IBM Watson Studio on Cloud Pak for Data

Score10 out of 10

219 Reviews and Ratings

What is IBM Watson Studio on Cloud Pak for Data?

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

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

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

Kapil Bansal View profile

Web Developer in Engineering at FreshlyBuilt (11-50 employees employees)

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

Li Rong

Software Engineer in Information Technology at nate (11-50 employees employees)

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

Abdulrahman Bello

Team Lead, Financials in Finance and Accounting at First Bank Limited (10,001+ employees employees)

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

John Robert Uy View profile

President in Professional Services at Agile Inference Business Support Services (1-10 employees employees)

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

NARESH SAMPARA View profile

Research Associate in Marketing at Personal (1-10 employees employees)

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

Amazon SageMaker

Azure Machine Learning

IBM Watson Studio on Cloud Pak for Data

What is IBM Watson Studio on Cloud Pak for Data?

Categories & Use Cases

Key Features

Top Performing Features

Automatic Data Format Detection

Visualization

Interactive Data Analysis

Areas for Improvement

Self-Service Model Delivery

Security, Governance, and Cost Controls

MDM Integration

Reviews

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Most Important Features

Return on Investment

Alternatives Considered

Other Software Used

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Return on Investment

Other Software Used

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Return on Investment

Other Software Used

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Alternatives Considered

Other Software Used

Pros

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Return on Investment

Alternatives Considered

Other Software Used

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