Flyte is a workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others.
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We’re excited to announce a new integration between Great Expectations and Flyte. We believe this is a much deeper and intuitive integration than ever before! Great Expectations is a Python-based open-source library for validating, documenting, and p...
We all love “undoing” when things don’t work as expected. Imagine the pain we would have to experience without such an option; we can’t just revert to or pull from what we have been working on before. From the perspective of machine learning or data...
MapReduce is a prominent terminology in the Big Data vocabulary owing to the ease of handling large datasets with the “map” and “reduce” operations. A conventional map-reduce job consists of two phases: one, it performs filtering and sorting of the d...
By: Max Hoffman (Software Engineer at Dolthub) Dolt and Flyte joined forces to build two data integrations. Dolt is a SQL database that supports Git Versioning. Flyte is a workflow orchestrator for creating and evolving machine learning processes and...
By: Jake Neyer (Software Engineer at Striveworks) At Striveworks, we are building a one-of-a-kind data science platform by integrating the building blocks that most data science teams already have in their tool belts and adding a few new ones to stre...
Run-time dependency is an important consideration when building machine learning or data processing pipelines. Consider a case where you want to query your database x number of times where x can be resolved only at run-time. Here, looping is the ulti...
