SAP Predictive Analytics: an easy and good tool for both experts and non-experts in data science
Abdelhalim DADOUCHE profile photo
October 31, 2019

SAP Predictive Analytics: an easy and good tool for both experts and non-experts in data science

Score 10 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with SAP Predictive Analytics

SAP Predictive Analytics is used by many teams from the SAP organization which perfectly fits the "SAP runs SAP" mantra. The use cases range from Sales & Marketing to IT operations and events sometimes in the R&D departments. There are plenty of uses cases covered by SAP Predictive Analytics from typical "classification" problems like "predicting which lead is going to convert into an opportunity" or some more advanced like "content recommendation" on the websites.
  • It doesn't require you to have a Ph.D. to build models!
  • You can use it to address a very large and wide dataset without worrying about sampling.
  • Automation is in the product DNA. You can prepare your data, ingest it into the "Kernel", then get insights about what was found, decide to publish it and schedule scoring tasks or model refresh in the same product.
  • The "User Experience" is sometimes lacking some clear basic things. Maybe a migration to a cloud-based environment will help bridge that gap.
  • API is probably the next item on my list. The existing one is not easy to access or use which limits the integration capabilities.
  • You don't need an army of Ph.D.s to address your needs (and if you have, lucky you as they will be able to do so much more now).
  • SAP Predictive Analytics allows you to reduce tremendously the time to build and maintain models.
  • Lower workforce cost + higher productivity = you already won the TCO battle. On the ROI side, because you will get better agility, you can "try" more things and adjust more quickly.
(Couldn't pick R from the list nor Python packages)

Actually, I don't see SAP Predictive Analytics stacking up against other tools, but rather complementing them. On one side why would we use something "more complex" to solve a "business as usual" problem, when you can use tools that will address it fast & well (maybe not "perfect" but do you need perfect all the time?). The time you save can then be invested in more advanced/sophisticated problems or address more "business as usual" problems.
The documentation provides an explanation about what features are available but not necessarily what's happening behind the scenes. On the other side, the "community" has grown since the acquisition and most questions are properly addressed by SAP folks. Since the "product maintenance" mode announcement was made, there wasn't much new content published except on the Smart Predict side (which is built by the SAP Predictive Analytics team).

Do you think SAP Predictive Analytics delivers good value for the price?

Yes

Are you happy with SAP Predictive Analytics's feature set?

Yes

Did SAP Predictive Analytics live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of SAP Predictive Analytics go as expected?

Yes

Would you buy SAP Predictive Analytics again?

Yes

When you don't have much data science skills or when you need to build something quick, you can get started really fast with SAP Predictive Analytics. There are scenarios, like the ones covered by a neural network, where SAP Predictive Analytics is not well suited, but the big question is usually: "do you really need a neural network to address this use case?"

Using SAP Predictive Analytics

ProsCons
Like to use
Technical support not required
Well integrated
Quick to learn
Convenient
Feel confident using
Familiar
None
  • Data Preparation
  • Modeling
  • understand some of the reports
the UI is a bit dated and available as a desktop tool mostly.