Data Observability vs. Data Quality
Data empowers businesses to gain valuable insights into industry trends and fosters profitable decision-making for long-term growth. It enables firms…
data quality
The Challenges of Data Migration: Ensuring Smooth Transitions Between Systems
Data migration — the process of transferring data from one system to another — is a critical undertaking for organizations…
Through the Looking Glass: What Does Data Quality Mean for Unstructured Data?
I go to data conferences. Frequently. Almost always right here in NYC. We have lots of data conferences here. Over…
Data Insights Ensure Quality Data and Confident Decisions
Every business (large or small) creates and depends upon data. One hundred years ago, businesses looked to leaders and experts…
Data Speaks for Itself: Data Validation – Data Accuracy Imposter or Assistant?
In my last article, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality” published…
The Art of Lean Governance: A Systems Thinking Approach to Data Governance
A systems thinking approach to process control and optimization demands continual data quality feedback loops. Moving the quality checks upstream…
Data Errors in Financial Services: Addressing the Real Cost of Poor Data Quality
Data quality issues continue to plague financial services organizations, resulting in costly fines, operational inefficiencies, and damage to reputations. Even…
Mastering Data Governance in Insurance: Balancing Innovation with Compliance
Mastering data governance has become a critical challenge for insurers in today’s rapidly evolving insurance landscape. Many companies struggle to…
Cleaning Up the Data Disaster: How Businesses Can Battle Dirty Data
Running a business with dirty data is like trying to drive a car blindfolded — it’s only a matter of…
10 Risks of IoT Data Management
What Is IoT Data Management? IoT data management refers to the process of collecting, storing, processing, and analyzing the massive…