1. Intuitive and visual for better efficiency: no need to code. You can intuitively design and follow the flow of data. This makes the whole process much less prone to errors and easier to debug 2. Fast and powerful: Can process huge amounts of data on an ordinary laptop 3. Designed for real world applications: I appreciated the fact that Anatella was clearly designed for data science partitioners in the real world and not only academia (and I say this as an academic). The predictive models fit very well with the ETL and pretty much all components needed for data processing and analysis are natively available. 4. The perfect “cognition amplifier” for data scientists: As a programmer, my experience is that data processing can become cumbersome when done exclusively with programming. The logic of the data flow is lost in the code and debugging becomes pretty tedious. Anatella fulfills perfectly this job while maintaining the clarity of the process. I would say, even for experienced programmers and Excel wizard and may be especially for them, Anatella has all its place in the data scientist toolbox. Review collected by and hosted on G2.com.

It’s not possible to create components of components. When doing complex operations, it is essential to aggregate a whole sequence of components into an abstract and reusable piece (equivalent to subroutines in programming). It would help keep clarity and prevent the model from morphing into a messy spaghetti dataflow The help is not detailed enough, and a repository of example model files would be helpful Review collected by and hosted on G2.com.