It was used for some basic purposes because all I did was use Jupyter notebooks to run codes on the Snowflake environment. This was done by me at my previous job. I had just started using Jupyter notebooks to run Python codes on Snowflake data warehouses.
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Though the tool provides exclusive features to run Python codes in a certain environment, it needs to improve support
What is our primary use case?
How has it helped my organization?
I was really more on the engineering side of things. The data scientists built certain models around it. So that, I guess, was a very big improvement.
What is most valuable?
For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks. Also, I think the data scientists used it to train their models. I am not the biggest user of it.
What needs improvement?
I think maybe the support is an area where it lacks. From my talks with the administrator, I think the support could be improved. My usage of it was limited to Jupyter notebooks.
For how long have I used the solution?
I have experience with IBM Watson Studio for about a couple of months, like three months. Also, I don't remember the version of the solution I was using.
What do I think about the stability of the solution?
Stability-wise, I rate the solution a seven out of ten.
What do I think about the scalability of the solution?
Scalability-wise, I rate the solution a six out of ten. However, I am not the best person to judge the solution based on scalability.
How was the initial setup?
The solution is deployed on the cloud.
What was our ROI?
I would think that my organization had seen a return on investment. However, I am not the best person to speak on its ROI.
What other advice do I have?
To those evaluating the product, I would say it's a good product to use from what I know, and it's not bad. Right now, we're just really making comparisons. I rate the overall solution a seven out of ten.
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