Healthy Data.
Better Decisions.
By examining quality, you can proactively plan for the future,
identify enhancements opportunities, and ensuring accurate decision-making.
Request a Data Quality Assessment
Enhanced database health.
As an SAP Gold Partner, Auritas brings you best in class
data quality management services.
Accurate, Complete and Consistent Data.
With Auritas' digital Data Quality Assessment, organizations gain valuable insights on their businesses. Data experts perform diagnostics of the health of your SAP Master & Transactional Data through a battery of 297 tests, requiring little engagement from corporate resources.
SUCCESSFULLY ASSESSED CLIENTS
Data Quality Management
Methodology by Auritas
The Auritas Data Management Factory methodology helps address data quality issues and
ensure a current, reliable, and accurate database in three steps: Assess, Address and Sustain.
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01.
Assess
Identify current quality issues and areas for improvement.
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02.
Address
Implement data and process-driven optimizations.
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03.
Sustain
Measure impact and ongoing quality monitoring.
Assess Master & Transactional Data
The insights that a business can extract out of their data are only as good as the data itself. Better data, better decisions.
Master Data
Core Dimensions Evaluated:
Transactional Data
Core Dimensions Evaluated:
Why is Data Quality Assessment important?
A DQA is crucial because high-quality data is foundational for making informed business decisions. It helps prevent costly errors, enhances operational efficiency, supports compliance with regulations, and improves customer satisfaction by ensuring the data your organization relies on is accurate and reliable.
What are the common data quality issues?
Common issues include duplicate records, missing or incomplete data, inconsistent data formats, outdated information, and data entry errors. These issues can affect data reliability and the effectiveness of business processes and can be undercovered by Auritas’ data quality assessment.
What are the steps after completing a Data Assessment?
After completing a DQA, Auritas provides a detailed report with findings and recommendations. The next steps typically involve implementing the recommended actions, which may include data cleansing, establishing data governance frameworks, improving data management processes, and ongoing monitoring to maintain data quality.
How does Auritas conduct a Data Quality Assessment?
Auritas conducts a DQA by first understanding the client’s data environment and business requirements. We then perform data profiling to identify issues, analyze data quality metrics, and evaluate data governance practices. Finally, we provide a detailed report with findings, recommendations, and an action plan for improvement.