IBM Watson Studio

IBM Watson Studio

About TrustRadius Scoring
Score 8.7 out of 100
IBM Watson Studio on Cloud Pak for Data

Overview

Recent Reviews

Review of IBM services

8
February 04, 2021
I am into mentoring services, so I teach and assist learners on this technology.
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Early review of IBM Watson

6
February 04, 2021
We mostly use IBM Watson Studio for its Notebook features for running Python codes. It allows us to work on the code together and generate …
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Experienced Analysis with IBM Watson

8
January 02, 2021
We primarily use IBM Watson Studio (formerly IBM Data Science Experience) as training for developing analytical skills in Coursera courses.
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Beginner Guide Review

7
December 01, 2020
IBM Watson studio is being used to host Juypter Notebooks. These notebooks contains analyses for various projects. The primary project …
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Review on IBM Watson

9
November 25, 2020
I have been using IBM Watson [Studio (formerly IBM Data Science Experience)] for the purpose of Data science course which was offered by …
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Reviewer Sentiment

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Negative ()
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Awards

TrustRadius Award Top Rated 2021

Popular Features

View all 16 features

Interactive Data Analysis (21)

7.7
77%

Visualization (21)

7.7
77%

Connect to Multiple Data Sources (21)

7.7
77%

Extend Existing Data Sources (21)

7.4
74%

Video Reviews

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Pricing

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What is IBM Watson Studio?

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

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Alternatives Pricing

What is Anaconda?

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What is Azure Machine Learning?

Microsoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.

Features Scorecard

Platform Connectivity

7.2
72%

Data Exploration

7.7
77%

Data Preparation

7.6
76%

Platform Data Modeling

7.5
75%

Model Deployment

6.8
68%

Product Details

What is IBM Watson Studio?

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.

IBM Watson Studio Competitors

IBM Watson Studio Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Comparisons

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Frequently Asked Questions

What is IBM Watson Studio's best feature?

Reviewers rate Built-in Processors highest, with a score of 7.9.

Who uses IBM Watson Studio?

The most common users of IBM Watson Studio are from Enterprises (1,001+ employees) and the Information Technology & Services industry.

Reviews

(1-25 of 54)
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Kapil Bansal | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Google Cloud may be a good place but it is not as easy to understand as IBM Watson is. Google Cloud has a lot of things and it is terrifying for a beginner. You need hours of specialization for that. On other hand, anyone can start using IBM Waston just by the following documentation.
Score 7 out of 10
Vetted Review
Verified User
Review Source
AWS Sagemaker is a well-established product that supports on-demand notebooks, data pipelines, and so on, however, it also comes with the learning overhead of the whole AWS stack. It does allow per-defined models, but the benefit of using IBM Watson Studio is that users are able to leverage per-trained models and significantly reduce training time.
Venugopal Dontaraboyana | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Organization of data, use of data, manage the data, visualize the data is easy. Use of the environment for any project. We can use python or R or Scala in the notebook. Data cleaning a remarkable feature of IMB Watson Studio. Deployment of ML models is easy. Monitoring the Models is also easy.
John Robert Uy | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Easy to use, but still requires a lot of coding to use. There is no ranking of models used and models are not persistent, which means you have to keep running the models again every time you leave the session. The filesystem is clunky and need to keep authorizing Google Drive to save any datasets.
Score 8 out of 10
Vetted Review
Verified User
Review Source
The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
NARESH SAMPARA | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
IBM offers a deep neural network training workflow, with a flow editor interface similar to the one used in Azure ML Studio. However, the custom build modeling in IBM has notebooks such as Jupiter to program models manually using popular frameworks like TensorFlow, sci-kit-learn, PyTorch, XGboost, PMML, and IBM SPSS.
Score 9 out of 10
Vetted Review
Verified User
Review Source
With my experience on Jupyter Notebook I think both are good and currently more comfortable with Watson Studio product. With Jupyter it's open source (free) is always good. "Lots of languages (50), data visualization with Seaborn, work with the building blocks in a flexible and integrated manner • modern JavaScript development: npm-based packaging, typescript, phosphor.js, • clean model/view separation, • well separated public/private APIs, fully extensible by third parties, high performance and Design."
Christopher Penn | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Reseller
Review Source
As an IBM Business Partner, we are financially incentivized to recommend and deploy IBM solutions where it makes sense to do so for the customer. Against other solutions, few have the governance and security that IBM offers, which is essential for any kind of work in highly regulated industries. IBM's solution may not be the sexiest, but it's the most bulletproof.
May 08, 2018

Watson vs. DATA

Isaiah King | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Watson Studio was our choice in data management because its "all-in-one" packaging. Watson studio also stood out to us because it was more affordable and free for our organization to try out. We also greatly value the open source ecosystem Watson Studio has fostered.
Score 7 out of 10
Vetted Review
Reseller
Review Source
  • AWS
AWS stacks up very favourably against Watson Studio, and in fact this is what the customer ultimately chose over Watson Studio after an evaluation period due to the sophistication, maturity, security, and capabilities of the AWS components. The downsides of AWS are having to pay for every byte downloaded, and the steep learning curve. The advantages of the Watson Studio environment over AWS are: better support for hybrid deployments (not everything has to go in the cloud); ease of integration with other Watson APIs and components (e.g. NLU, Speech to Text, etc.), and cheaper usage costs
Score 8 out of 10
Vetted Review
Verified User
Review Source
The learning curve for DSX is smaller compared to other tools. The data science user base often has preferred tools that they have used previously which are often not DSX which makes adoption of DSX by trained data scientists harder than new users.
Andrea Bardone | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
IBM DSx is more comprehensive and easy to use, IBM Data science experience has many connectors to the data source and guarantees the portability with your old projects.