IBM Watson Studio on Cloud Pak for Data

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Watson Studio
Score 8.0 out of 10
N/A
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.N/A
Pricing
IBM Watson Studio on Cloud Pak for Data
Editions & Modules
No answers on this topic
Offerings
Pricing Offerings
IBM Watson Studio
Free Trial
No
Free/Freemium Version
No
Premium Consulting/Integration Services
No
Entry-level Setup FeeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM Watson Studio on Cloud Pak for Data
Considered Both Products
IBM Watson Studio
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
  • Data ingestion
  • Batch data processing
  • Built-in connectors to Python
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
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.
Chose IBM Watson Studio on Cloud Pak for Data
It provides better user experience. All your data on cloud and does not take up space locally.
Chose IBM Watson Studio on Cloud Pak for Data
I think they are very similar but IBM Watson is not good enough yet to pay for the services that I can already get from Jupyter Notebook.
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
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, …
Chose IBM Watson Studio on Cloud Pak for Data
As it offers more features and can be used for several applications like AI,ML,DS etc.,
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
We didn’t evaluate other products but we liked what we saw in Watson Studio.
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
They are close, but I feel Alteryx is more of an enhanced Jupyter capability, whereas WS is more of an enterprise solution for multiple teams
Chose IBM Watson Studio on Cloud Pak for Data
Not applicable
Chose IBM Watson Studio on Cloud Pak for Data
Less satisfied with Watson and lack of support.
Chose IBM Watson Studio on Cloud Pak for Data
I am excited with the roadmap of Watson Studio incorporating SPSS Modeler in the offerings.
Chose IBM Watson Studio on Cloud Pak for Data
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.
Chose IBM Watson Studio on Cloud Pak for Data
AWS Sagemaker is new, and I personally think it's better than sliced bread. There's very little set up to do. Watson Studio needs to up its game against Sagemaker.
Chose IBM Watson Studio on Cloud Pak for Data
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 …
Chose IBM Watson Studio on Cloud Pak for Data
Watson Studio offers more capabilities and diversity in tools and services.
Chose IBM Watson Studio on Cloud Pak for Data
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.
Chose IBM Watson Studio on Cloud Pak for Data
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.
Top Pros
Top Cons
Features
IBM Watson Studio on Cloud Pak for Data
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
8.1
22 Ratings
4% below category average
Connect to Multiple Data Sources8.022 Ratings
Extend Existing Data Sources8.022 Ratings
Automatic Data Format Detection9.921 Ratings
MDM Integration6.414 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
10.0
22 Ratings
17% above category average
Visualization10.022 Ratings
Interactive Data Analysis10.022 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
14% above category average
Interactive Data Cleaning and Enrichment9.922 Ratings
Data Transformations10.021 Ratings
Data Encryption8.020 Ratings
Built-in Processors10.021 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
11% above category average
Multiple Model Development Languages and Tools10.021 Ratings
Automated Machine Learning9.922 Ratings
Single platform for multiple model development9.922 Ratings
Self-Service Model Delivery8.020 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
8.0
22 Ratings
7% below category average
Flexible Model Publishing Options9.022 Ratings
Security, Governance, and Cost Controls7.022 Ratings
Best Alternatives
IBM Watson Studio on Cloud Pak for Data
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.3 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternatives
User Ratings
IBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
8.0
(65 ratings)
Likelihood to Renew
8.2
(1 ratings)
Usability
9.6
(2 ratings)
Availability
8.2
(1 ratings)
Performance
8.2
(1 ratings)
Support Rating
8.2
(1 ratings)
In-Person Training
8.2
(1 ratings)
Online Training
8.2
(1 ratings)
Implementation Rating
7.3
(1 ratings)
Product Scalability
8.2
(1 ratings)
Vendor post-sale
7.3
(1 ratings)
Vendor pre-sale
8.2
(1 ratings)
User Testimonials
IBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
IBM
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
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Pros
IBM
  • Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
  • SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
  • Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
  • Estimator validation lets data scientists test and prove different models.
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Cons
IBM
  • The cost is steep and so only companies with resources can afford it
  • It will be nice to have Chinese versions so that Chinese engineers can also use it easily
  • It takes a while to learn how to input different kinds of skin defects for detection
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Likelihood to Renew
IBM
because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
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Usability
IBM
The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
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Reliability and Availability
IBM
From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
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Performance
IBM
Never had slow response even on our very busy network
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Support Rating
IBM
I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
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In-Person Training
IBM
The trainers on the job are very smart with solutions and very able in teaching
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Online Training
IBM
The Platform is very handy and suggests further steps according my previous interests
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Implementation Rating
IBM
It surprised us with unpredictable case of use and brand new points of view
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Alternatives Considered
IBM
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.
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Scalability
IBM
It helped us in getting from 0 to DSX without getting lost
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Return on Investment
IBM
  • Could instantly show data driven insights to drive 20% incremental revenue over existing results
  • Still don't have a real use case for unstructured data like twitter feed
  • Some of the insights around user actions have driven new projects to automate mundane tasks
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ScreenShots