Compare Amazon SageMaker vs. IBM SPSS Statistics

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Most Helpful Review
Find out what your peers are saying about Amazon SageMaker vs. IBM SPSS Statistics and other solutions. Updated: May 2021.
501,151 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:

Pros
"The few projects we have done have been promising.""They are doing a good job of evolving.""The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases.""Allows you to create API endpoints.""The deployment is very good, where you only need to press a few buttons."

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"Most of the product features are good but I particularly like the linear regression analysis.""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.""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.""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.""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.""It has the ability to easily change any variable in our research.""The most valuable feature is the user interface because you don't need to write code.""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."

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Cons
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.""I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox.""AI is a new area and AWS needs to have an internship training program available.""Lacking in some machine learning pipelines.""Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

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"I think the visualization and charting should be changed and made easier and more effective.""Technical support needs some improvement, as they do not respond as quickly as we would like.""The statistics should be more self-explanatory with detailed automated reports.""Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.""The product should provide more ways to import data and export results that are user-friendly for high-level executives.""The design of the experience can be improved.""This solution is not suitable for use with Big Data.""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."

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Pricing and Cost Advice
"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation.""The support costs are 10% of the Amazon fees and it comes by default."

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"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."

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Top Answer: You can quickly build models because it does the work for you.
Top Answer: In comparing the price of other products, SPSS Statistics is too expensive. Even when most of the universities in the Middle East have licenses for SPSS Statistics, they do not have licenses for the… more »
Top Answer: The technical support should be improved.
Ranking
13th
Views
12,082
Comparisons
10,231
Reviews
4
Average Words per Review
510
Rating
7.5
5th
Views
4,020
Comparisons
3,123
Reviews
15
Average Words per Review
720
Rating
7.9
Popular Comparisons
Also Known As
AWS SageMaker, SageMaker
SPSS Statistics
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Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

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.
Offer
Learn more about Amazon SageMaker
Learn more about IBM SPSS Statistics
Sample Customers
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
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
Top Industries
VISITORS READING REVIEWS
Computer Software Company27%
Media Company17%
Comms Service Provider12%
Financial Services Firm7%
REVIEWERS
University29%
Financial Services Firm21%
Aerospace/Defense Firm7%
Non Profit7%
VISITORS READING REVIEWS
Comms Service Provider26%
Computer Software Company16%
Educational Organization14%
University6%
Company Size
REVIEWERS
Midsize Enterprise57%
Large Enterprise43%
REVIEWERS
Small Business28%
Midsize Enterprise22%
Large Enterprise50%
Find out what your peers are saying about Amazon SageMaker vs. IBM SPSS Statistics and other solutions. Updated: May 2021.
501,151 professionals have used our research since 2012.

Amazon SageMaker is ranked 13th in Data Science Platforms with 5 reviews while IBM SPSS Statistics is ranked 5th in Data Science Platforms with 15 reviews. Amazon SageMaker is rated 7.6, while IBM SPSS Statistics is rated 8.0. The top reviewer of Amazon SageMaker writes "A solution with great computational storage, has many pre-built models, is stable, and has good support". On the other hand, the top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, H2O.ai and Domino Data Science Platform, whereas IBM SPSS Statistics is most compared with IBM SPSS Modeler, TIBCO Statistica, MathWorks Matlab, Weka and Alteryx. See our Amazon SageMaker vs. IBM SPSS Statistics report.

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