How to think about data management

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When tackling data management, it is important that the entire company works on it. We will explain specific methods for doing so.
A company-wide initiative, including management
Data management is not something that should be left to specialist departments such as the systems department, but is an issue that should be addressed by the entire company. It is important to make all employees understand the importance of data management and to smoothly proceed with the entire project, and a company-wide effort including management is required.

To raise awareness within the company, it is important to clarify the purpose of data management and how to use the data and paint a concrete image. For example, when viber database dealing with product master data, by clarifying the purpose such as what the data will be used for, whether a data list is required, and whether it will be linked to an EC site or store system, it will be possible to narrow down the method of building the database and the necessary data management solutions, making it easier to compare and consider. In addition, it is important to clarify the resources required to achieve the purpose and the priority of stakeholders, and to communicate sufficiently with the relevant staff. The key to success is to always keep the purpose in mind while working on data management.
Maintain data consistency and quality

When working on data management, whether or not you can guarantee the quality and consistency of data is directly linked to the reliability and business efficiency of your company. First, you need to define the importance of the data and separate it. It
is also important to regularly verify and clean the data and properly dispose of old data. To avoid holding onto excessive amounts of unnecessary data, you can clarify the process from when the data is generated to when it is finally deleted, set a "lifecycle" for the data, and clarify the retention period to ensure more efficient data management.
In this way, it is necessary to establish a process for properly handling data from the input stage to management so that the accuracy of the data can always be maintained, and to work on quality control. This will prevent inappropriate decisions from being made due to incorrect information, and improve business efficiency.