Defining reliability: SLAs for data platform teams
Reliable and trustworthy data is critical for any data-driven company, but it can be a big challenge when there are multiple teams each producing, transforming, and consuming data from one another simultaneously. Data teams are often caught in the middle, struggling to keep everyone happy. SLAs can remedy this challenge, serving as a powerful tool for aligning on the definition of quality and who’s responsible for addressing issues when they arise. Watch this video to learn:
Reliable and trustworthy data is critical for any data-driven company, but it can be a big challenge when there are multiple teams each producing, transforming, and consuming data from one another simultaneously. Data teams are often caught in the middle, struggling to keep everyone happy. SLAs can remedy this challenge, serving as a powerful tool for aligning on the definition of quality and who’s responsible for addressing issues when they arise. Watch this video to learn:
- The challenges posed when data quality hasn’t been quantified
- How to build SLAs for data including creating SLIs and SLOs
- Using SLAs as a prioritization tool
- Measuring success and using SLAs to communicate reliability
