For years, enterprises have run mission-critical data systems with outdated tools that weren’t designed to manage the current exploding supply of data. The problem is only getting worse as massive data volumes, data pipeline complexity, new technologies and hybrid environments conspire to challenge the business value of data systems. This affects everyone in an organization – data teams struggle with operational issues and often fail to meet the increasing demand for real-time data insights, data consumers don’t trust the data they need to make key business decisions, and executives can’t ensure data delivery and pipeline performance meet business requirements.
This session will focus on how, when and where enterprises can apply data observability to:
- Successfully architect, operate, and optimize complex data systems at scale
- Gain full visibility into data processing, data, and data pipelines
- Use ML to automate data identification, quality and management
- Manage costs during digital transformation to cloud services
- Improve data reliability while reducing operational risk and cost management