Compare IBM SPSS Statistics vs. SAP Predictive Analytics

IBM SPSS Statistics is ranked 4th in Data Science Platforms with 10 reviews while SAP Predictive Analytics is ranked 17th in Data Science Platforms with 2 reviews. IBM SPSS Statistics is rated 8.0, while SAP Predictive Analytics is rated 8.6. The top reviewer of IBM SPSS Statistics writes "Has many existing algorithms that we can use but it should have the ability to create higher-level presentations". On the other hand, the top reviewer of SAP Predictive Analytics writes "Enables us to forecast and pull trends and has an easy installation ". IBM SPSS Statistics is most compared with IBM SPSS Modeler, Weka, MathWorks Matlab, IBM Watson Studio and KNIME, whereas SAP Predictive Analytics is most compared with Microsoft Azure Machine Learning Studio, SAS Enterprise Miner, IBM SPSS Modeler, KNIME and Amazon SageMaker. See our IBM SPSS Statistics vs. SAP Predictive Analytics report.
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Most Helpful Review
Find out what your peers are saying about IBM SPSS Statistics vs. SAP Predictive Analytics and other solutions. Updated: July 2020.
425,604 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS.The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful.In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions.The most valuable feature is the user interface because you don't need to write code.It has the ability to easily change any variable in our research.They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do.You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use.The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important.

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I think the features of the actual ability to forecast and pull trends and correlations has been really good.The most valuable features are the analytics and reporting.

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One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated.The solution needs more planning tools and capabilities.Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them.This solution is not suitable for use with Big Data.The design of the experience can be improved.The product should provide more ways to import data and export results that are user-friendly for high-level executives.Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.The statistics should be more self-explanatory with detailed automated reports.

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This solution works for acquired data but not live, real-time data.

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Pricing and Cost Advice
The price of this solution is a little bit high, which was a problem for my company.We think that IBM SPSS is expensive for this function.

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The pricing is reasonableA free trial version is available for testing out this solution.

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Popular Comparisons
Compared 14% of the time.
Compared 3% of the time.
Compared 8% of the time.
Also Known As
SPSS StatisticsSAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
Your organization has more data than ever, but spreadsheets and basic statistical analysis tools limit its usefulness. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next. Virtually eliminate time-consuming data prep; and quickly create, manipulate and distribute insights for decision making.

SAPĀ® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

Learn more about IBM SPSS Statistics
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Sample Customers
LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDAmBank
Top Industries
Financial Services Firm22%
Consumer Goods Company11%
Aerospace/Defense Firm11%
Software R&D Company24%
K 12 Educational Company Or School17%
Comms Service Provider11%
Media Company10%
No Data Available
Find out what your peers are saying about IBM SPSS Statistics vs. SAP Predictive Analytics and other solutions. Updated: July 2020.
425,604 professionals have used our research since 2012.

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