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
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
Introduction The most common data issue that enterprises deal with is that of its quality. You have the right data applications deployed, the sources capture
“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
An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes. With large amounts of data being generated
Of U.S. healthcare providers have incurred an adverse event within the last two years due to a patient matching issue. Survey from eHI and NextGate
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
In the previous blog The role of data quality in the world of retail, we discussed the role clean data plays in the retail industry
We’ve all experienced the thrill of a perfectly timed Netflix recommendation or the joy of discovering a new favorite song in your Spotify playlist. It
In early 2022, Unity Technologies faced an unexpected data quality issue—one that cost the company $110 million. Resulting from the ingestion of flawed data by
A recent survey reported that the top KPI for data teams in 2021 was data quality and reliability. But the majority of the respondents said that they
Research shows that while 24% of data teams use tools to find data quality issues, most of their problems still go unresolved. This means that
Data Ladder offers an end-to-end data quality and matching engine to enhance the reliability and accuracy of the enterprise data ecosystem without friction.
