IBM SPSS Modeler vs. Cortana (discontinued)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Modeler
Score 7.4 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.
$499
per month
Cortana (discontinued)
Score 8.0 out of 10
N/A
Microsoft's Cortana was a general purpose productivity assistant, that has been deprecated as a standalone product.N/A
Pricing
IBM SPSS ModelerCortana (discontinued)
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 ModelerCortana (discontinued)
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsIBM 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.—
More Pricing Information
Features
IBM SPSS ModelerCortana (discontinued)
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Modeler
7.0
1 Ratings
17% below category average
Cortana (discontinued)
-
Ratings
Connect to Multiple Data Sources7.01 Ratings00 Ratings
Extend Existing Data Sources7.01 Ratings00 Ratings
Best Alternatives
IBM SPSS ModelerCortana (discontinued)
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.0 out of 10
ZoomInfo Chat
ZoomInfo Chat
Score 8.0 out of 10
Medium-sized Companies
Posit
Posit
Score 9.6 out of 10
Genesys DX (discontinued)
Genesys DX (discontinued)
Score 10.0 out of 10
Enterprises
Posit
Posit
Score 9.6 out of 10
Genesys DX (discontinued)
Genesys DX (discontinued)
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerCortana (discontinued)
Likelihood to Recommend
7.0
(7 ratings)
7.1
(3 ratings)
Usability
8.0
(1 ratings)
-
(0 ratings)
Support Rating
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
IBM SPSS ModelerCortana (discontinued)
Likelihood to Recommend
IBM
Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
Read full review
Microsoft
It's easy for anyone who is expecting some simple AI problems like fetching the keywords, understanding the intent, language translation, etc. to be solved from an existing database and all they need is to connect to their APIs via a subscription model. But for complex use cases, there is still room for improvement like customization of underlying AI models for a specific use case like identifying some unique identifiers with respect to industry.
Read full review
Pros
IBM
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
Read full review
Microsoft
  • Being hosted in Azure solves a massive hosting problem
  • The language understanding system has the ability to revolutionize many vertical markets
  • Integrating with Cortana Analytics was really simple due to easy to understand documentation
Read full review
Cons
IBM
  • Has very old style graphs, with lots of limitations.
  • Some advanced statistical functions cannot be done through the menu.
  • The data connectivity is not that extensive.
  • It's an expensive tool.
Read full review
Microsoft
  • More partnerships with colleges and schools to increase the workforce with technical knowledge (increase local workforce)
  • Have more online training and documentation in other languages
  • Have affordable prices for students
Read full review
Usability
IBM
It is fairly user friendly, with limited practice. Similar to many statistical programs it requires a little time to get comfortable with, but once you use if for a project, the second time around is much easier.
Read full review
Microsoft
No answers on this topic
Support Rating
IBM
The online support board is helpful and the free add ons are incredibly appreciated.
Read full review
Microsoft
No answers on this topic
Alternatives Considered
IBM
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.
Read full review
Microsoft
IBM Watson Assistant has been early into this market and has improved a lot over time compared to Azure AI Cortana. More documentation related to the services. But Ease of integration Azure AI ranks over IBM Watson Assistant. And again in terms of services offered under the ecosystem, Azure AI precedes IBM Watson Assitant.
Read full review
Return on Investment
IBM
  • Positive - Ease of decision making and reduction in product life cycle time.
  • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
  • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
Read full review
Microsoft
  • Difficult to ascertain the ROI as we are a software house who have developed a module in our application using Cortana. However for companies that use our software I would say the use of sentiment analysis in our application could free up at least 1 full time resource to be used elsewhere in their organisation.
Read full review
ScreenShots

IBM SPSS Modeler Screenshots

Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.