It took the world decades to develop widely accepted standards for working with relational data and SQL. I believe we are at the early stages of doing the same with event data and sequence analytics. It is starting to simultaneously emerge in many different fields:
- eng observability (traces at Datadog, Sumologic, etc)
- operational research (process mining at Celonis)
- product analytics (funnels at Amplitude, Mixpanel)
As with every new field, there are a lot of different and overlapping terms being suggested and explored at the same time.
We are trying to contribute to the field with a deep fundamental approach at Motif Analytics, including a purpose-built set of core sequence operations, rich flow visualizations, a pattern matching query engine, and foundational AI models on event sequences [1].
Fun fact: creators of Scuba turned it into a startup Interana (acquired by Twitter), who we took a lot of inspiration from for Motif's query engine.
[1] https://motifanalytics.com
- eng observability (traces at Datadog, Sumologic, etc)
- operational research (process mining at Celonis)
- product analytics (funnels at Amplitude, Mixpanel)
As with every new field, there are a lot of different and overlapping terms being suggested and explored at the same time.
We are trying to contribute to the field with a deep fundamental approach at Motif Analytics, including a purpose-built set of core sequence operations, rich flow visualizations, a pattern matching query engine, and foundational AI models on event sequences [1].
Fun fact: creators of Scuba turned it into a startup Interana (acquired by Twitter), who we took a lot of inspiration from for Motif's query engine.
[1] https://motifanalytics.com