SAP Things - Theory -17- How do SAP projects organize data

SAP Things - Theory -17- How do SAP projects organize data

A pot of stale wine to the end of life. nvidia partner Public number: MZ consulting Miscellaneous talk

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We cannot emphasize the importance of data, especially the material data (or what we call product data) that is the basis of all business operations is the most basic and the most important. So let's talk about how to organize data. SAP Outsourcing In my opinion, we need to pay attention to the following points in the data arrangement of SAP project.

1. Data collation is something that needs to be planned and executed at the beginning of the project. smart waste management That is to say, data collection should be organized and collected throughout the project, and a data collection plan should be formulated and implemented from the beginning of the project, including the scope of data, templates (details to each field), collection methods, and import methods.

2. Data collation and material liquidation (the so-called material liquidation is the assets that have been suspended for a long time or have inconsistent accounts, including debt and debt (receivable, payable), fixed assets, inventory) should be carried out simultaneously, so as to ensure that the accounts are consistent when SAP is launched.

3. The data arrangement process is transparent and unified. The goal is for all project team members and project stakeholders to understand how and why the data has changed, including changes in the original and future data, changes in data collation, and what needs to be changed.

4. The process of data management needs to be clearly defined, which data, how to maintain, how to flow, how to notify and how to update should be clearly defined.

5. Configuration of the data team, dedicated personnel, according to the size and complexity of the number to see whether it is necessary to leave the post for special data sorting work.

6. The principle of data collation "should have what should be, should not be in", to avoid redundancy, but also to avoid missing;

7. Everyone has the same understanding of the attributes of the data, the understanding of the key fields should be consistent, and the user understands the logical relationship between the data;

8. Version control, under what circumstances changes need to update the new version, and record the major changes between versions for easy recall and search.

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