• by Ray Schultz , Columnist, July 17, 2025

Data challenges affect every department in a company, particularly the email team. And the biggest issues concern access to data from other units, judging by The State Of Data Confidence, a study from Collibra, conducted by Ascend2. 

Of the professionals surveyed, 90% say they would benefit from improved data sharing, moderately or significantly. But only 21% list reducing information silos as a top priority.  

As it is, there are several hurdles to accessing data from other departments:

• Data-quality issues impacting the trustworthiness of shared data — 44%
• Data silos that prevent efficient data sharing across teams — 37%
• Inconsistent data standards or definitions across departments — 32%
• Limited data visibility or discoverability within the organization — 32% 
• Manual processes causing delays in data access — 30% 
• Difficulty in tracking data lineage for context and reliability — 28% 
• Lack of centralized data catalog or repository — 26%
• Insufficient access controls to permissions for secure sharing — 24%

How adept are companies managing these ai tasks? They rate themselves as having: 

• High confidence — 45%
• Moderate confidence — 42%
• Low confidence — 11% 

High-confidence organizations tend to: 

• Monitor data consistency — 59% 
• Access timeliness of data — 44% 
• Validate data formats — 52%
• Maintain high visibility into data pipelines — 64% 

Overall, 55% of high-confidence firms feel their data is highly consistent. In contrast, firms in the less confident groups act as follows, with the following actions:

• Monitor data consistency — 47% 
• Access timeliness of data — 24% 
• Validate data formats — 42%
• Maintain high visibility into data pipelines — 20%

High-confidence firms also follow these data governance practices:

• We have well-established data governance roles — 61%
• We have fully standardized data policies and terminology across the organization — 59%
• Regular audits are conducted to monitor data governance practices — 57%
• Our data governance roles align closely with overall organizational goals — 55%
• We have defined KPIs that track data governance performance — 53%
• We have fully standardized definitions — 52%

On another front, brands are attempting to cope with artificial intelligence. The top challenges when building or deploying AI models are:

• Reliability of data — 53%
• Ensuring compliance with growing regulations — 45% 
• Assessing potential risks — 41%
• Balancing pressure to ship new AI models quickly with the need to minimize risk — 41%
• Traceability/explainability of data — 39% 
• Ensuring alignment across cross-functional stakeholders — 36%