1. Data management status and improvement plan
Recently, as data emerges as a key factor in corporate strategic decision-making, interest in data integration and data quality is increasing. Data standardization is essential to ensure data quality.
However, the following realistic problems in data utilization are obstacles to delivering accurate information to users in a timely manner.
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| The need for data standardization |
Due to the lack of data standard policy, data with the same meaning is duplicated under different names in the process of information system development and operation, or data with the same name is calculated with different logic between systems and used with different meanings.
□ Lack of timeliness in providing information due to delay in understanding the meaning of data
Due to non-management of standards for data names and data definitions, it is difficult to provide accurate information to information users in a timely manner by wasting a lot of time in identifying necessary data when new information requirements or information requirements change.
□ Difficulties in data integration
There are cases where unit system-oriented data standards are applied or not applied, so when building a system based on integrated information requirements for company-wide data, such as building a company-wide data warehouse, it is difficult to understand the meaning of data and to determine whether data is duplicated. there is
□ Difficulty in information system change and maintenance
Due to the lack of data standard policy, it is difficult to grasp the meaning of data when changing or maintaining information systems, and it is difficult to determine whether existing data can be used when new information requirements are reflected, resulting in a lot of effort in maintenance.
□ Cause of data problem
□ Simultaneous information system development
□ Unformed company-wide data management mindset
□ Absence of company-wide data management personnel
□ Absence of enterprise data standard management tool
Data standard management requires the support of many automated systems, such as data standards, data standard compliance checks, and data standard inquiry and utilization. When developing an information system, manual application of data standards and compliance checks were performed, but there are many difficulties in standard management methods that are close to manual work in the operation stage.
□ Data management improvement plan
Since data is a key element for a company’s strategic decision-making, enterprise-wide data standardization activities are required to achieve data integration and data quality.
2. Expected effect of data standardization
When company-wide data standardization activities are performed, business users can use accurate data and make the right decisions. This has a great influence on the competitiveness of a company.
□ Increased clear communication due to name unification
By using the same name for the same data, clear and prompt communication between various layers such as developer-business, operator-business, and operator-operator is possible.
□ Reduction of time and effort required to locate necessary data
By using standardized data when new information requirements arise, it is possible to quickly grasp the meaning of data and the location of data, delivering accurate information to information users at the desired time.
□ Improvement of data quality due to application of consistent data format and rules
Data quality can be improved by preventing data input errors by applying data formats and rules in accordance with data standards. In addition, by using data based on standards, errors in decision making due to the use of incorrect data are reduced.
□ Reducing data conversion and refining costs when interfacing data between information systems
If data from other systems is needed in a data integration project or in an individual system, if the data is managed according to the company-wide data standard, it can be used as it is without performing a separate conversion or refinement process, so no additional cost is incurred.
Source: Korea Data Industry Promotion Agency (https://dataonair.or.kr/)
