Q. Your company has developed a machine learning model outside of SAC (e.g., in Python or TensorFlow) to predict customer churn, and you want to integrate the model into SAC for real-time predictions and analysis.
How would you integrate a machine learning model developed externally (outside SAC) into SAP Analytics Cloud for real-time predictions?
Ans: To integrate the ML model developed externally into SAC for real-time prediction and analysis, we can have a few of the below, out of many approaches:
Approach 1: Using SAP Predictive Services as an intermediary between SAC and other external models.
– We can do so by deploying ML Models on SAP BTP – such as using SAP AI Core and AI Foundation which allows you to serve ML models via rest APIs. These are mainly used when we are using tensorflow or any other deep learning framework.
– We can also use SAP Data Intelligence by deploying a Python-based ML model, for the orchestration of data pipelines.
– Once the model is being deployed, we can expose the model as REST API endpoint that will accept the input data and return predictions as possible. The input output formats should be standardized.
– Next, we integrate the model with SAC. Map the input fields to the API parameters & the output fields to the data model structure.
Afterward, we can build the dashboard for real-time predictions. There, we can create story and dashboards which uses the live data connections to the external machine learning models. Afterwards, we can set-up realtime data refresh which ensures various model predictions and allow up-to-date data based on latest customer data.
Various other approaches we can use are SAP Data Intelligence or SAP HANA for Model deployment concept. Another approach can be using SAP Analytics Cloud Smart Predict concept for simpler models.
There are various key considerations which we should take care includes latency, security, model maintenance and scalability of the approaches.
Using these approaches, we can integrate machine learning models which are developed externally into SAP Analytics Cloud, and perform all real-time predictions within SAC dashboards for various business analysis purposes.
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