All Resources
How to Improve Data Quality: Define, Design, and Deliver
76% of organizations say data-driven decision-making is their top goal for 2025. However, 67% of data and analytics professionals don’t fully trust the data used
Guide to pattern matching: What it means and how to do it?
Finding patterns is easy in any kind of data-rich environment; that’s what mediocre gamblers do. The key is in determining whether the patterns represent signal
Data Standardization Guide: Types, Benefits, and Process
Poor data standardization is a hidden profit killer. When customer names, products, or sales figures appear in different formats across systems (and often even within
Data Integration Explained: Definition, Types, Process, and Tools
With 89% of employees reporting sifting through up to six data sources daily to find relevant information, data sprawl emerges as a major culprit undermining
How poor data quality impacts a recession survival plan
“You get recessions, you have stock market declines. If you don’t understand that’s going to happen, then you’re not ready. You won’t do well in
8 Principles of Data Management
An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes. With large amounts of data being generated
Data Quality Management: What, Why, How, and Best Practices
“Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction, and skillful execution; It represents the wise choice
How to Improve Data Quality in Financial Services
24 percent of insurers say that they are ‘not very confident’ about the data they use to assess and price risk. Corinium Intelligence The economic
Data quality in healthcare – Benefits, challenges, and steps for improvement
38 percent of U.S. healthcare providers have incurred an adverse event within the last two years due to a patient matching issue. Survey from eHI
