How can you manage ERP data from creation to archiving?

Providing management steps applicable at each of the 5 stages of the data life cycle: A-Data creation. -> Data accuracy checks -> Add validations to prevent incorrect data entry B-Data processing and storage. ->Implement appropriate data structure to optimize data and its retrieval ->Check for updates of the ERP system C-Data usage. ->Regular data audits are required here to fix consitency issues ->Check if only authorized users can access sensitive information ->Schedule jobs to regularly back up the data D-Data archiving. ->Implement proper data archiving policies(for ex: archive it for a fixed tenure for any future analysis) E-Data destruction. ->Secure disposal of old data ->Follow data compliance policies applicable to your workspace

To manage data archiving effectively, we should use tools and techniques that enable data migration, retention, and retrieval, such as data extraction, transformation, and loading (ETL) tools, data lifecycle management (DLM) solutions, and data access tools.Just one week back I have arranged to extracted ERP 10 years old database from another country to India.

When creating Data one of the most important aspects is its purpose. Not all data is good data and bad data can be more detrimental to a business than no data at all. When determining the data you will be tracking it is important to have a clear understanding of it's purpose, determine any gaps that could affect its validity and ensure a proper storage for future use and proper disposal once it's use is no longer needed.

Yes I agree on this data maintenance point.we should not let users to maintain customer, vendor & material master data directly in sap .It should integrate with MDM for the creation/updation & deletion.

When mantaining Data we must take into consideration: Authorizations- who will be mantaining this data and if the people involved understand the process. Standardization - is the process for mantaining the data consistent to prevent data corruption. Failsafes - Are there failsafes in place in case errors take place. How robust is your ERP- Not all ERPs are equal and choosing the wrong one could have a negative impact years later as your business grows and the needs change.

For the faster data access S4 Hana will be better in compression to ECC . Generally reports & dashboard by creating job scheduler in sap takes time while fetching data for years.

One thing that is always helpful is a proper data governance guidelines. -Organize your data in meaningful areas. - Document the whole data flow process from extraction to reporting and keep this documentation updated. -Dispose of bad data or data no longer needed. This will prevent false reporting that could affect your business. If required by law to store it then archive it for future acess. But prevent this bad data from corrupting your good data. -Use the proper tools, inhouse solutions are hard to mantain when people leave an enterprise. Trust industry tested systems.

Archiving relevant data is NOT the one and only??. Even data in any physically Archive should be kept in mind for later access: regardless manual, via reports and other. There are some standards to be used for; nevertheless reports might to be extended by a few Code lines to use this in parallel to eable fast access. SAP didn't provide fast access as default. Simple read on Archive (as SAP provides) is therefore not useful and too slow on multiple reasons. On the other hand a data handling strategy is useful to keep data volume small, but effizient for properly analysis a.s.o.

Always follow regulatory processes from your country. If errors are made the important thing is to document the events for auditing purposes. Once data has passed its useful period consider removing it from your reports by archiving or deleting it. Having large amounts of data can be resource intensive on any system plus the involved costs and errors that it can have on reporting software. If you are only using the last 5 years why do you have stored 20 years of data? Of course time is not the measurement but usefulness. So when designing your retention policies always take this into consideration.

Once it has passed its useful period archive your data. Data congestion in any system should always be avoided. By experience I have seen companies have thousands of reports they have not used in years, this has a cost when performing migrations, server costs etc. A happy ERP system is a well mantained ERP system.

Data management is a whole science and to ensure a robust system always remember that good data is clear data. Clear data governance will make your business make better and more informed decisions. Data is data only if it's real data.