How to proceed with MDM (Master Data Management)

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ishanijerin1
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Joined: Tue Jan 07, 2025 4:50 am

How to proceed with MDM (Master Data Management)

Post by ishanijerin1 »

The appropriate way to proceed with MDM will vary depending on the size and industry of your company. Here we will introduce a general approach. Let's put it into practice after understanding what you need to do at each stage.
Current situation analysis and goal setting
Since the objectives of managing master data vary from company to company, the first step is to analyze the current situation. It is first necessary to clarify what information exists in each department's system, then identify issues and determine the purpose for which MDM should be implemented.

For example, if a company operates multiple e-commerce sites, information tends to be scattered across each store. If you want to collect information on customers, products, etc. held by each store, it is inefficient to inquire each time. In such cases, if you implement MDM and centrally manage master data, you can quickly access the information you need.
Organize and prepare your data
Once the objectives have been set, the data is zalo database organized. If the data is divided into several layers, it is desirable to decide up to which layer the data will be used as master data.

For example, suppose that your company manufactures products that are divided into three layers: "in prototype", "sales target", and "in production". In this case, smooth data management is possible by deciding up to which information will be managed as the company's master data and which information will be managed individually in each department's system.

When collecting data, try to eliminate data that is meaningless to manage. If old or unnecessary data is mixed in, proper MDM cannot be performed. It is important to perform "data cleansing" to collect only organized and accurate information.

Data cleansing is also called "data cleaning" and refers to the task of increasing the accuracy of data. In addition to discarding old data and updating it to the latest data, it is also necessary to correct errors and delete duplicates.
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