Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More. Data is critical to every business, but when the volume of the information and the complexity of pipelines grow, things are bound to break!According to a new survey of 200 data professionals working in the U.S., instances of data downtime — periods when enterprise data remains missing, inaccurate, or inaccessible — have nearly doubled year over year, given the surge in the number of quality incidents and the firefighting time taken by teams.The poll, commissioned by data observability company Monte Carlo and conducted by Wakefield Research in March 2023, highlights a critical gap that needs to be addressed as organizations race to pull in as many data assets as they can to build downstream AI and analytics applications for business-critical functions and decision-making.“More data plus more complexity equals more opportunities for data to break. A higher proportion of data incidents are also being caught as data is becoming more integral to the revenue-generating operations of organizations. This means business users and data consumers are more likely to catch incidents that data teams miss,” Lior Gavish, co-founder and CTO of Monte Carlo, tells VentureBeat.

Last week Datafold launched an open source package for diffing data between databases e.g. PostgreSQL <> Snowflake.

To further strengthen our commitment to providing industry-leading coverage of data technology, VentureBeat is excited to welcome Andrew Brust and Tony Baer as regular contributors. Watch for their articles in the Data Pipeline. New York-headquartered data reliability company Datafold has launched an open-source diffing tool to help enterprises compare databases and perform checks to validate data consistency