Google Cloud AI vs. IBM SPSS Modeler

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud AI
Score 8.3 out of 10
N/A
Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.N/A
IBM SPSS Modeler
Score 7.8 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
Pricing
Google Cloud AIIBM SPSS Modeler
Editions & Modules
No answers on this topic
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
Offerings
Pricing Offerings
Google Cloud AIIBM SPSS Modeler
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
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
Best Alternatives
Google Cloud AIIBM SPSS Modeler
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
Medium-sized Companies
Posit
Posit
Score 9.1 out of 10
Mathematica
Mathematica
Score 8.2 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Posit
Posit
Score 9.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud AIIBM SPSS Modeler
Likelihood to Recommend
10.0
(6 ratings)
10.0
(6 ratings)
Likelihood to Renew
10.0
(1 ratings)
-
(0 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
7.3
(3 ratings)
10.0
(1 ratings)
Implementation Rating
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Google Cloud AIIBM SPSS Modeler
Likelihood to Recommend
Google
Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
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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.
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Pros
Google
  • good conversion from the voice to the text
  • speed in the conversion from voice to text
  • time-saving in the conversion activity
  • analysis of the results of the conversion in real time
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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.
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Cons
Google
  • Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
  • Customization of existing modules and libraries is harder and it does need time and experience to learn.
  • Google Cloud AI can do a better job in providing better support for Python and other coding languages.
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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.
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Likelihood to Renew
Google
We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
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IBM
No answers on this topic
Usability
Google
So far we have not had any problems with the application, it is extremely easy to use and it is also easy to install. It does not require much training since the instruction is quite clear for its execution and application in the procedures of the company. The team in charge of this application is very pleased to work with this app.
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IBM
No answers on this topic
Support Rating
Google
Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
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IBM
The online support board is helpful and the free add ons are incredibly appreciated.
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Implementation Rating
Google
In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
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IBM
No answers on this topic
Alternatives Considered
Google
These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
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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.
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Return on Investment
Google
  • Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
  • We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
  • The ROI seems positive since we are full in with Google, and the tools come along with the functionality.
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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.
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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.