Good for large teams with large data reiterating on their data projects in various steps.
Collaboration is the key aspect in whatever projects we do at our organization. We have people from web development, data science, and ML …
Overview
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…
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Popular Features
- Interactive Data Analysis (22)10.0100%
- Visualization (22)10.0100%
- Connect to Multiple Data Sources (22)8.080%
- Extend Existing Data Sources (22)8.080%
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…
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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 lifecycle management and accelerates time to value with an open, flexible multicloud architecture.
IBM Watson Studio Competitors
IBM Watson Studio Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Frequently Asked Questions
Amazon SageMaker and Azure Machine Learning are common alternatives for IBM Watson Studio.
Reviewers rate Automatic Data Format Detection and Visualization and Interactive Data Analysis highest, with a score of 10.
The most common users of IBM Watson Studio are from Small Businesses (1-50 employees).
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(221)Attribute Ratings
Reviews
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December 01, 2020
Beginner Guide Review
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.
62.5%
6.3
60%
6.0
57.5%
5.8
75%
7.5
60%
6.0
- Positive - Allowed a quick and thorough analyzes to be completed on PPP loan data.
- Positive - For this price tier, it was well worth the price as the ROI was greater than the cost.
- Negative - The cost for the next tier is a bit pricey, it should only be selected by those departments and projects that absolutely require those services.
November 24, 2020
My first experience on Watson Studios
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.
40%
4.0
90%
9.0
40%
4.0
80%
8.0
85%
8.5
- Well I'm just starting thus I can't provide any input yet.
- I would imagine it could provide a positive impact if I data mined and properly presented that visual tool to my stakeholders.
- Negative impact is yet to be determined.
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."
February 25, 2019
IBM Watson Studio: Ideal for Rapid Data Science and ML POCs and Deployments with Watson
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.
47.5%
4.8
70%
7.0
85%
8.5
87.5%
8.8
90%
9.0
- As a reseller, selling Watson Studio as a machine learning platform package is relatively straightforward.
- Buyers and partners know, appreciate, and trust the IBM brand.
- Watson Studio models obey best practices, which means they are less subject to human error.
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
Watson Studio is used within Manifest Life Inc to help gather, process, and visualize various amounts of data. We use Watson Studio throughout our data management lifecycle and view it as the best all-in-one data management offering within the market. Watson Studio has helped our organization manage our data operations more fluidly through the offerings ease of use and minimal learning barrier. This product from IBM works like a charm and is flexible in small and/or large business environments. Data sets of all size can be easily cleaned, processed and leveraged in order to help meet our business objectives and create new opportunities.
- Cloud-based file sharing helped our organization stay up to date when managing assets, new or old.
- Watson studio does a fantastic job visualizing outcome data which enabled our organization to easily create a narrative based on what we were able to see.
- Particularly within our organization, Watson Studio strength was noticed in its ability to processes enormous amounts of data in such a short amount of time.
- Watson Studio could used improvement in its user-based community. I'd like to see more local and remote events showcasing its potential.
- Watson Studio could improve by providing its users, use-cases that leverage data in unusual ways.
- We think Watson studio could also improve by decreasing its price in order to capture new talent in the data industry.
- Watson Studio has allowed our organization leverage open data to create new streams of revenue that previously could not be tapped into.
- Watson Studio has allowed us to conduct business without the need of additional third party vendors.
- Watson Studio has allowed us to see a ROI where previously there was none.
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.
- Data cleansing
- Data visualizing
- Data sharing
- Understanding ML feature
- Using algorithms
- Features including spark
March 15, 2018
Market Simulator with DSX
DSX is been used by my department only as a pilot project to prove the tool capabilities, although we are currently doing different projects: one to simulate the Brazilian retail market to find the best places to open stores, measure performance of existing stores, another to read verbatim text from our clients, and a third to correlate sales behavior with population cluster.
- Flexibility: all the other solutions we procure were modular with black boxes.
- Data center is in Europe, since in my company we can't have data in US
- From all the solutions we procure IBM was the only team that actually embarked on the project and didn't only tried to sell a tool/service.
- The download of files is terrible
- Managing the files is terrible
- We have been more assertive in the places we can open stores, which has a direct impact on the ROI.
- Measuring the performance of stores and takeing actions on it
- Targeting behavior of clients
- SAP Leonardo, Oracle R, google TensorFlow and Axiom Sales Force Development
SAP Leonardo : Still too young and very hard to use. Besides it doesn’t had maximization tools
Oracle R : They were the only ones that were actually able to replicate the DSX capabilities, but they lacked the team to do so.
Google TensorFlow : impossible for programming and very expensive to hire the consulting
Sales force : Didn’t have the capabilities of creation , they are only black boxes of pre-fabricated solutions
Spark beyond : Kind of black boxes and didn’t have any kind of support in Brazil.