Modelling platform migration is a process that provides significant benefits to the business and allows you to realise the full potential of your modelling capability. It’s not so much about new features, but more about cost savings, risk mitigation, innovation and faster delivery.
One thing that I’m frequently asked is how client models can be better integrated with database or data warehouse environments. This article explores what else might be possible with Mo.net…
Following on from the Mo.net Loves Python series. this article outlines how to change the input data used by the Mo.net projection when being called from Python.
In the last article I demonstrated how to run a Python script with arguments from a Mo.net group projection task and return the results from the script back to Mo.net. In this third and final part of the Mo.net Loves Python series, I will reverse the scenario and use a Python script to call a Mo.net projection task.
Part two of our Mo.net Loves Python series. We look at how to run an existing Python-based Black Scholes model from a Mo.net group projection task, passing in arguments to define the vector size to use, and retrieving the completion message & run time from the Python script.
The first article in our Mo.net Loves Python series. We discuss how Mo.net and Python can be integrated in a range of different ways to meet a multitude of potential use cases.