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SAP BDC Architect

ramaporanki
Explorer
418

What approach have people taken for handling data quality issues when integrating multiple S/4HANA systems into Datasphere?

What approach have people taken for handling data quality issues when integrating multiple S/4HANA systems into Datasphere?

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Atul_Joshi85
Active Contributor
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378

When integrating multiple S/4HANA systems into Datasphere, the biggest challenge is inconsistent master data across systems. The approach we’ve seen work best is a layered one:

  • Master Data Governance (MDG) at the source to enforce validation rules and harmonize customer, supplier, and product records.

  • Semantic modeling in Datasphere to align meaning across systems so analytics don’t break when fields differ.

  • Data federation instead of bulk ETL, so you avoid duplicating bad data and always read the latest state.

  • Data quality monitoring dashboards to catch anomalies early and feed corrections back into MDG workflows.

This combination keeps governance tight, avoids data sprawl, and ensures that integrated analytics reflect a single, trusted version of the truth.

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Thank You Atul for detailed explanation.  If the data from different s/4 HANA systems needs a lot of cleaning or matching before we can use it, would federation would still be the better option ? or would you replicate the data first, clean and harmonize it, and then use it for reporting ?

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