IBM Watson Studio

IBM Watson Studio Reviews

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Score 7 out of 10
Vetted Review
Verified User
Review Source
The IBM Watson Studio is mainly used for one single department, the data science team. It mainly addresses the devops overhead of heavy jupyter notebooks and provides an integrated interface for people who are not familiar with infra and storage. It also provides a point of integration with other IBM services.
  • Sharing with team
  • GitHub integration
  • Free pricing plan if you want to try things out
  • Loading times can be slow
  • Tabs can be hard to navigate
  • not enough out of box examples
IBM Watson studio on Cloud Pak for Data is well suited for medium sized teams. It allows for collaboration between technical and non-technical users. It is less suited for companies who already has large built production ML pipelines, as the cost of migration could be high and the initial overhead of learning the tools still remains
Score 8 out of 10
Vetted Review
Verified User
Review Source
IBM Watson Studio on Cloud Pak for Data helps me bring in multiple data streams in Batch and streaming mode and helps me to run ETL processes and then run ML algorithms on top of the processed data. The beauty is I don't need to think about managing resources like CPU, storage, and processing elements and focus all my efforts on the data analytics.
  • Data ingestion
  • ETL processes
  • Integration with Python notebooks for ML algorithms
  • Support to run SQL queries on Cloud
  • Support for streaming data
  • Streaming data support
  • Connecting with existing Hadoop systems
  • Data visualization on top of the data
Well suited for
  • Data Storage
  • Data Warehousing
  • Data Ingestion
  • Data Analysis using Python

Less Suited for things like
  • Streaming Data
  • ETL tools area
  • AutoML algorithms out of the box
  • NoSQL Database support
Score 7 out of 10
Vetted Review
Verified User
Review Source
Currently, I am a student and I do not have any idea how many students studying and practicing along with me are using IBM Watson Studio on Cloud Pak for Data. Mostly, this platform might be used by the students under the computer science and information technology department. I use it mostly for my projects by learning to implement several concepts, helping me build and strengthen them.
  • Data security
  • Choice of the amount of computation power
  • Providing an option for sharing the files while hiding the sensitive content present in them
  • Checking if it is under use or not because for free users who cannot afford to pay, it is hard to manage the amount of computation periods provided
  • When there is nothing to execute, the run time should be paused to prevent wasting resources
  • Please try to provide the lite pack with a few more resources to help those who cannot afford to pay
It provides a lot of professional services which are not provided by other platforms
Score 9 out of 10
Vetted Review
Verified User
Review Source
IBM Watson Studio [formerly IBM Data Science Experience] helps my business unit to make some business decisions concerning management of cash and keeping stocks of debit cards. Generally it help us predict the amount of cash and debit card we would be needing to meet up the demands of the customer at the time.
My organization as a whole use it to predict the profitability of Automated Teller Machines (ATM) and to find insights while there are higher traffic on some machines.
  • Helps to predict profitability of terminals at any of our locations
  • Helps to predict peak and off-peak periods, hence, it aids preparation
  • Help us to plan and improve on cash management efficiency by relying of past data
  • IBM Watson studio needs to improve on its mobile experience
  • A help chatbot would go a long way to guide users
This depends on your application. I believe IBM Watson Studio [(formerly IBM Data Science Experience)] is agile enough to carry out most of my basic business intelligence tasks
John Robert Uy | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Used to test prototype applications for clients. Mostly used for creating predictive data models, descriptive models, and basic ETL. There are plans to test new speech-to-text and image-to-text applications for new clients in 2021. Cloud storage is a secondary use since it is the only platform that supports older or legacy databases
  • Auto AI makes creating predictive models so much easier and faster. It creates several models and ranks them according to precision (or accuracy) allowing us to rapidly select the most optimized model. While the models are not perfect at the first run, it gives us an idea on which models to focus on cutting the turnaround times from 3 days to less than 4 hours.
  • The cloud structure allows us to reuse datasets that are in different projects. This cuts down the need to create new pipelines or ETL steps.
  • Auto AI allows us to select the best models to use when creating predictive models. The app ranks and lists down the models according to accuracy (or precision0. This alone is worth the subscription as it cut down our turnaround times from 3 days to 1 day.
It is well suited for mechanistic models such as time series and descriptive analysis. There is almost no code necessary when creating these models, as it takes the guesswork out of setting up the parameters. There are also models that we've never before even tried because of its complexities but AutoAI shows that these models are sometimes best for the given problem.
Score 10 out of 10
Vetted Review
Verified User
Review Source
I have been working on IBM Watson Assistant and Watson Studio for a while now. I have used the Visual Recognition service with Watson and it works superbly with the thresholds in image recognition and cognitive study. I am using it in the department to teach cloud services and their provisioning to students. It addresses the implementation need for visual recognition algorithms for the purpose of the development of technical projects at the institute level.
  • Provisioning of tools and services across domains like AI , machine learning, IOT, etc.
  • Integration with web, Facebook, etc.
  • Facilitation of easy deployments on web services.
  • CLI is something I find little a difficult.
  • Refined up-gradation of video tutorials with regards to tools.
  • Increasing of allowed instances for LITE users.
Well suited for the study and provisioning of services. However, there is the scope of the implementation of more services with tutorials. Guide books to use IBM Watson with ease should be available.
NARESH SAMPARA | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
I am using IBM Watson studio for my personal interest. Since it is not involved a lot of programming, I am creating my own website with a chatbot whereas the chatbot will be answering about my research and carrier. I am using the IBM Watson Studio for analyzing the visual data.
  • No programming skills.
  • Well structured.
  • Proper instructions.
  • Takes time to integrate Watson.
  • High switching costs.
  • IBM Watson studio desktop.
The IBM Watson Studio is suited for everyone in the organization including a data scientist (who can do the in-depth coding), to a business analyst. Especially when the organizations have to analyze the unstructured data. It has the flexibility in the use of different data science development environments including R, Python and SPSS.
Shivam Sharma | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
We use IBM Watson Studio [(formerly IBM Data Science Experience)] across [a] wide range of our projects, as our organization deals in projects related to Machine Learning and Artificial Intelligence. So almost [the] entire organization depends on IBM Watson Studio and our focus is to always give error free professional services which mostly happened due to IBM's great plans and whole integrated services. It not only ameliorated our client's satisfaction but we also saw growth in our organization.
  • IBM Watson Studio [(formerly IBM Data Science Experience)] give[s] integrated services like data refinery flow, [which] save developers lots of time in cleaning and enhancing the data.
  • IBM Watson Studio has [given] the services for everything a developer [needs], which made this tool a necessity.
  • The plans provided for IBM Watson Studio by IBM are affordable as well every spark is also available and they are always ready to assist in any case.
  • [IBM] Watson [Studio] lack the speed, even at highest network speed. It will be a great experience if things open just after 1 second of clicking.
  • A notebook should close automatically after inactivation for 30 minutes. This would be a great help to me.
  • IBM should provide free tutorials and courses for a wider reach.
IBM Watson [Studio] [(formerly IBM Data Science Experience)] is a utilitarian for projects related to Machine Learning and Artificial Intelligence. Features like MDM Configuration help developers a lot. Even Auto AI Experiment is a great help in making models. Watson provide overall support for ML and AI. With the integration of payspark things become easy and fast.
Score 9 out of 10
Vetted Review
Verified User
Review Source
Currently I'm using IBM Watson as part of my Professional development via Coursera. IBM Watson to my knowledge isn't being used by my colleagues. I plan on using it to gather data and analytics to better support my customers. As an example I'm a Logistic Assistance Representative with a specialization in Tactical Radio communications thus if I can analysis the Army equipment readiness data and parts requisitioning backlogs I can better pin-point the average turn around time to assist my supported units and the respective parts managers to increase the parts availability and thus improving their readiness.
  • Helpful get started tutorial videos in Watson Studios.
  • Lots of notebooks to choose from.
  • Github push is a great way to share and collaborate with others.
  • I'd like to have more CHU's on the lite version.
  • When using Python environment it would be great when I make an error coding that corrective suggestions would be available.
  • Being very new it's a learning curve maybe a I'm new to coding tutorial class would help.
The sheer amount of services from DB to many others is more than one would expect especially being a lite user.
The assumption that every user is well versed in coding or just maneuvering around in Watson studio is definitely no true. Thus having said that a process of instruction or maybe a better tutorial might be appropriate.
Venugopal Dontaraboyana | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Storing data in the form of Worksheets and CSV files so that multiple users can use the data partially irrespective of location.
Running and deploying ML and AI Models. It helps - no need to have local hardware. We are able to achieve all the tasks over the cloud.
Used in different parts of the organization.
  • Deployment of ML Models.
  • Use of sharable data.
  • Multiple users can be added to a project.
  • UI difficult.
  • Use of Microsoft tools like Visio for flow.
  • In built Excel editor.
I am not sure whether can use Watson for Robotic process automation. I like the ease of usage of Watson for ML Models and Image processing. I love the way the Project is associated with Assets. I like the different data connectors.
Score 6 out of 10
Vetted Review
Verified User
Review Source
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 neat reports.
  • Kind of slow to launch
  • Not industry standard
  • Too many tabs to navigate through
If you are a small company with insufficient funding, it would be better to go with open source resources because they are free and do the same job. If you are a bigger company with enough resources, then IBM Watson Studio could be better in terms of security and accessibility.
Score 8 out of 10
Vetted Review
Verified User
Review Source
This system is currently being used with a few students on a data science degree within the School of Computing at our University. We are using IBM Watson as a means to overcome the hardware limitations we have within the our work setting. IBM Watson provides student with access to high powered machines allowing them to run complex machine learning algorithms without having to worry about hardware negatively effecting the performance of said algorithms. It is also a relatively simple system to use, making it a useful teaching tool which requires minimal support for academics. Students have provided positive feedback regarding the use of this service and we plan to expand our use of Watson Studio throughout our other degree options.
  • Clear distinction between services provided.
  • Jack of all trades without being a master of none.
  • Complex processing without an major latency.
  • Some aspects of the UI can be overwhelming for a novice user.
  • Integration with some non-Watson Studio services is limited.
IBM Watson Studio is very much suitable for data scientists when running a variety of analytical models using various languages such as R, Python and Scala. If you are planning to use data science driven languages in a cloud setting then IBM Watson Studio is a good option as it combines lots of relevant tools such as Notebooks, RStudio and Spark in a single environment. If you are looking to work in these environments as a group then Watson Studio also works well with the distribution and sharing of workspaces. This service however, isn't always the best solution as it can become costly if you are consistently running a large amount of intensive projects.
Score 10 out of 10
Vetted Review
Verified User
Review Source
[IBM Watson Studio (formerly IBM Data Science Experience)] is being used by a department [to] address user experience problems and [for] training some employees.
[IBM] Watson Studio provides access to data sets on-premises [that] we need.
The platform also has a large community and embedded resources such as articles on the latest developments and it is very important to us to develop solutions.
  • Collaboration
  • Machine learning
  • Analytics models
  • Learn how to use some models
  • Better help functions
  • Better integrations tools
It is possible [for] you quickly develop predictive models using business expertise and deploy them into business operations and to improve decision making, because [IBM Watson Studio (formerly IBM Data Science Experience)] offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics.
Watson VR comes with built-in models that you can use to analyze images for scenes, objects, and many other categories.
February 04, 2021

Review of IBM services

Score 8 out of 10
Vetted Review
Verified User
Review Source
I am into mentoring services, so I teach and assist learners on this technology.
  • Data Visualization - IBM Cognos.
  • Jupyter notebooks- Python Coding.
  • Speech to text recognition.
  • AI Bot can be better for IBM Cognos.
Watson is good when you do not have applications and software locally variable on your laptop or PC.
Score 8 out of 10
Vetted Review
Verified User
Review Source
We primarily use IBM Watson Studio (formerly IBM Data Science Experience) as training for developing analytical skills in Coursera courses.
  • The platform offers the ability to integrate with other platforms.
  • The interface is intuitive and easy to use.
  • The interface allows you to use different tools as needed like Jupyter notebooks and DB2.
  • It can be difficult to navigate at times.
  • The platform does not offer as much educational material as I would like.
IBM Watson Studio (formerly IBM Data Science Experience) is very useful for using different analysis techniques to import and interpret data sets. Converting and cleaning data is easy using IBM Watson Studio (formerly IBM Data Science Experience), so it is very helpful in scenarios where you know what you're trying to achieve. From an educational standpoint, it would be nice if the platform offered more instance-related material, but the platform is very useful for experienced analysis.
December 01, 2020

Beginner Guide Review

Score 7 out of 10
Vetted Review
Verified User
Review Source
IBM Watson studio is being used to host Juypter Notebooks. These notebooks contains analyses for various projects. The primary project being a ML algorithm that can detect fraud in PPP loans. This is specifically being used in the Engineering department at SJSU. It addresses the problem of users having the capable hardware to run the required software programs, since everything is now cloud based.
  • Usability - The Cloud Object Storage is fairly easy to implement with a Juypter Notebook
  • Design - After some initial learning curve, it becomes easy to navigate through the site.
  • Features - IBM is adding more and more features to their existing architecture.
  • Layout - There is a learning curve learning how to navigate the site, it's not as straightforward at it may seem.
  • Documentation - There is not that much good documentation available about how to setup various Watson Studio projects (configurations, etc.). Third-party resources provide a set of documentation and guides.
  • Bugs - There are some small bugs when using Watson Studio. One issue is when inviting collaborators to a project, depending on which computer you are using and what OS you have as well as your screen size, the invite button is "hidden". The invite button can only be noticed when zooming out far enough.
Watson Studio is suited for quick data validation checks. It's fairly simple to upload data resources and to get something up and running.
(Less Appropriate )I have not seen or had experience with Watson Studio services that can handle a large amount of data.
November 25, 2020

Review on IBM Watson

Score 9 out of 10
Vetted Review
Verified User
Review Source
I have been using IBM Watson [Studio (formerly IBM Data Science Experience)] for the purpose of Data science course which was offered by IBM on coursera. As part of that I had come across IBM Watson . It helped a lot for learners who want to do things practically . But I felt that the interface can be made much better so that people can use it in a more flexible way . Also some times there are issues when using jupyter notebooks with python . I felt that can be improved for better user experience
  • More variety of applications
  • More Flexible
  • Better compatibility
  • User Experience
  • Functionality issues with some applications
  • Speed
It is well suited for building applications using AI,ML etc..
November 04, 2019

Watson Studio Review

Score 6 out of 10
Vetted Review
Verified User
Review Source
It is used in the form of value chain at a macro level to drive optimization value and manage unplanned upsets. It is used by my department.
  • It is very user friendly.
  • Secure and can have federation security.
  • Very quick and high-resolution visual graphics.
  • Advanced modeling techniques.
  • It should have the capability to utilize thermodynamic models and extract key values.
Watson Studio is great for visualization and model computing, however, it doesn’t have error handling capability inbuilt.
Christopher Penn | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Reseller
Review Source
Watson Studio is the first third of IBM's new Watson machine learning data pipeline. It's a powerful, reasonably intuitive, low-code environment for building machine learning models and integrating IBM's machine learning APIs (speech recognition, image recognition, etc.) into your ML pipeline. If you already consume Watson APIs, Watson Studio will help streamline current and future deployments.
  • 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.
  • Watson Studio's UI is not always intuitive, especially when it comes to requirements and specific settings.
  • Documentation is not strong; tutorials and walkthroughs are noticeably light.
  • Tight integration with IBM APIs also means less well-made integrations to third party data sources and APIs—MySQL support notably absent.
Watson Studio is optimal for experienced data scientists and machine learning professionals to develop and deploy models quickly while enforcing best practices that set up projects for deployment and management down the road. It's not appropriate for people without a data science or machine learning background for production use; the ease of the visual modelers does not mean it makes machine learning easy or intuitive.
Score 8 out of 10
Vetted Review
Verified User
Review Source
It is currently used by the data analytics department. It is used to address cost analysis and actuarial analysis.-

  • It is relatively easy to use
  • It works seamlessly with multiple languages.
  • Its administration is surprisingly easy
  • And it's easy to install / upgrade / maintain
  • Need better training materials for data scientists. Especially the ones who are not formally educated as data scientists.
  • The videos in the tutorials are all on Youtube which are usually blocked on most work campuses.
  • And the IBM Think campus training could have been better as well
Well suited for my organization's claim diagnosis level analysis across the years. Less suited for lower level data analysis which does not add much value.
February 14, 2019

Watson Studio review

Van West | TrustRadius Reviewer
Score 5 out of 10
Vetted Review
Verified User
Review Source
We currently use Watson Studio for NLP/NLU purposes in our client environments. It addressed problems in physical space interactions between front line associates and customers. We also leverage tonality and sentiment models in addition to transcription to effectively process large amounts of voice interactions in the physical world. Watson Studio has proven useful in addressing these problems in these environments, but we are limited in our capacity to roll it out further due to edge compute limitations with the platform.
  • Speech to text
  • Keyword analysis
  • Tonality
  • Sentiment
  • Architectural support team to get up and running
Well suited for cloud-based environments, and less suited for edge-based processing.
Pedro Henrique de Almeida | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
My organization is currently going thru an expansion process, from being solely a consulting company to creating and developing products itself and for this expansion, a new team was assembled, the Research & Development team and I'm part of this team. As part of our research to create products that are really relevant to the market we are aiming at, and since we're already are a gold level IBM partner organization, it made sense for us to acquire knowledge with IBM DSx in order to maximize our efficiency and develop better products.
  • Feature rich. IBM DSx provides a plethora of tools to leverage the use of data science in your organization and suit your specific needs.
  • IBM DSx supports a huge variety of sources of data. From your traditional SQL database to every major data warehouse, IBM DSx does a great job at connecting to or pulling from your data source.
  • Its greatest strength is the fact that is a cloud-based service. There's no need to waste time on configuring and maintaining an environment to start analyzing data, which may not be an easy task.
  • Pricing. The price for this product is quite steep and, since it features so many solutions, it makes sense to cost as much as it does. But the creation of personal plans with fewer features might prove interesting to bring the product to a broader audience, like enthusiasts that are starting to get in touch with data science.
  • Some issues regarding notebooks and the use of data refinery are quite annoying to the experience because, depending on the use that you make of it, they might appear quite regularly.
  • Lack of a changelog. Like many IBM products and platforms, DSx is in constant development and is updated regularly. This is a great point, except for the fact that sometimes it lacks a changelog to properly inform what has been changed, requiring the user to investigate on its own.
I believe IBM DSx is a great fit for organizations that are engaged deeply in data science and are looking for a solution that is able to both leverage the efficiency of their actual work and train additional data scientists since it also features many tutorials to increase the knowledge for its users. I don't think it is the appropriate product for a full group of starters on data science and/or organizations that plan on using data science on a small scale because of its price and the high number of features.
February 23, 2018

DSx - as a beginner

Bhaumik Pandya | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
DSX is being used by a sub-department of our company.

We are using it for the projects of service-automation and recommendation systems to analyse data and build models.
  • Can connect to IBM DB2 - Data Warehouse and has integrated IDEs for Data-Scientists including RStudio, Jupyter Notebooks and SQL-Dashboard.
  • A version of DSX, DSX-Desktop, makes it quite easy to play with your data and is powered by Spark.
  • Access to ML Libs such as, Python Sci-kit Learn makes it simple to not only apply the model over data and optimize it, but also to deploy to Watson Machine Learning service for production purposes.
  • I would love to deploy the R-models for production.
Consider an ecosystem or application backend, that has different databases with different types of data (structured, documents etc.). Normally, a simple analytics for such data sources requires to fetch and query data from multiple sources and build visualizations for them. With DSX RStudio or Jupyter and DashDB (or DB2), all data can be accessed at one point. This makes it, as per the definition, a more practical approach than Data Lakes, where you can also build and deploy ML models. Almost everything that a data scientist needs.
José Adolfo Ramírez Magdaleno | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Reseller
Review Source
To move data from to an API public government service to an operational dashboard that shows real time results.

All the connections and data preparation jobs are achieved with DSX through a Python Jupyter notebook which runs automatically every 10 minutes and solves the whole process without human intervention.
  • Scalable in the sense that its performance can grow without complications, but also in its capabilities, since various services can be included at a very competitive price: optimization, machine learning, storage, etc.
  • Collaborative solution, since you do not work in isolation, you can generate data science projects with your peers, manage permissions, manage versions of the script.
  • Enabled in Spark, the top framework for data science and machine learning.
  • It would be very valuable to include a calculator that will help you identify how many cores or require hiring Spark resources and storage resources, to make a precise sizing from the start.
Ideal for companies that have teams (3 to more professionals) of data scientists who need to guarantee results at all times and without breaks, in the sense that DSX is in a cloud that does not require installations or dependencies of the IT department.
Colin Sumter | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Reseller
Review Source
We bid on specialized projects in the public sector using a confidential configuration that solves a variety of problems. Marketing Research, Unified Data Governance, Modern Call Center, and other Cloud Initiatives. It's an integral part of our training for Engagement, Conversion, and Fulfillment of our BPM. This plans optimization segments by use case rather than dedicating resources to a single Industry like everyone else.
  • Rapid Data Science; IBM has done a great job of automating the data prep.
  • Asset Classification; there's a way to use numerical language prediction vs. natural language processing by using highly specialized data classification catalog within the DSx.
  • Visual Data Modeling; this results in faster time to value because you won't spend all day tuning a data model. Allowing you to compare different data models in the same weather forecast.
  • There should be a heavier emphasis on the IBM DSx Community. Showing people where to begin.
  • Perhaps more information related to how data science improves an organizations competency inventory to reduce the intimidation factors.
It's suited for big data analytics. Some industries would Pharma data, Oil & Gas, Financial Markets, HR, Sales, Price Variance, and etc. Most professionals do repetitive data prep on static spreadsheets. DSx reduces the data duplication and allows everyone to see the same picture. And makes segregation of duties simple: the modeler can be isolated from the data tuning operation and both can be isolated from the decision maker.

IBM Watson Studio Scorecard Summary

Feature Scorecard Summary

Platform Connectivity (4)
75%
7.5
Connect to Multiple Data Sources (24)
77%
7.7
Extend Existing Data Sources (23)
79%
7.9
Automatic Data Format Detection (23)
75%
7.5
MDM Integration (17)
70%
7.0
Data Exploration (2)
79%
7.9
Visualization (24)
79%
7.9
Interactive Data Analysis (24)
80%
8.0
Data Preparation (4)
77%
7.7
Interactive Data Cleaning and Enrichment (24)
74%
7.4
Data Transformations (23)
78%
7.8
Data Encryption (21)
76%
7.6
Built-in Processors (23)
80%
8.0
Platform Data Modeling (4)
77%
7.7
Multiple Model Development Languages and Tools (23)
80%
8.0
Automated Machine Learning (24)
77%
7.7
Single platform for multiple model development (24)
77%
7.7
Self-Service Model Delivery (21)
74%
7.4
Model Deployment (2)
72%
7.2
Flexible Model Publishing Options (24)
75%
7.5
Security, Governance, and Cost Controls (24)
68%
6.8

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.

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Frequently Asked Questions

What is IBM Watson Studio's best feature?

Reviewers rate Interactive Data Analysis and Built-in Processors and Multiple Model Development Languages and Tools highest, with a score of 8.

Who uses IBM Watson Studio?

The most common users of IBM Watson Studio are from Enterprises and the Information Technology & Services industry.