Smart forecasting with fast and accurate database analysis
Intelligent software that helps a lot in helping our various predictions in multiple projects. We do not need to know statistics or …
Overview
What is SAP Predictive Analytics?
SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.
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What is SAP Predictive Analytics?
SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.
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Product Details
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- Tech Details
What is SAP Predictive Analytics?
SAP®
Predictive Analytics software brings predictive insight to business users,
analysts, data scientists, and developers in your company. The products offers predictive automation, allowing customers to unlock the potential of Big Data from
virtually any source. By automating the building and management of
sophisticated predictive models to deliver insight in real time, this software
aims to make it easier to make better, more profitable decisions across the
enterprise.
SAP Predictive Analytics Features
- Supported: Automate analytics with Python API
- Supported: Publish predictive models to business applications
- Supported: Support data privacy to achieve legal compliance
SAP Predictive Analytics Competitors
SAP Predictive Analytics Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
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Reviews
(1-3 of 3)Companies can't remove reviews or game the system. Here's why
Intelligent software that helps a lot in helping our various predictions in multiple projects. We do not need to know statistics or special coding to use this platform. We look at forecasting sales and development of our services in different geographical areas. The development and sales department benefits a lot from SAP Predictive Analytics software. When it is possible to anticipate some conditions with software, you can reduce costs and avoid rework. In our work, having information plays a big role in providing advice to customers, which helps us. We only need data, which helps to make more accurate predictions. Data here is like good fuel for moving a car.
- All different common database like JDBC, XLS, CSV, and more types can be connected
- Easy integration with SAP Lumira workflow
- Simple and conceptual design and convenient diagrams
- Working with this software is very simple and enjoyable for me as [an] IT consultant and expert, but it is a bit complicated for novice users.
- Some big data takes more time‌to load, which I think could be faster
- Connect different data sources
- Load data from different sources or in fact any source
- Integration with SAP related products like SAP Lumira and SAP HANA
- Proper forecasting increases our credibility with partners and customers
- Forecasting determines the amount of investment in each sector and reduces the cost of additional costs
- Board, SAS Advanced Analytics and IBM SPSS Modeler
Each of them has a special use and we used SAP Predictive Analytics here because, in addition to the appropriate speed, it also had convenient and appropriate compatibility with other SAP products, which makes the work easier for our team.
October 31, 2019
SAP Predictive Analytics: an easy and good tool for both experts and non-experts in data science
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.
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.
- Data Preparation
- Modeling
- understand some of the reports
No
We have purchased PA but are in the process of proving its worth. It was brought in with the hope of being able to forecast work that is currently done manually, to give an 80% complete starting state that can be altered vs. starting completely from scratch. Additional use cases that will be explored include using historical data to predict trends going forward, which can be used as thresholds to then limit the scope of the investigation. The plan is to use it across our finance organization and even beyond depending on the outcome of our POCs.
- Ability to use built-in algorithms or expand using R. This means that (with training) casual users can take advantage but also data analysts can do their thing!
- Integration and consistency with Lumira. Even Lumira on its own has a quick 'predict' functionality (although limited/black box)
- Ability to do the analysis and then present visually using the Lumira visualization capabilities
- It's extremely hard to get started. We even have a data scientist who, when we put Predictive Analytics in front of them, they could not intuitively create a data model and start analyzing. Even with deep knowledge of data analysis, the interface isn't intuitive and it's hard to get to the point of having imported a data set and start analyzing/predicting
- Our platform team had confusion installing Predictive Analytics, particularly on the BI Platform. Additional complexity came when it came to using APL Libraries (AFL Wrapper or Stored Procedures)
- We are still working on merging datasets. In theory, we get how to do it but we come across all sorts of issues which don't occur in Spotfire (missing records etc.)
- It will potentially save time in forecast creation by giving an algorithm-derived forecast which can then be adjusted vs. starting from scratch. We can call this, a system enabled forecast
- Thresholds can be created based on historical data to flag actuals as in/out of the 'norm', or to limit the scope of an investigation
- We spent a lot of time so far and haven't got very far with it - it's been quite frustrating to use and a lot of time/money has been invested
We have typically used Spotfire for data analysis but decided to move to SAP Business Objects due to its innate connection with SAP. I found Lumira to be good for visualizations but it is not meant for data analysis. Therefore, we have introduced Predictive Analytics to see if it can fill that gap. So far, it's been far less intuitive than Spotfire to get started, and as far as I am aware so far, it does not bring many additional capabilities. I do, however, like that it utilizes the Lumira look/feel and integrates very well.