With the rapid development of information technology, big data has become an indispensable strategic resource for today's enterprises and units. In this data-driven era, how to effectively govern data and put it into the table has become the key to determining the competitiveness of enterprises or units. This article will deeply analyze the relationship between data governance and data asset ingrescency, and provide practical suggestions for enterprises and organizations to do a good job of data asset ingresming.
1. The intrinsic relationship between data governance and data asset entry
Data governance is the comprehensive, systematic, and standardized management and control of data assets to ensure the accuracy, integrity, security, and availability of data. The inclusion of data assets in the table refers to the inclusion of governed data into the balance sheet of an enterprise or a unit in accordance with certain rules and standards, so as to reflect the value of data assets.
There is a strong link between data governance and data asset onboarding. First, data governance provides a prerequisite for data assets to be included in the table. Only data that is effectively governed can ensure its quality and value and then be included in the balance sheet. Second, the entry of data assets into the table is an important embodiment of data governance results. By incorporating data into the balance sheet, the value of data assets can be intuitively displayed, providing a basis for decision-making of enterprises and enterprises.
2. How to do a good job of data assets in the table
Establish a sound data governance system.
Enterprises and units should establish a sound data governance system, including management systems and norms for data standards, data quality, data security, and data use. Establish a clear data governance policy to ensure data compliance and accuracy, and lay a solid foundation for data assets to be tabled.
Clarify the scope and valuation methodology of data assets.
Before adding data assets to a table, you need to clarify the scope and valuation method of data assets. This includes identifying the types of data that are valuable to the business or organization, and determining how to value those data assets. Through reasonable data asset evaluation, you can ensure the accuracy and fairness of data asset entry.
Strengthen data quality control.
Data quality control is a key part of the process of data asset ingress to the table. Enterprises or units should establish a strict data quality control mechanism to clean, deduplicate, verify and other operations to ensure the accuracy and completeness of data. At the same time, the quality of data is regularly checked and evaluated, and data problems are found and corrected in a timely manner to ensure the quality of data assets in the table.
Strengthen data security protection.
In the process of data assets being added to the table, data security protection cannot be ignored. Enterprises or units should establish a sound data security protection mechanism, including data encryption, access control, data backup and other measures to ensure the security of data in the process of transmission, storage and use. At the same time, strengthen the daily monitoring and management of data security to prevent data leakage and abuse.
Promote the standardization of data asset entry into tables.
In order to promote the standardization and standardization of data assets in the table, enterprises or units should actively participate in the formulation and implementation of relevant standards. By formulating a unified standard and process for data asset ingresming, the efficiency and accuracy of data asset ingress can be improved, and the comparability and transparency of data assets can also be improved.
Third, enterprises must pay attention to data asset management
In today's era of rapid development of information technology, data has become an indispensable strategic resource for enterprises and units. However, not all data resources can be tabled as data assets. From data resources to data assets, and then to "table-in" data assets, systematic management and follow-up are required, which involves a series of management work such as data asset confirmation, evaluation, privacy protection, and transaction circulation. At present, there is no unified norm in this regard in China, and many enterprises are constantly exploring in practice.
The "Guiding Opinions" issued by the Ministry of Finance clarified the construction of a "market-led, first-class, multi-party co-construction" data asset governance model, and put forward a series of tasks, including managing data assets in accordance with laws and regulations, clarifying the rights and responsibilities of data assets, improving relevant standards for data assets, strengthening the use and management of data assets, and promoting the development and utilization of data assets. The implementation of these tasks requires enterprises and units to pay attention to the importance of data asset management.
Data asset management consists of two processes: data resourceization and data assetization. In practice, enterprises can follow the following general steps for data asset management: overall planning, management implementation, audit inspection, and asset operation. There is no strict sequence between these steps, and organizations have the flexibility to develop a reasonable implementation plan at each stage according to their own circumstances.
Fourth, the practical steps of data asset management
Phase 1: Overall planning.
At this stage, organizations need to conduct a data asset inventory and assess data asset management capabilities. The results of the assessment will guide the development of a data strategy and establish an organizational responsibility system to ensure the standardized implementation of the data asset management system.
Phase 2: Management Implementation.
The main goals of the management implementation stage are to establish a standardized system, build a management platform, manage the whole process and innovate data applications. This includes formulating an organization-level data asset standard and specification system, building a big data platform, realizing the whole-process management of data resources, and enriching data services through innovative data applications.
Stage 3: Audit and inspection.
In the audit inspection stage, organizations need to evaluate the results of data resourcing and improve management methods. This includes adapting to changes in business and data according to established standards and specifications, and optimizing data asset management models and methods through regular inspections.
Phase 4: Asset Operation.
The main goal of the asset operation stage is to build a data value evaluation system and operation strategy, and to promote the internal and external circulation of data. By establishing a feedback and incentive mechanism between managers and users, the value of data assets is released.
Nuggets a trillion-dollar market of data elements
The market value of data elements is huge, and the development of data circulation is ushering in a new wave of industry, which is a new opportunity for enterprises to dig gold. Behind the active exploration of data resources by enterprises is the recognition of the "wealth" attribute of data assets. "Entering data assets into the table" is not only the first step to promote data assetization, but also a key step to tap "new wealth".
As a benchmark manufacturer of data asset management recognized by the industry, Yixin Huachen has cooperated with various ecological partners to launch data element solutions, starting from the combing of data resources, focusing on the path of realizing the value of data assets, and accelerating the leap of enterprise data value.
The data element solution of Yixin Huachen covers 6 key steps, and focuses on promoting the three major capacity building of enterprise data resource inventory and table preparation, data product planning and design, data operation mode and equity project incubation in stages and focuses, helping enterprises to achieve agile and efficient data resource inventory, providing one-stop data table entry services, customizing scientific and reasonable data product planning and operation models around enterprise needs, and helping enterprises maximize the realization of data assets.
As a leading provider of data asset management products and services in China, Yixin Huachen not only has a full life cycle data product system and provides a full range of data asset management solutions, but also has deep experience in industry construction and has gathered a large number of channel resources, which can better empower the full scenario of data assetization and activate the value of enterprise data elements.