Unless you're a young startup, your data infrastructure is unlikely to be purely a modern data stack. So, how do you work with what you've got?

As we step into 2024, the data and analytics landscape continues to evolve, presenting data leaders new opportunities as well as new challenges.

Inspired by another CEO's discussion of "Four C's" in relation to their own observability company, I realized the importance of distilling our core architectural insights into our own set of guiding principles, the "Five C's.”

Data inaccuracies are not merely technical glitches; they can lead to significant business risks, particularly when it comes to an organization's reputation.

“No data is better than bad data” is a phrase you’ve probably heard from a CEO who...

Data observability enables a step-change in how much you can confidently do with your data by making it easy to keep data fresh and high quality 24/7.

At Bigeye, we believe SLAs can help answer a really big question for both data teams and the data consumers who depend on them: what does “data quality” mean exactly?

What are the three elements of data observability, and what do they mean?

Data teams tend to fall into one of three shapes. That shape will That will dictate the best strategy for rolling out and managing observability over your data, pipelines, and assets like analytics dashboards and machine learning models.