IBM Watson Studio vs Teradata Analytics [EOL] comparison

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3,410 views|2,249 comparisons
100% willing to recommend
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views| comparisons
50% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between IBM Watson Studio and Teradata Analytics [EOL] 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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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It has a lot of data connectors, which is extremely helpful.""The system's ability to take a look at data, segment it and then use that data very differently.""Watson Studio is very stable.""It is a stable, reliable product.""The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video.""For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks.""It is a very stable and reliable solution.""It has greatly improved the performance because it is standardized across the company."

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"nPath has made journey/path analysis much easier.""It has been fantastic for running complete data sets (no sampling required).""Provides ease of formulating a solution based on SQL-like queries."

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Cons
"Watson Studio would be improved with a clearer path for the deployment of docker images.""Some of the solutions are really good solutions but they can be a little too costly for many.""I think maybe the support is an area where it lacks.""The initial setup was complex.""It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs.""The solution's interface is very slow at times.""I want IBM's technical support team to provide more specific answers to queries.""Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."

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"I would like to see more/better documentation. They also need to enhance analytic/data science algorithms.""I have found some problems with the figures depicted on graphs and figures shown, like scores which could not be negative but which were depicted as such.""We have struggled with uptime. Some of the features need to be updated."

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Pricing and Cost Advice
  • "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."
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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 »
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    Ranking
    11th
    Views
    3,410
    Comparisons
    2,249
    Reviews
    5
    Average Words per Review
    426
    Rating
    8.2
    Unranked
    In Data Science Platforms
    Comparisons
    Also Known As
    Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
    Teradata Aster Analytics, Aster Analytics
    Learn More
    IBM
    Video Not Available
    Overview

    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.

    Teradata Aster® Analytics Portfolio provides a suite of ready-to-use, multi-genre advanced analytics functions that empowers business users to uncover and operationalize non-intuitive insights. Teradata Aster Analytics includes the Aster Database, Aster Client and the Aster Portfolio that consists of SQL, SQL-MapReduce and Graph functions for multi-genre advanced analytics. These functions provide everything from data acquisition and preparation to analytic modeling and visualization.

    Sample Customers
    GroupM, Accenture, Fifth Third Bank
    Information Not Available
    Top Industries
    REVIEWERS
    Manufacturing Company22%
    Insurance Company11%
    Marketing Services Firm11%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company11%
    Comms Service Provider8%
    Educational Organization8%
    No Data Available
    Company Size
    REVIEWERS
    Small Business71%
    Large Enterprise29%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise13%
    Large Enterprise66%
    No Data Available
    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.
    767,847 professionals have used our research since 2012.

    IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews while Teradata Analytics [EOL] doesn't meet the minimum requirements to be ranked in Data Science Platforms. IBM Watson Studio is rated 8.2, while Teradata Analytics [EOL] is rated 7.0. The top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". On the other hand, the top reviewer of Teradata Analytics [EOL] writes "Streamlines formulating solutions based on SQL-like queries". IBM Watson Studio is most compared with Databricks, Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI and Amazon Comprehend, whereas Teradata Analytics [EOL] is most compared with .

    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.