Creating accurate data reporting between multiple systems.
A leading transportation service provider wanted to improve data quality between multiple systems for accurate reporting.
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Incorrect and error-prone reporting in the legacy system.
The client was finding it difficult to manage data quality between multiple operational systems. Data from legacy systems had a lot of issues and were the cause of incorrect reporting, and the client was looking for a better option.
Big data analytics and root cause analysis.
We analyzed and setup a data analytics engine to reconcile data from various systems, improve data mapping, and correct any data discrepancies. We set up multiple checkpoints and issue flagging methodology at every data handshake. Prioritization and root cause analysis of various events was done by the system for better insights.
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Improved reporting accuracy with the central data repository.
The client gained a central repository with cleaned and mapped data for analysis. This improved input data accuracy resulting in inaccurate reporting. The client was also able to implement automated data reconciliation for downstream processes which improved business agility.