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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM SPSS Modeler

    Score9.6 out of 10
    N/AIBM 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

    Jupyter Notebook

    Score8.6 out of 10
    N/AJupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
    Pricing
    IBM SPSS ModelerJupyter Notebook
    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 ModelerJupyter Notebook
    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
    Community Pulse
    IBM SPSS ModelerJupyter Notebook
    Considered Both Products
    IBM
    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
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    100%
    Would buy again
    23 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    23 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    96%
    Happy with the feature set
    22 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    17 Answers
    Implementation went as expected
    No answers on this topic
    95%
    Implementation went as expected
    20 Answers
    Features
    IBM SPSS ModelerJupyter Notebook
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM SPSS Modeler and Jupyter Notebook
    Feature
    IBM SPSS Modeler
    8.9
    2 Ratings
    6% above category average
    Jupyter Notebook
    9.0
    22 Ratings
    7% above category average
    Connect to Multiple Data Sources8.82 Ratings10.022 Ratings
    Extend Existing Data Sources8.82 Ratings10.021 Ratings
    Automatic Data Format Detection9.01 Ratings8.514 Ratings
    MDM Integration9.01 Ratings7.415 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM SPSS Modeler and Jupyter Notebook
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    7% above category average
    Jupyter Notebook
    7.0
    22 Ratings
    18% below category average
    Visualization9.01 Ratings6.022 Ratings
    Interactive Data Analysis9.01 Ratings8.022 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM SPSS Modeler and Jupyter Notebook
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    9% above category average
    Jupyter Notebook
    9.5
    22 Ratings
    15% above category average
    Interactive Data Cleaning and Enrichment9.01 Ratings10.021 Ratings
    Data Transformations9.01 Ratings10.022 Ratings
    Data Encryption9.01 Ratings8.514 Ratings
    Built-in Processors9.01 Ratings9.314 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM SPSS Modeler and Jupyter Notebook
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    Jupyter Notebook
    9.3
    22 Ratings
    10% above category average
    Multiple Model Development Languages and Tools9.01 Ratings10.021 Ratings
    Automated Machine Learning9.01 Ratings9.218 Ratings
    Single platform for multiple model development9.01 Ratings10.022 Ratings
    Self-Service Model Delivery9.01 Ratings8.020 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM SPSS Modeler and Jupyter Notebook
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    5% above category average
    Jupyter Notebook
    10.0
    20 Ratings
    15% above category average
    Flexible Model Publishing Options9.01 Ratings10.020 Ratings
    Security, Governance, and Cost Controls9.01 Ratings10.019 Ratings
    Best Alternatives
    IBM SPSS ModelerJupyter Notebook
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM SPSS ModelerJupyter Notebook
    Likelihood to Recommend
    9.7
    (8 ratings)
    10.0
    (23 ratings)
    Usability
    8.9
    (2 ratings)
    10.0
    (2 ratings)
    Support Rating
    10.0
    (1 ratings)
    9.0
    (1 ratings)
    User Testimonials
    IBM SPSS ModelerJupyter Notebook
    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.
    Incentivized
    Read full review
    Open Source
    I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
    Incentivized
    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.
    Incentivized
    Read full review
    Open Source
    • Simple and elegant code writing ability. Easier to understand the code that way.
    • The ability to see the output after each step.
    • The ability to use ton of library functions in Python.
    • Easy-user friendly interface.
    Incentivized
    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.
    Incentivized
    Read full review
    Open Source
    • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
    • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
    Incentivized
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    Usability
    IBM
    The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
    Incentivized
    Read full review
    Open Source
    Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
    Incentivized
    Read full review
    Support Rating
    IBM
    The online support board is helpful and the free add ons are incredibly appreciated.
    Incentivized
    Read full review
    Open Source
    I haven't had a need to contact support. However, all required help is out there in public forums.
    Incentivized
    Read full review
    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.
    Incentivized
    Read full review
    Open Source
    With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
    Incentivized
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    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.
    Incentivized
    Read full review
    Open Source
    • Positive impact: flexible implementation on any OS, for many common software languages
    • Positive impact: straightforward duplication for adaptation of workflows for other projects
    • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
    Incentivized
    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.