Our Blog
Take a deep dive into the The 5 Pillars of Data Observability, and End-to-end data observability.
Learn about the data lineage challenges and how data pipeline traceability can provide a complete understanding of the data's journey to improve quality and reliability.
Here’s the uncomfortable truth: the way most organizations manage data incidents in ServiceNow is broken. Pantomath's Somesh Saxena gives his thoughts.
Shashank Saxena, Pantomath CEO, unpacks what’s really behind AI’s 95% failure rate — and why it has nothing to do with model accuracy.
Pantomath CEO, Somesh Saxena, was interviewed by Authority Magazine as part of their “How To Effectively Leverage Data To Take Your Company To The Next Level” series. Read about his insights and take on the topic.
Special thanks to Coretek, Enlivened Tech, Lydonia, and Pantomath for making the CDO Magazine Columbus Executive Community Dinner such a resounding success.
The World’s Leading Companies Trust Pantomath
There are five common mistakes that teams often make on their journey toward data observability. Learn how to avoid them!
You can’t simply implement data observability and then hope for the best. Learn about the top 10 essential metrics to make your business thrive.
Data quality has a long history, dating back at least to mainframes in the 1960s. Learn about the path Data Quality has taken, and where it's headed.
Learn about who should share ownership and responsibility for data quality and reliability in an organization from Craig Smith, Pantomath's VP of Customer Experience.
Data quality and reliability is paramount to the success of modern-day organizations. Data quality issues can lead to significant business disruptions, poor decision-making with bad data, and overall lack of trust in data. Learn about Pantomath's unique approach to data quality.
Learn how a data leader at a large enterprise created a purpose-built platform for data teams to address bad data through end-to-end data observability and cross-platform pipeline traceability for ultimate data reliability.
