IBM Watson Studio on Cloud Pak for Data vs. SAS Data Management

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Watson Studio
Score 7.6 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
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.N/A
Pricing
IBM Watson Studio on Cloud Pak for DataSAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM Watson StudioSAS Data Management
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 DataSAS Data Management
Considered Both Products
IBM Watson Studio
Chose IBM Watson Studio on Cloud Pak for Data
I selected IBM Data Science Experience (DSx) because it promotes collaboration. That being said, it could be a bit challenging to prevent people who use it for the first time, because the interface could seem a bit complex for some - said by people I worked with. Therefore, it …
SAS Data Management

No answer on this topic

Top Pros
Top Cons
Features
IBM Watson Studio on Cloud Pak for DataSAS Data Management
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
SAS Data Management
-
Ratings
Connect to Multiple Data Sources8.022 Ratings00 Ratings
Extend Existing Data Sources8.022 Ratings00 Ratings
Automatic Data Format Detection9.921 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
9.9
22 Ratings
16% above category average
SAS Data Management
-
Ratings
Visualization9.922 Ratings00 Ratings
Interactive Data Analysis9.922 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
SAS Data Management
-
Ratings
Interactive Data Cleaning and Enrichment9.922 Ratings00 Ratings
Data Transformations9.921 Ratings00 Ratings
Data Encryption8.020 Ratings00 Ratings
Built-in Processors9.921 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
SAS Data Management
-
Ratings
Multiple Model Development Languages and Tools9.921 Ratings00 Ratings
Automated Machine Learning9.922 Ratings00 Ratings
Single platform for multiple model development9.922 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
SAS Data Management
-
Ratings
Flexible Model Publishing Options9.022 Ratings00 Ratings
Security, Governance, and Cost Controls7.022 Ratings00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
-
Ratings
SAS Data Management
8.3
10 Ratings
1% above category average
Connect to traditional data sources00 Ratings8.610 Ratings
Connecto to Big Data and NoSQL00 Ratings8.19 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
-
Ratings
SAS Data Management
6.7
8 Ratings
22% below category average
Simple transformations00 Ratings6.18 Ratings
Complex transformations00 Ratings7.48 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
-
Ratings
SAS Data Management
6.7
8 Ratings
20% below category average
Data model creation00 Ratings5.56 Ratings
Metadata management00 Ratings7.47 Ratings
Business rules and workflow00 Ratings6.67 Ratings
Collaboration00 Ratings7.07 Ratings
Testing and debugging00 Ratings6.17 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
-
Ratings
SAS Data Management
7.9
9 Ratings
4% below category average
Integration with data quality tools00 Ratings7.69 Ratings
Integration with MDM tools00 Ratings8.27 Ratings
Best Alternatives
IBM Watson Studio on Cloud Pak for DataSAS Data Management
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Skyvia
Skyvia
Score 9.6 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.3 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Watson Studio on Cloud Pak for DataSAS Data Management
Likelihood to Recommend
8.0
(65 ratings)
7.6
(11 ratings)
Likelihood to Renew
8.2
(1 ratings)
9.0
(2 ratings)
Usability
9.6
(2 ratings)
6.0
(2 ratings)
Availability
8.2
(1 ratings)
-
(0 ratings)
Performance
8.2
(1 ratings)
9.0
(1 ratings)
Support Rating
8.2
(1 ratings)
7.7
(6 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 DataSAS Data Management
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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SAS
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
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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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SAS
  • SAS/Access is great for manipulating large and complex databases.
  • SAS/Access makes it easy to format reports and graphics from your data.
  • Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
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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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SAS
  • Requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres.
  • Debugging errors from the logs is a complicated process.
  • E-mail alert system is very primitive and needs customization to make it more modern,
  • Cannot send SMS alerts for jobs.
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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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SAS
We are happy with the software and its functionality. As a SAS-shop, DataFlux is a logical choice for complex data integration.
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Usability
IBM
The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
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SAS
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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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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SAS
No answers on this topic
Performance
IBM
Never had slow response even on our very busy network
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SAS
It worked as expected.
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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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SAS
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
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In-Person Training
IBM
The trainers on the job are very smart with solutions and very able in teaching
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SAS
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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SAS
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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SAS
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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SAS
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
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Scalability
IBM
It helped us in getting from 0 to DSX without getting lost
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SAS
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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SAS
  • We have more users who can connect to the many different data sources.
  • Our users do have existing SAS programming knowledge and that can carry over.
  • Business functions are starting to rely on SAS Data Integration Studio work product shortly after introduction.
Read full review
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