Session Outline
Data is overwhelming companies rather than helping them because of data quality issues. Full stack data observability is the best way to monitor data from ingestion all the way to consumption. Full-stack data observability allows you to identify and troubleshoot data quality issues before they become a business problem.
Key Takeaways:
- Currently, data teams waste too many of their resources troubleshooting data quality issues.
- The best way to monitor and troubleshoot data quality issues is by adopting data observability.
- The pillars of data observability are metrics and logs/metadata, and lineage.
- Data observability needs to act as an overseeing layer of a company’s existing data stack, so it is essential that data observability is full-stack.
