IBM Watson Studio on Cloud Pak for Data vs. MonkeyLearn

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Watson Studio
Score 9.1 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
MonkeyLearn
Score 9.2 out of 10
N/A
MonkeyLearn is a Text Analysis platform that allows companies to create new value from text data.
$299
per month
Pricing
IBM Watson Studio on Cloud Pak for DataMonkeyLearn
Editions & Modules
No answers on this topic
API
$299
month
Studio
custom pricing
Offerings
Pricing Offerings
IBM Watson StudioMonkeyLearn
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM Watson Studio on Cloud Pak for DataMonkeyLearn
Top Pros
Top Cons
Features
IBM Watson Studio on Cloud Pak for DataMonkeyLearn
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
MonkeyLearn
-
Ratings
Connect to Multiple Data Sources8.022 Ratings00 Ratings
Extend Existing Data Sources8.022 Ratings00 Ratings
Automatic Data Format Detection10.021 Ratings00 Ratings
MDM Integration6.414 Ratings00 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
MonkeyLearn
-
Ratings
Visualization10.022 Ratings00 Ratings
Interactive Data Analysis10.022 Ratings00 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
MonkeyLearn
-
Ratings
Interactive Data Cleaning and Enrichment10.022 Ratings00 Ratings
Data Transformations10.021 Ratings00 Ratings
Data Encryption8.020 Ratings00 Ratings
Built-in Processors10.021 Ratings00 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
MonkeyLearn
-
Ratings
Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
Automated Machine Learning10.022 Ratings00 Ratings
Single platform for multiple model development10.022 Ratings00 Ratings
Self-Service Model Delivery8.020 Ratings00 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
MonkeyLearn
-
Ratings
Flexible Model Publishing Options9.022 Ratings00 Ratings
Security, Governance, and Cost Controls7.022 Ratings00 Ratings
Best Alternatives
IBM Watson Studio on Cloud Pak for DataMonkeyLearn
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM Watson Studio
IBM Watson Studio
Score 9.1 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.2 out of 10
PG Forsta HX Platform
PG Forsta HX Platform
Score 9.0 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
PG Forsta HX Platform
PG Forsta HX Platform
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Watson Studio on Cloud Pak for DataMonkeyLearn
Likelihood to Recommend
8.0
(65 ratings)
9.4
(7 ratings)
Likelihood to Renew
8.2
(1 ratings)
-
(0 ratings)
Usability
9.6
(2 ratings)
-
(0 ratings)
Availability
8.2
(1 ratings)
-
(0 ratings)
Performance
8.2
(1 ratings)
-
(0 ratings)
Support Rating
8.2
(1 ratings)
-
(0 ratings)
In-Person Training
8.2
(1 ratings)
-
(0 ratings)
Online Training
8.2
(1 ratings)
-
(0 ratings)
Implementation Rating
7.3
(1 ratings)
-
(0 ratings)
Product Scalability
8.2
(1 ratings)
-
(0 ratings)
Vendor post-sale
7.3
(1 ratings)
-
(0 ratings)
Vendor pre-sale
8.2
(1 ratings)
-
(0 ratings)
User Testimonials
IBM Watson Studio on Cloud Pak for DataMonkeyLearn
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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MonkeyLearn
I have used MonkeyLearn to analyze texts and extract information, that has been a tough task for me because I have to do it manually, but this software has made it easy for me, it is very easy to use and very intuitive, I can use it for extracting information from emails, chats, forums, websites, etc. I would definitely recommend using this platform to others.
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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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MonkeyLearn
  • I like how MonkeyLearn can track customer feedback for us, it helps us get more data about customer needs, it makes it easier for us to analyze customer feedback and act on it in the future.
  • Easily build and train a machine learning model to tag and classify your text.
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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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MonkeyLearn
  • Sometimes the segregation is generic based on the email content and needs more examples to learn.
  • Financial category is not easily segregated/tagged.
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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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MonkeyLearn
No answers on this topic
Usability
IBM
The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
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MonkeyLearn
No answers on this topic
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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MonkeyLearn
No answers on this topic
Performance
IBM
Never had slow response even on our very busy network
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MonkeyLearn
No answers on this topic
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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MonkeyLearn
No answers on this topic
In-Person Training
IBM
The trainers on the job are very smart with solutions and very able in teaching
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MonkeyLearn
No answers on this topic
Online Training
IBM
The Platform is very handy and suggests further steps according my previous interests
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MonkeyLearn
No answers on this topic
Implementation Rating
IBM
It surprised us with unpredictable case of use and brand new points of view
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MonkeyLearn
No answers on this topic
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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MonkeyLearn
Text analysis tools. Thanks to its more than 60 native integrations in the platforms, they make it possible to import your data sets. Furthermore, they also make it easy to export your data sets to other programs. Built-in extensions make their flexible platforms. Some of these integrations include word processing, detection, and web mining.
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Scalability
IBM
It helped us in getting from 0 to DSX without getting lost
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MonkeyLearn
No answers on this topic
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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MonkeyLearn
  • Extract custom data within texts.
  • Their labeling process is fast and efficient.
  • The Studio version of the tool is an excellent option for a complete analysis solution.
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ScreenShots