#1 most frequent
United States of America
100.0%2 installations of 2
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.
Categories & Use Cases
Top Performing Features
Automatic Data Format Detection
Automatic detection of data formats and schemas
Category average: 9.2
Visualization
The product’s support and tooling for analysis and visualization of data.
Category average: 8.3
Interactive Data Analysis
Ability to analyze data interactively using Python or R Notebooks
Category average: 8.8
Areas for Improvement
Self-Service Model Delivery
Multiple model delivery modes to comply with existing workflows
Category average: 8.3
Security, Governance, and Cost Controls
Built-in controls to mitigate compliance and audit risk with user activity tracking
Category average: 8.6
MDM Integration
Integration with MDM and metadata dictionaries
Category average: 7.8
Who Buys & Uses IBM Watson Studio on Cloud Pak for Data
Why Use IBM Waston Studio?
Pros
- IBM Watson Services like speech to text, etc. are just some clicks away. You just need to specify some basic details like location etc and the resource will be ready for use.
- IBM DB2 engine is a fully managed relational database for all your needs.
- There are a lot of services available from which users can choose what suits his/her needs.
Cons
- In starting, I found navigating through different services a bit difficult and overwhelming.
- IBM dashboard should be redesigned to make it simple.
- Rest all looks good.
Most Important Features
- Able to run Jupyter notebooks and code there.
- Image recognition and text to speech service saves our lot of time.
- Cloud Storage and Databases ease the work of managing a remote database.
Return on Investment
- IBM Waston is a lot time saving.
- Machine learning services and resources have great accuracy.
- Documentation is really good.
Alternatives Considered
Google Cloud AI
Other Software Used
Google Cloud Pub/Sub
IBM Watson Studio on Cloud Pak for Data Review
Pros
- Sharing with team
- Github integration
- Free pricing plan if you want to try things out
Cons
- Loading times can be slow
- Tabs can be hard to navigate
- not enough out of box examples
Return on Investment
- Made running experiments more streamlined
- Reduced devops overhead
- Sometimes does mean integration with things that are not on IBM harder
Other Software Used
PyCharm, GitHub, Google Authenticator
My IBM Watson Studio experience
Pros
- 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
Cons
- IBM Watson studio needs to improve on its mobile experience
- A help chatbot would go a long way to guide users
Return on Investment
- We just recently adopted the use of IBM Watson Studio. It would take Q1 2021 figure to ascertain its impact on our bottom-line.
Other Software Used
Jupyter Notebook, RStudio, Anaconda
Auto AI is a must have for every Data Analyst
Pros
- 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.
Cons
- 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.
Return on Investment
- Positive: reduce our turnaround times were reduced from 3 days to 1 day. This allows us to create more models and service more clients.
Alternatives Considered
Google BigQuery and Google Cloud AI
Other Software Used
KNIME Analytics Platform, Weka.IO, Google Cloud Storage
Data scientist - as a beginner
Pros
- No programming skills.
- Well structured.
- Proper instructions.
Cons
- Takes time to integrate Watson.
- High switching costs.
- IBM Watson studio desktop.
Return on Investment
- Ease of deployment.
- The cost of ownership is high for a personal use.
- It's very convenient for quick hit applications.
Alternatives Considered
Microsoft Azure
Other Software Used
Python IDLE, MATLAB, IBM Watson Assistant
