Blog Posts on Cloud, Data Lake, Data Quality Validation and Data Reconciliation
Challenges With Data Observability Platforms and How to Overcome Them
5 Critical Challenges of Cloud Data Pipeline Leaks and How to Ensure Data Quality
Organizations, especially those in financial services, struggle to ensure data quality in the cloud. Data pipelines often drop rows thanks to issues with infrastructure that companies don’t control, but the scale at which these organizations process data means that manual methods of identifying these leaks are insufficient.
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Poor Data Quality regulatory nightmare for a major Bank
Bank wrongly collects debt from customers due to IT errors. One of Europe’s reputed progressive banks is Danske Bank (Denmark).…
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Why the Fortune 500 is Dumping Hadoop
Saw this very informative article on the ongoing demise of Hadoop. Our customers are experiencing the same conditions the author…
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AI/ML-Led Automated Data Quality: a Whitepaper Overview
Introduction In today’s data-driven world, Data Quality Management (DQM), especially with gen AI data quality solutions, is not just a…
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Expert Insights from Turing Award Winner on Improving Data Reliability in Modern Systems
Turing Award Winner and MIT Professor, Dr. Michael Stonebraker, provided a groundbreaking perspective on data reliability in his white paper.…
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Mitigating Impact of Data Quality on GDPR Compliance
For GDPR (General Data Protection Regulation, a short introduction is attached below this article), Data Quality and Data Integrity are…
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Eliminate 30% of Manual Rework in Healthcare With Advanced Data Integrity & Quality Solutions
Key Takeaway Health insurance companies are losing millions of dollars each year due to poor healthcare Data Integrity and healthcare…
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