IBM SPSS Statistics vs. IBM Watson Studio on Cloud Pak for Data

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Statistics
Score 8.5 out of 10
N/A
SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).
$99
per month
IBM Watson Studio
Score 8.0 out of 10
N/A
IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.N/A
Pricing
IBM SPSS StatisticsIBM Watson Studio on Cloud Pak for Data
Editions & Modules
Subscription
$99.00
per month
Base
$3,610
one-time fee per user
Standard
$7,960
one-time fee per user
Professional
$15,900
one-time fee per user
Premium
$23,800
one-time fee per user
No answers on this topic
Offerings
Pricing Offerings
IBM SPSS StatisticsIBM Watson Studio
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM SPSS StatisticsIBM Watson Studio on Cloud Pak for Data
Considered Both Products
IBM SPSS Statistics

No answer on this topic

IBM Watson Studio
Chose IBM Watson Studio on Cloud Pak for Data
I am excited with the roadmap of Watson Studio incorporating SPSS Modeler in the offerings.
Chose IBM Watson Studio on Cloud Pak for Data
Watson Studio offers more capabilities and diversity in tools and services.
Chose IBM Watson Studio on Cloud Pak for Data
The learning curve for DSX is smaller compared to other tools. The data science user base often has preferred tools that they have used previously which are often not DSX which makes adoption of DSX by trained data scientists harder than new users.
Chose IBM Watson Studio on Cloud Pak for Data
Is more complementary, we can have just one platform, due to we need to cover the analytics cycle. Just one platform couldn’t cover all the users profile.
Chose IBM Watson Studio on Cloud Pak for Data
DSx stands out in that deployment can be done easily through Watson ML whereas for other technologies separate paradigms are needed.
Chose IBM Watson Studio on Cloud Pak for Data
SPSS - Totally different approaches, SPSS UI is now a well-known name with a well-established user base who we consider aren´t going anywhere but Statistics.

Modeler - A proven analytical solution with capabilities to deal with huge datasets, scalability offers you now the …
Chose IBM Watson Studio on Cloud Pak for Data
The mix of proprietary and open-source benefits that DSx offers gives me more flexibility than any other options I have encountered. I have the custom program building capability of Anaconda with the built-in predictive models of SPSS Modeler. I have more visualization …
Top Pros
Top Cons
Features
IBM SPSS StatisticsIBM Watson Studio on Cloud Pak for Data
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Statistics
-
Ratings
IBM Watson Studio on Cloud Pak for Data
8.1
22 Ratings
4% below category average
Connect to Multiple Data Sources00 Ratings8.022 Ratings
Extend Existing Data Sources00 Ratings8.022 Ratings
Automatic Data Format Detection00 Ratings9.921 Ratings
MDM Integration00 Ratings6.414 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM SPSS Statistics
-
Ratings
IBM Watson Studio on Cloud Pak for Data
10.0
22 Ratings
17% above category average
Visualization00 Ratings10.022 Ratings
Interactive Data Analysis00 Ratings10.022 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM SPSS Statistics
-
Ratings
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
14% above category average
Interactive Data Cleaning and Enrichment00 Ratings9.922 Ratings
Data Transformations00 Ratings10.021 Ratings
Data Encryption00 Ratings8.020 Ratings
Built-in Processors00 Ratings10.021 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM SPSS Statistics
-
Ratings
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
11% above category average
Multiple Model Development Languages and Tools00 Ratings10.021 Ratings
Automated Machine Learning00 Ratings9.922 Ratings
Single platform for multiple model development00 Ratings9.922 Ratings
Self-Service Model Delivery00 Ratings8.020 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
IBM SPSS Statistics
-
Ratings
IBM Watson Studio on Cloud Pak for Data
8.0
22 Ratings
7% below category average
Flexible Model Publishing Options00 Ratings9.022 Ratings
Security, Governance, and Cost Controls00 Ratings7.022 Ratings
Best Alternatives
IBM SPSS StatisticsIBM Watson Studio on Cloud Pak for Data
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Alteryx
Alteryx
Score 9.0 out of 10
Mathematica
Mathematica
Score 8.3 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS StatisticsIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
8.5
(86 ratings)
8.0
(65 ratings)
Likelihood to Renew
8.6
(22 ratings)
8.2
(1 ratings)
Usability
8.0
(14 ratings)
9.6
(2 ratings)
Availability
6.0
(1 ratings)
8.2
(1 ratings)
Performance
6.0
(1 ratings)
8.2
(1 ratings)
Support Rating
6.4
(12 ratings)
8.2
(1 ratings)
In-Person Training
-
(0 ratings)
8.2
(1 ratings)
Online Training
-
(0 ratings)
8.2
(1 ratings)
Implementation Rating
8.7
(7 ratings)
7.3
(1 ratings)
Configurability
5.0
(1 ratings)
-
(0 ratings)
Ease of integration
5.0
(1 ratings)
-
(0 ratings)
Product Scalability
5.0
(1 ratings)
8.2
(1 ratings)
Vendor post-sale
5.0
(1 ratings)
7.3
(1 ratings)
Vendor pre-sale
5.0
(1 ratings)
8.2
(1 ratings)
User Testimonials
IBM SPSS StatisticsIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
IBM
SPSS is well-suited for the following: 1) User Behavior Analysis: SPSS handles large datasets to analyze user behavior data. 2) Customer Satisfaction / Foundational Surveys: SPSS facilitates analysis of quant data from satisfaction surveys, keeping us informed about customer needs and preferences. 3) A/B test analysis: SPSS statistical tools for A/B test analysis, which helps optimize user experience of our products. Scenarios where SPSS are less appropriate: 1) Qualitative Data Analysis: I do not use SPSS for open-ended survey responses/qual data. 2) Live/in-vivo data analysis: SPSS is not ideal for real-time data processing. 3) Complex Data Integration: SPSS isn’t the best fit for complex data integration tasks
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IBM
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
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Pros
IBM
  • SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
  • Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
  • SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
  • SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
  • In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
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IBM
  • Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
  • SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
  • Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
  • Estimator validation lets data scientists test and prove different models.
Read full review
Cons
IBM
  • It would be beneficial to have AMOS as part of the SPSS package instead of purchasing it separately.
  • It would be beneficial to have other statistical tests, such as PROCESS, be part of the standard SPSS tests instead of having the need to run a syntax to have it installed.
  • My dataset tends to be smaller, and I have never had any issues with using SPSS. I heard that SPSS may not be optimal when handling large datasets.
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IBM
  • The cost is steep and so only companies with resources can afford it
  • It will be nice to have Chinese versions so that Chinese engineers can also use it easily
  • It takes a while to learn how to input different kinds of skin defects for detection
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Likelihood to Renew
IBM
Both
money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis
using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data
entry and data analysis for my research. Output from SPSS is very easy to
interpret for data analysis and findings
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IBM
because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
Read full review
Usability
IBM
Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.
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IBM
The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
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Reliability and Availability
IBM
SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data
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IBM
From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
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Performance
IBM
SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.
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IBM
Never had slow response even on our very busy network
Read full review
Support Rating
IBM
I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
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IBM
I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
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In-Person Training
IBM
No answers on this topic
IBM
The trainers on the job are very smart with solutions and very able in teaching
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Online Training
IBM
No answers on this topic
IBM
The Platform is very handy and suggests further steps according my previous interests
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Implementation Rating
IBM
Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
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IBM
It surprised us with unpredictable case of use and brand new points of view
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Alternatives Considered
IBM
I have used R when I didn't have access to SPSS. It takes me longer because I'm terrible at syntax but it is powerful and it can be enjoyable to only have to wrestle with syntax and not a difficult UI.
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IBM
The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
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Scalability
IBM
I am neutral because I have not had to look into scalability since I am using as a student.
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IBM
It helped us in getting from 0 to DSX without getting lost
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Return on Investment
IBM
  • IBM SPSS has allowed me to quickly analyze data for research.
  • IBM SPSS has allowed me to complete analyses in order to submit research findings to conferences and complete manuscripts.
  • IBM SPSS has enabled me to meet research objectives set out in grant proposals.
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IBM
  • Could instantly show data driven insights to drive 20% incremental revenue over existing results
  • Still don't have a real use case for unstructured data like twitter feed
  • Some of the insights around user actions have driven new projects to automate mundane tasks
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