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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    OpenText Magellan

    Score9 out of 10
    N/AOpenText Magellan Analytics Suite leverages a comprehensive set of data analytics software to identify patterns, relationships and trends through data visualizations and interactive dashboards.N/A

    TensorFlow

    Score7.6 out of 10
    N/ATensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.N/A
    Pricing
    OpenText MagellanTensorFlow
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    OpenText MagellanTensorFlow
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Features
    OpenText MagellanTensorFlow
    BI Standard Reporting
    Comparison of BI Standard Reporting features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    7.0
    2 Ratings
    15% below category average
    TensorFlow
    -
    Ratings
    Customizable dashboards7.02 Ratings00 Ratings
    Report Formatting Templates7.01 Ratings00 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    8.3
    3 Ratings
    4% above category average
    TensorFlow
    -
    Ratings
    Drill-down analysis8.03 Ratings00 Ratings
    Formatting capabilities8.03 Ratings00 Ratings
    Integration with R or other statistical packages9.01 Ratings00 Ratings
    Report sharing and collaboration8.02 Ratings00 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    8.3
    2 Ratings
    1% above category average
    TensorFlow
    -
    Ratings
    Publish to Web8.02 Ratings00 Ratings
    Publish to PDF8.02 Ratings00 Ratings
    Report Versioning9.02 Ratings00 Ratings
    Report Delivery Scheduling8.02 Ratings00 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    8.0
    1 Ratings
    0% above category average
    TensorFlow
    -
    Ratings
    Pre-built visualization formats (heatmaps, scatter plots etc.)9.01 Ratings00 Ratings
    Predictive Analytics7.01 Ratings00 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    9.0
    2 Ratings
    6% above category average
    TensorFlow
    -
    Ratings
    Role-Based Security Model9.02 Ratings00 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)9.02 Ratings00 Ratings
    Single Sign-On (SSO)9.02 Ratings00 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    7.0
    2 Ratings
    10% below category average
    TensorFlow
    -
    Ratings
    Responsive Design for Web Access7.02 Ratings00 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile7.02 Ratings00 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of OpenText Magellan and TensorFlow
    Feature
    OpenText Magellan
    6.2
    1 Ratings
    22% below category average
    TensorFlow
    -
    Ratings
    REST API5.01 Ratings00 Ratings
    Javascript API9.01 Ratings00 Ratings
    Java API5.01 Ratings00 Ratings
    Themeable User Interface (UI)7.01 Ratings00 Ratings
    Customizable Platform (Open Source)5.01 Ratings00 Ratings
    Best Alternatives
    OpenText MagellanTensorFlow
    Small Businesses
    Cyfe
    Score4 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Medium-sized Companies
    Qlik Cloud Analytics (Qlik Sense)
    Score8.1 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    Sisense
    Score6.9 out of 10
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    OpenText MagellanTensorFlow
    Likelihood to Recommend
    9.0
    (11 ratings)
    6.0
    (15 ratings)
    Likelihood to Renew
    3.9
    (9 ratings)
    -
    (0 ratings)
    Usability
    9.0
    (1 ratings)
    9.0
    (1 ratings)
    Support Rating
    9.0
    (2 ratings)
    9.1
    (2 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.0
    (1 ratings)
    Data Sharing and Collaboration
    9.0
    (8 ratings)
    -
    (0 ratings)
    Data Sources
    8.0
    (8 ratings)
    -
    (0 ratings)
    User Testimonials
    OpenText MagellanTensorFlow
    Likelihood to Recommend
    OpenText
    If you do not have a large budget and are a large organization, I would steer clear of Actuate. If you are looking to do very complex washboarding, I would not use them. Your developers have to be very skilled to work with this. Plan to bring in consultants if necessary to help your process. Adhoc reporting is weak. If your pricing is user based and you expand, this could be very expensive.
    Read full review
    Open Source
    TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
    Incentivized
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    Pros
    OpenText
    • The report outputs can vary across different types such as HTML, PDF, and Excel
    • Their open source offering is very sufficient
    • There are great boards and blogs for developers and engineers to expand and use their features.
    • The people from the company that I've worked with are professional and courteous.
    Incentivized
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    Open Source
    • A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
    • Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
    • Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.
    Incentivized
    Read full review
    Cons
    OpenText
    • The documentation on all the available features, but most importantly on the scripting side, can be improved
    • The standard look & feel of some basic options, like parameter selection or sorting and filtering, looks dated and can't be customized
    • The server portal needs to provide better tools
    • More integration is needed with other OpenText products
    Incentivized
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    Open Source
    • RNNs are still a bit lacking, compared to Theano.
    • Cannot handle sequence inputs
    • Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
    Read full review
    Likelihood to Renew
    OpenText
    I am no longer working for the company that was using Actuate but I believe they would continue to use it because the stitching costs would be to high. It would require a complete rewrite of the reports and the never version of Actuate (BIRT) even required an almost complete report rewrite
    Incentivized
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    Open Source
    No answers on this topic
    Usability
    OpenText
    It is quite intuitive to use. It is fit specifically for doing sentiment, emotion, and intention analysis as well as text classification and text summarization. I would have given 10 if it is fit for the purpose of doing image processing and analysis as well. There is a huge market to analyze video and image data.
    Incentivized
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    Open Source
    Support of multiple components and ease of development.
    Incentivized
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    Support Rating
    OpenText
    Always there on the front and backend for us and the client.
    Read full review
    Open Source
    Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
    Incentivized
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    Implementation Rating
    OpenText
    No answers on this topic
    Open Source
    Use of cloud for better execution power is recommended.
    Incentivized
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    Alternatives Considered
    OpenText
    It is vastly superior to these in many ways, for complex reporting it is a much more sophisticated solution. Visualizations are very good. Javascript extensibility is very powerful, others don't support this or as well. Pentaho and MS are both OLAP oriented. Pentaho is moving more toward big data, which was not our primary focus. Others are stuck in the Crystal Reports Band metaphor.
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    Open Source
    Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
    Incentivized
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    Return on Investment
    OpenText
    • Actuate can handle 50 to 60 sub reports inside a report very well.
    • Dynamically creating the datasource, chart, graph, reports are the main advantages. We can do any level of drilling, and can create a performance matrix dashboard efficiently.
    Read full review
    Open Source
    • Learning is s bit difficult takes lot of time.
    • Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
    • Once you have learned this, it make your job very easy of getting the good result.
    Incentivized
    Read full review
    ScreenShots

    OpenText Magellan Screenshots

    Screenshot of A Magellan BI & Reporting dashboard that an individual can interact with and personalize to their needs, such as changing chart types or computations.Screenshot of Magellan Data Discovery provides a Smart User Interface, designed to equip new users and users seeking a more streamlined set of features for insightsScreenshot of Magellan Data Discovery provides an Advanced User Interface that allows data analytics pros to leverage its breadth of sophisticated capabilities for insightsScreenshot of Magellan Text Mining insights can be displayed within easy-to-use dashboards.Screenshot of Data scientists can create visualizations within the Magellan Notebook and see it dynamically update as they write changes to it.