IBM SPSS Modeler vs. Toad Data Point

Overview
ProductRatingMost Used ByProduct SummaryStarting 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
Toad Data Point
Score 7.9 out of 10
N/A
Toad Data Point is a cross-platform, self-service, data-integration tool that simplifies data access, preparation and provisioning. It provides data connectivity and desktop data integration, and with the Workbook interface for business users, it provides simple-to-use visual query building and workflow automation.
$365
Pricing
IBM SPSS ModelerToad Data Point
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
Base Edition
$365
Pro Edition
$528
Offerings
Pricing Offerings
IBM SPSS ModelerToad Data Point
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
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
Community Pulse
IBM SPSS ModelerToad Data Point
Features
IBM SPSS ModelerToad Data Point
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Modeler
7.0
Ratings
18% below category average
Toad Data Point
-
Ratings
Connect to Multiple Data Sources7.00 Ratings00 Ratings
Extend Existing Data Sources7.00 Ratings00 Ratings
Best Alternatives
IBM SPSS ModelerToad Data Point
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.1 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerToad Data Point
Likelihood to Recommend
7.0
(0 ratings)
7.0
(0 ratings)
Usability
8.0
(0 ratings)
10.0
(0 ratings)
Support Rating
10.0
(0 ratings)
-
(0 ratings)
User Testimonials
IBM SPSS ModelerToad Data Point
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.
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Toad Data Point is the clear tool of choice if the end-user is interested in reports that are relatively simple to build using SQL code and export to Excel. It is less useful if the analyst also needs to run statistical models on the data and visualize the data for those functions I usually use RStudio or Jupyter Notebook which incorporates those features much more seamlessly.
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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.
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  • Ease of use. It is a very easy product to use without any particular training.
  • Multiple data source connection. It easily connects to multiple data sources which allows you to use different data sources to run reports.
  • Seamless application. Once you set everything up-- whether it is an FTP or export of data-- you can set it and forget it!
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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
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  • The program can error out when reconnecting to a database from a timeout but that is easily fixed by restarting the program.
  • If you aren't familiar with database tools the UI can be overwhelming to some.
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Usability
The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
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I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap
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Support Rating
The online support board is helpful and the free add ons are incredibly appreciated.
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No answers on this topic
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.
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TOAD excels at connecting to divergent data sources, but appears geared more to DBAs than to regular query users. Microsoft's offerings excel against Microsoft SQL Server, but sometimes struggle with other data sources. However, SSMS and vs code excel at many developer productivity/workflow enhancements. vs code, in particular, has a lively extension system that allows it to be tailored for development/querying/model building/etc. That flexibility comes at a cost - the learning curve is steep for new users. The tradeoff between complexity and power may not be good for some environments/users/situations.
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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
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  • It is the least common denominator - not particularly optimized for our environment or workflows.
  • Hangs or slowdowns add anywhere from 5% - 7% for projects utilizing large/complicated data setts. (This could be due to other IT-imposed constraints and not entirely due to TOAD.)
  • Trying to perform some operations requires reading documentation and experimenting in order to figure out the TOAD-specific approaches and commands.
  • It just works (when we understand it). Updates don't break things and things don't suddenly start behaving differently. Best of all, we don't mysteriously lose functionality.
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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.