wealth management, and more detailed business contents. such as bank educational financial products, tourism financial products and so on.

With the continuous change of consumption scenarios, new business areas will continue to appear, and there will be more and more directions of data governance, which requires enterprises to comprehensively carry out data governance.

4. Application-driven data governance

The purpose of data governance is intelligent applications, and data governance and data applications must be constantly integrated and transitional. In order to have a purpose, data governance needs to formulate good standards and methods of data governance from the very beginning, and gradually implement it from the starting point of application in the process of implementation.

So much for sharing the data on how CTO/CIO manages the data. I hope the above content can be helpful to you and learn more knowledge. If you think the article is good, you can share it for more people to see.

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