Oracle Cloud Reports Data Validation Validation of Reports Data is extremely critical and important to the success of every Oracle ERP Cloud

Oracle Cloud Reports Data Validation by Opkey

August 14, 2020
Dimpy Sharma

Oracle Cloud Reports Data Validation Validation of Reports Data is extremely critical and important to the success of every Oracle ERP Cloud testing implementation. Without knowing how or what to validate, or without the proper tools, validation can lead to unpredictable test cycles, long hours, and project delays. Frequently, a project team’s pre-conversion validation plan heavily relies on the review of Payroll mismatch/Reconciliation errors as they occur, resulting in production delays during the project to review and repair records. This is followed by a divided post change validation process mostly manual that involves spot checking records from the front end, Excel dumps, and a manual comparison between legacy and Oracle Cloud reports OR pre-update or post update reports. In contrast, Opkey has developed a way to avoid the headaches traditionally associated with data validation and better ensure data validation success as part of our entire autonomous testing solution of Oracle Accelerator.

Criticality/Challenges Major releases, configuration changes, patching, or any other modification or tuning of applications can bear the risk of a negative impact on your production environment if not tested properly. We use unique tools, processes, and expertise in regression testing of our Oracle Applications. However, on an average organizations get executed more than 1,000 regression test cases for customers every quarter out of which 200 of them are reports with heavy data configuration tables/rows which affect our financial statements, payrolls for thousands of employees, and high priority data calculations. Primarily, this solution at Opkey took birth by looking at our Oracle HCM customers investing hundreds of hours invalidating these reports data manually, validating thousands of rows to ensure data integrity after an Oracle Release OR 3rd party patch. It cannot be stressed enough how even a small error in payroll/ financial processing could cause financial embarrassment, employee grievances, or even legal consequences to our customers and that we cannot rely on manual statistical sampling anymore.

Solution Opkey’s Reports Data Validation resolves the challenges and reduces the risk to Zero of validating Oracle Cloud Payroll/ Financials Data Integrity by allowing its customers to run a before and after patch compares of its data files through our One-Click Solution tool.  Our Comprehensive reconciliation reports validation tool focuses on whether Oracle or 3rd party changes have not impacted the key financials, also allows the validation of fast formulas through data elements comparison. It also gives users a side-by-side comparison of current and future states based on Employees, PSU’s, Worker’s, Departments, etc, and quickly identify potential issues, verifying that business reports balance between current and future states are not deviating. It also isolates data differences between the prior and current Oracle Cloud environments, allowing the team to focus on what changed rather than what was already validated.

Conclusion Data entered into an ERP system like Oracle is used throughout the organization. Because of the integrated nature of ERP, if inaccurate data is entered into the common database, the erroneous data may have a negative domino effect throughout the enterprise. The inaccuracy of data can also lead to errors in market planning, production planning, material procurement, or capacity acquisition. If a company with inaccurate data just forges ahead under the assumption that data errors will be corrected when they are spotted, the ERP will start losing its credibility.  Opkey’s Reports Validation Tool for its ERP customers is helping organizations process and validate thousands of payroll and financial records with the click of a button saving hundreds of hours of effort with the risk of Zero human error.

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