SAP HANA python API - machine learning use cases

[Former Member]

Hi,

what are the typical use cases when I can deveolp my models in the Jupyter notebook with data in SAP HANA?

I am asking because most of the machine learning use cases I know have data in formats like wav, txt, csv or stored in data lake e.g. Hadoop or streaming data from IOT sensors. HANA memory is very expensive so it would make no sense to load this data to HANA.

Do you know any use cases or similar scenarios? Any links?

BR

Robert

[AndreasForster]

Hello Robert, ML can provide value through improving or automating business decisions. Very often data for such processes is kept in a SAP HANA systen, ie under BW-on-HANA or BW4. With the hana_ml Wrapper Data Scientists can easily train ML models without having to extract the data out of the system, thus avoiding data duplication, improving data governance, keeping the architecture lean. Since the data is not moved, the hand-over from Data Scientist to IT for deployment becomes easier. The ML models can be integrated into larger workflows, ie you could deploy a model as REST-API on Data Intelligence for inference and provide a chatbot frontend with Conversational AI for your end users to get predictions on the fly. All without having to extract the data. The actual use cases can be very different depending on the industry or department. I worked on projects for example to estimate the quality of a customer's product based on different raw materials, or estimating the fair price of a used product, or generally around customer analytics. I understand it is planned to expose time-series forecasting through the ml_wrapper. This would be another major area, ie for demand forecasting, financial forecasting, etc. Please also feel free to ping me directly. Greetings, Andreas