As enterprises continue to expand their use of advanced analytics, machine learning, real-time reporting, and self-service business intelligence, the reliability of underlying data ecosystems has become increasingly critical. Ensuring the data powering enterprise decisions remains accurate, complete, timely, and trustworthy is becoming increasingly important as organizations scale their data and analytics capabilities.
At the same time, growing data volumes, expanding data architectures, and increasingly interconnected data ecosystems are creating new challenges around observability, lineage, monitoring, operational resilience, and data quality management. Incomplete lineage visibility, schema drift, data quality degradation, broken dependencies, and limited insight into upstream and downstream impacts can significantly affect analytics accuracy, reporting integrity, business confidence, and operational decision-making.
In this highly interactive, member-driven working session, the event moderators will facilitate a structured, open exchange where all attendees are expected to actively contribute to the group conversation - sharing what is working, what is not, and to engage in a candid, group problem-solving dialogue around the most pressing challenges facing many enterprise data environments.
Please Note: This is not a passive event. Throughout the event, all attendees are expected to actively participate in the discussion and contribute real-world challenges and solutions.
Topics of discussion will include, yet will not be limited to:
- Data observability frameworks, platforms, and strategies for monitoring modern data ecosystems
- Identifying, diagnosing, and resolving data pipeline failures, bottlenecks, and performance issues
- Data lineage, dependency mapping, and root cause analysis across complex data architectures
- Approaches for improving data quality, reliability, accuracy, completeness, and timeliness
- Establishing data service level agreements (SLAs), reliability metrics, and operational accountability
Karthik Josyula, Head of Data & AI Platforms, Data & Analytics, KOHLER
Shrikant Sonparote, Lead Software Engineer, LOWE’S
Kapil Kumar Sharma, Data Architect, Data & Business Operations - Virtual Demand Center, CISCO
