Angoss KnowledgeENTERPRISE [EOL] vs IBM Watson Studio comparison

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Executive Summary

We performed a comparison between Angoss KnowledgeENTERPRISE [EOL] and IBM Watson Studio based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: April 2024).
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Pricing and Cost Advice
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  • "Watson Studio's pricing is reasonable for what you get."
  • "IBM Watson Studio is a reasonably priced product"
  • "IBM Watson Studio is an expensive solution."
  • "The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
  • More IBM Watson Studio Pricing and Cost Advice →

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    Top Answer:From an improvement perspective, I would say that if the deployment environment and IBM Watson Studio's environment are separated, then it would be good. I would like them to be one and offer users a… more »
    Ranking
    Unranked
    In Data Science Platforms
    11th
    Views
    3,410
    Comparisons
    2,249
    Reviews
    5
    Average Words per Review
    426
    Rating
    8.2
    Comparisons
    Also Known As
    KnowledgeENTERPRISE, Datawatch Angoss, Angoss KnowledgeENTERPRISE
    Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
    Learn More
    IBM
    Video Not Available
    Overview

    KnowledgeENTERPRISE is a comprehensive data science platform that is integrated with Spark technology to provide unprecedented analytics and data processing capabilities. Its in-place analysis capability on distributed data eliminates data movement and allows users to stay within their Big Data environments.

    This single, fully-integrated software solution enables access to open source machine-learning libraries, Big Data technologies, collaboration and governance features, comprehensive advanced analytics functionality, and numerous deployment options allowing users to overcome challenges in Big Data ingestion, access, and results interpretation. 

    IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

    Sample Customers
    Barclays, ANZ, Fidelity, Comcast, Rogers, T-Mobile, DirecTV
    GroupM, Accenture, Fifth Third Bank
    Top Industries
    No Data Available
    REVIEWERS
    Manufacturing Company22%
    Insurance Company11%
    Marketing Services Firm11%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company11%
    Comms Service Provider8%
    Educational Organization7%
    Company Size
    No Data Available
    REVIEWERS
    Small Business71%
    Large Enterprise29%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise13%
    Large Enterprise67%
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    768,578 professionals have used our research since 2012.

    Angoss KnowledgeENTERPRISE [EOL] doesn't meet the minimum requirements to be ranked in Data Science Platforms while IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews. Angoss KnowledgeENTERPRISE [EOL] is rated 0.0, while IBM Watson Studio is rated 8.2. On the other hand, the top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". Angoss KnowledgeENTERPRISE [EOL] is most compared with Analance, whereas IBM Watson Studio is most compared with Databricks, Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI and Amazon Comprehend.

    See our list of best Data Science Platforms vendors.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.