IBM SPSS Statistics vs SAP Predictive Analytics comparison

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Executive Summary

We performed a comparison between IBM SPSS Statistics and SAP Predictive Analytics based on real PeerSpot user reviews.

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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files.""IBM SPSS Statistics depends on AI.""The features that I have found most valuable are the Bayesian statistics and descriptive statistics.""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.""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.""The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis.""The most valuable feature is its robust statistical analysis capabilities.""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."

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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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Cons
"This solution is not suitable for use with Big Data.""I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable.""Better documentation on how to use macros.""If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution.""Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.""It could provide even more in the way of automation as there are many opportunities.""There is a learning curve; it's not very steep, but there is one.""Improvements are needed in the user interface, particularly in terms of user-friendliness."

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

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Pricing and Cost Advice
  • "If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
  • "More affordable training for new staff members."
  • "Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
  • "We think that IBM SPSS is expensive for this function."
  • "The price of this solution is a little bit high, which was a problem for my company."
  • "The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
  • "It's quite expensive, but they do a special deal for universities."
  • "The price of IBM SPSS Statistics could improve."
  • More IBM SPSS Statistics Pricing and Cost Advice →

  • "A free trial version is available for testing out this solution."
  • "The pricing is reasonable"
  • More SAP Predictive Analytics Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
    Top Answer:While the pricing of the product may be higher, the accompanying service and features justify the investment. However, to address pricing concerns, I suggest customizing pricing options for developing… more »
    Top Answer:In some cases, the product takes time to load a large dataset. They could improve this particular area.
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    7th
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    3,773
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    2,318
    Reviews
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    Average Words per Review
    537
    Rating
    8.6
    24th
    Views
    520
    Comparisons
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    Also Known As
    SPSS Statistics
    SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
    Learn More
    Overview

    IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

    IBM SPSS Statistics Benefits

    Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:


    • Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.


    • Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.


    • Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle. 


    IBM SPSS Statistics Features


    • Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.


    • Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.


    • Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.


    Reviews from Real Users

    IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

    An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

    A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

    SAP® 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.

    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-TILDA
    mBank
    Top Industries
    REVIEWERS
    University46%
    Financial Services Firm17%
    Aerospace/Defense Firm4%
    Non Profit4%
    VISITORS READING REVIEWS
    University16%
    Educational Organization12%
    Comms Service Provider11%
    Computer Software Company8%
    VISITORS READING REVIEWS
    Financial Services Firm12%
    Educational Organization12%
    Comms Service Provider9%
    University9%
    Company Size
    REVIEWERS
    Small Business26%
    Midsize Enterprise19%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise13%
    Large Enterprise75%
    Buyer's Guide
    Data Science Platforms
    March 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    IBM SPSS Statistics is ranked 7th in Data Science Platforms with 36 reviews while SAP Predictive Analytics is ranked 24th in Data Science Platforms. IBM SPSS Statistics is rated 8.0, while SAP Predictive Analytics is rated 8.6. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of SAP Predictive Analytics writes "Easy to implement, good data forecasting and reporting". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and Weka, whereas SAP Predictive Analytics is most compared with IBM Watson Studio, Microsoft Azure Machine Learning Studio, KNIME, Domino Data Science Platform and IBM SPSS Modeler.

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    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.