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

IBM SPSS Modeler

IBM Watson Studio on Cloud Pak for Data

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
IBM SPSS Modeler	Score 7.1 out of 10	N/A	IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.	$4,670 per year
IBM Watson Studio	Score 10.0 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 Modeler

IBM Watson Studio on Cloud Pak for Data

Editions & Modules

IBM SPSS Modeler Personal: 4,670
per year
IBM SPSS Modeler Professional: 7,000
per year
IBM SPSS Modeler Premium: 11,600
per year
IBM SPSS Modeler Gold: contact IBM
per year

No answers on this topic

Offerings

Pricing Offerings
IBM SPSS Modeler	IBM Watson Studio
Free Trial
Yes	No
Free/Freemium Version
No	No
Premium Consulting/Integration Services
No	No

Entry-level Setup Fee

Optional

No setup fee

Additional Details

IBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.

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More Pricing Information

Community Pulse
	IBM SPSS Modeler	IBM Watson Studio on Cloud Pak for Data
Considered Both Products	IBM SPSS Modeler George DeMaagd, PharmD.,BCPS Professor of Pharmacy and Associate Dean of Academic Administration College of Pharmacy Chose IBM SPSS Modeler Python requires knowledge of programming, higher learning curve vs IBM SPSS Modeler Incentivized Helpful? Tim Daciuk Director, Advanced Analytics Chose IBM SPSS Modeler IBM SPSS Modeler is considerably easier to use. It allows for very rapid development and the ability to get to a goal quickly. There is no need to learn a new programming language so the analyst has the ability to focus on the problem rather than the pedantics of managing … Incentivized Helpful? Ben Holmes Senior Data Scientist Chose IBM SPSS Modeler We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and … Incentivized Helpful? Char Paul Psych n Stats Tutor Chose IBM SPSS Modeler JASP NVivo R Incentivized Helpful? Akos Krommer, CISA, ACDA Solution Specialist (Data Analytics) Chose IBM SPSS Modeler SPSS has a great set of analytical models, but SPSS is especially strong (compared to other tools) in complex statistical modeling and predictive analytics/statistics. However, the data connectivity features of SPSS are not the best, as the data sources SPSS can work with are … Incentivized Helpful? Himanshu Singh Product Manager Chose IBM SPSS Modeler The field of data analytics has important value for each organization. IBM SPSS Modeler is one of the leaders in this highly competitive vertical. IBM SPSS is very intuitive compared with others, and has reduced the complexity. This software has various good functionalities … Incentivized Helpful? Jesús Quintana Gerente de Ventas Sector Gobierno Chose IBM SPSS Modeler When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers. Incentivized Helpful? JM Jim McDonough President Chose IBM SPSS Modeler SPSS Modeler provides a much more intuitive approach in helping you create and test models. Incentivized Helpful?	IBM Watson Studio Kapil Bansal Web Developer Chose IBM Watson Studio Google Cloud may be a good place but it is not as easy to understand as IBM Watson is. Google Cloud has a lot of things and it is terrifying for a beginner. You need hours of specialization for that. On other hand, anyone can start using IBM Waston just by the following … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio Data ingestion Batch data processing Built-in connectors to Python Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio Anaconda and Jupyter Notebook Incentivized Helpful? LR Li Rong Software Engineer Chose IBM Watson Studio AWS Sagemaker is a well-established product that supports on-demand notebooks, data pipelines, and so on, however, it also comes with the learning overhead of the whole AWS stack. It does allow per-defined models, but the benefit of using IBM Watson Studio is that users are … Incentivized Helpful? Venugopal Dontaraboyana IT Specialist Chose IBM Watson Studio Organization of data, use of data, manage the data, visualize the data is easy. Use of the environment for any project. We can use python or R or Scala in the notebook. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio It provides better user experience. All your data on cloud and does not take up space locally. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio I think they are very similar but IBM Watson is not good enough yet to pay for the services that I can already get from Jupyter Notebook. Incentivized Helpful? John Robert Uy President Chose IBM Watson Studio Easy to use, but still requires a lot of coding to use. There is no ranking of models used and models are not persistent, which means you have to keep running the models again every time you leave the session. The filesystem is clunky and need to keep authorizing Google Drive … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio 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 … Incentivized Helpful? NARESH SAMPARA Research Associate Chose IBM Watson Studio IBM offers a deep neural network training workflow, with a flow editor interface similar to the one used in Azure ML Studio. However, the custom build modeling in IBM has notebooks such as Jupiter to program models manually using popular frameworks like TensorFlow, … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio As it offers more features and can be used for several applications like AI,ML,DS etc., Incentivized Helpful? MW Michael Weaver Logistic Assistance Representave (LAR) Chose IBM Watson Studio With my experience on Jupyter Notebook I think both are good and currently more comfortable with Watson Studio product. With Jupyter it's open source (free) is always good. "Lots of languages (50), data visualization with Seaborn, work with the building blocks in a flexible and … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio We didn’t evaluate other products but we liked what we saw in Watson Studio. Incentivized Helpful? Christopher Penn Co-Founder and Chief Innovator Chose IBM Watson Studio As an IBM Business Partner, we are financially incentivized to recommend and deploy IBM solutions where it makes sense to do so for the customer. Against other solutions, few have the governance and security that IBM offers, which is essential for any kind of work in highly … Incentivized Helpful? ashish devassy Manager Chose IBM Watson Studio We did not use any other one so this would be hard for me to answer. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio They are close, but I feel Alteryx is more of an enhanced Jupyter capability, whereas WS is more of an enterprise solution for multiple teams Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio Not applicable Incentivized Helpful? Van West Chief Strategy Officer Chose IBM Watson Studio Less satisfied with Watson and lack of support. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio I am excited with the roadmap of Watson Studio incorporating SPSS Modeler in the offerings. Incentivized Helpful? Isaiah King Founding Member Chose IBM Watson Studio Watson Studio was our choice in data management because its "all-in-one" packaging. Watson studio also stood out to us because it was more affordable and free for our organization to try out. We also greatly value the open source ecosystem Watson Studio has fostered. Incentivized Helpful? Dr. George Ng Lecturer (Software and Information Technology Council) Chose IBM Watson Studio AWS Sagemaker is new, and I personally think it's better than sliced bread. There's very little set up to do. Watson Studio needs to up its game against Sagemaker. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio AWS stacks up very favourably against Watson Studio, and in fact this is what the customer ultimately chose over Watson Studio after an evaluation period due to the sophistication, maturity, security, and capabilities of the AWS components. The downsides of AWS are having to … Incentivized Helpful? Sebastian Ferro Consultant Sr. Chose IBM Watson Studio Watson Studio offers more capabilities and diversity in tools and services. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio 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. Incentivized Helpful? Andrea Bardone consultant Chose IBM Watson Studio IBM DSx is more comprehensive and easy to use, IBM Data science experience has many connectors to the data source and guarantees the portability with your old projects. Incentivized Helpful?

Features

IBM SPSS Modeler

IBM Watson Studio on Cloud Pak for Data

Platform Connectivity

Comparison of Platform Connectivity features of Product A and Product B
	IBM SPSS Modeler 7.0 Ratings 18% below category average	IBM Watson Studio on Cloud Pak for Data 8.1 Ratings 3% below category average
Connect to Multiple Data Sources	7.00 Ratings	8.00 Ratings
Extend Existing Data Sources	7.00 Ratings	8.00 Ratings
Automatic Data Format Detection	00 Ratings	10.00 Ratings
MDM Integration	00 Ratings	6.40 Ratings

Data Exploration

Comparison of Data Exploration features of Product A and Product B
	IBM SPSS Modeler - Ratings	IBM Watson Studio on Cloud Pak for Data 10.0 Ratings 18% above category average
Visualization	00 Ratings	10.00 Ratings
Interactive Data Analysis	00 Ratings	10.00 Ratings

Data Preparation

Comparison of Data Preparation features of Product A and Product B
	IBM SPSS Modeler - Ratings	IBM Watson Studio on Cloud Pak for Data 9.5 Ratings 15% above category average
Interactive Data Cleaning and Enrichment	00 Ratings	10.00 Ratings
Data Transformations	00 Ratings	10.00 Ratings
Data Encryption	00 Ratings	8.00 Ratings
Built-in Processors	00 Ratings	10.00 Ratings

Platform Data Modeling

Comparison of Platform Data Modeling features of Product A and Product B
	IBM SPSS Modeler - Ratings	IBM Watson Studio on Cloud Pak for Data 9.5 Ratings 13% above category average
Multiple Model Development Languages and Tools	00 Ratings	10.00 Ratings
Automated Machine Learning	00 Ratings	10.00 Ratings
Single platform for multiple model development	00 Ratings	10.00 Ratings
Self-Service Model Delivery	00 Ratings	8.00 Ratings

Model Deployment

Comparison of Model Deployment features of Product A and Product B
	IBM SPSS Modeler - Ratings	IBM Watson Studio on Cloud Pak for Data 8.0 Ratings 6% below category average
Flexible Model Publishing Options	00 Ratings	9.00 Ratings
Security, Governance, and Cost Controls	00 Ratings	7.00 Ratings

Best Alternatives
	IBM SPSS Modeler	IBM Watson Studio on Cloud Pak for Data
Small Businesses	Jupyter Notebook Score 9.4 out of 10	Jupyter Notebook Score 9.4 out of 10
Medium-sized Companies	Posit Score 10.0 out of 10	Posit Score 10.0 out of 10
Enterprises	Posit Score 10.0 out of 10	Posit Score 10.0 out of 10
All Alternatives	View all alternatives	View all alternatives

User Ratings
	IBM SPSS Modeler	IBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend	7.0 (0 ratings)	8.0 (0 ratings)
Likelihood to Renew	- (0 ratings)	8.2 (0 ratings)
Usability	8.0 (0 ratings)	9.6 (0 ratings)
Availability	- (0 ratings)	8.2 (0 ratings)
Performance	- (0 ratings)	8.2 (0 ratings)
Support Rating	10.0 (0 ratings)	8.2 (0 ratings)
In-Person Training	- (0 ratings)	8.2 (0 ratings)
Online Training	- (0 ratings)	8.2 (0 ratings)
Implementation Rating	- (0 ratings)	7.3 (0 ratings)
Product Scalability	- (0 ratings)	8.2 (0 ratings)
Vendor post-sale	- (0 ratings)	7.3 (0 ratings)
Vendor pre-sale	- (0 ratings)	8.2 (0 ratings)

User Testimonials
	IBM SPSS Modeler	IBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend	Modeler is well suited for understanding consumer data. The ability to create a prediction and then to understand what is driving that prediction is strong in Modeler. Modeler is closely aligned with the CRISP-DM data mining approach meaning it is not just the 'doing' but also the theoretical background behind the development of data mining models. Incentivized Tim Daciuk Director, Advanced Analytics Read full review	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. Incentivized Verified User Anonymous Read full review
Pros	A very nice and easy to use interface. A great variety of analytics, from statistical calculation to data validation and predictive statistics. Has a steep learning curve. Incentivized Akos Krommer, CISA, ACDA Solution Specialist (Data Analytics) Read full review	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. Incentivized Christopher Penn Co-Founder and Chief Innovator Read full review
Cons	Some Analyses aren't there out of the box but can be added through open languages like R and Python. Graphs could be better. Unable to read data stored in OLAP databases Incentivized Jesús Quintana Gerente de Ventas Sector Gobierno Read full review	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 Incentivized Verified User Anonymous Read full review
Likelihood to Renew	No answers on this topic	because we find out that DSX results have improved our approach to the whole subject (data, models, procedures) Incentivized Davide Tognon Engineering Technician Read full review
Usability	The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources Incentivized JM Jim McDonough President Read full review	The UI flawlessly merges this offering by providing a neat, minimal, responsive interface Incentivized Isaiah King Founding Member Read full review
Reliability and Availability	No answers on this topic	From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected Incentivized Davide Tognon Engineering Technician Read full review
Performance	No answers on this topic	Never had slow response even on our very busy network Incentivized Davide Tognon Engineering Technician Read full review
Support Rating	The online support board is helpful and the free add ons are incredibly appreciated. Incentivized Char Paul Psych n Stats Tutor Read full review	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 Incentivized Davide Tognon Engineering Technician Read full review
In-Person Training	No answers on this topic	The trainers on the job are very smart with solutions and very able in teaching Incentivized Davide Tognon Engineering Technician Read full review
Online Training	No answers on this topic	The Platform is very handy and suggests further steps according my previous interests Incentivized Davide Tognon Engineering Technician Read full review
Implementation Rating	No answers on this topic	It surprised us with unpredictable case of use and brand new points of view Incentivized Davide Tognon Engineering Technician Read full review
Alternatives Considered	We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and I really like several of the helpful components for usability for SPSS like peaks into nodes. Incentivized Ben Holmes Senior Data Scientist Read full review	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. Incentivized Verified User Anonymous Read full review
Scalability	No answers on this topic	It helped us in getting from 0 to DSX without getting lost Incentivized Davide Tognon Engineering Technician Read full review
Return on Investment	I am able to study and work from home sustainably I can help others have a high quality university education experience to graduate confident and competent to meet gaps in the wider community Market research for my business Help other small businesses to create viable and high quality products and services Contribute to research projects: ethical, high quality data analyses and interpretation Incentivized Char Paul Psych n Stats Tutor Read full review	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 Incentivized Verified User Anonymous Read full review
ScreenShots	IBM SPSS Modeler Screenshots