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Dataiku vs IBM Watson Studio comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
9th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.0
Reviews Sentiment
7.2
Number of Reviews
8
Ranking in other categories
No ranking in other categories
IBM Watson Studio
Ranking in Data Science Platforms
12th
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
13
Ranking in other categories
AI Development Platforms (9th)
 

Mindshare comparison

As of December 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.7%, up from 2.7% compared to the previous year. The mindshare of Dataiku is 11.8%, up from 7.6% compared to the previous year. The mindshare of IBM Watson Studio is 2.1%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Md Masudul Hassan - PeerSpot reviewer
Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts
I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.
Sabrine Bendimerad - PeerSpot reviewer
Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.
Abilio Duarte - PeerSpot reviewer
A highly robust and well-documented platform that simplifies the complex world of AI
The main challenge lies in visibility and ease of use. Providing training sessions can be immensely helpful in helping users navigate and understand the tool's potential. This approach would empower users to explore and make the most of the tools and technologies at their disposal. Another area where IBM could enhance its offering is by providing more visibility to end users regarding the vast potential that Watson offers.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The most valuable feature is its robust statistical analysis capabilities."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"The most valuable feature is the set of visual data preparation tools."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"The solution is quite stable."
"Data Science Studio's data science model is very useful."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"IBM Watson Studio consistently automates across channels."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"It is a stable, reliable product."
"It has a lot of data connectors, which is extremely helpful."
"The scalability of IBM Watson Studio is great."
"The system's ability to take a look at data, segment it and then use that data very differently."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
 

Cons

"IBM SPSS Statistics does not keep you close to your data like KNIME."
"Needs more statistical modelling functions."
"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"The reports could be better."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"I think it would help if Data Science Studio added some more features and improved the data model."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"The ability to have charts right from the explorer would be an improvement."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"The decision making in their decision making feature is less good than other options."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"The solution's interface is very slow at times."
"The initial setup was complex."
"I want IBM's technical support team to provide more specific answers to queries."
"We would like to see it more web-based with more functionality."
 

Pricing and Cost Advice

"The price of IBM SPSS Statistics could improve."
"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"More affordable training for new staff members."
"It's quite expensive, but they do a special deal for universities."
"I rate the tool's pricing a five out of ten."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"The price of this solution is a little bit high, which was a problem for my company."
"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
"Pricing is pretty steep. Dataiku is also not that cheap."
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"IBM Watson Studio is a reasonably priced product"
"Watson Studio's pricing is reasonable for what you get."
"IBM Watson Studio is an expensive solution."
"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
9%
University
8%
Manufacturing Company
8%
Financial Services Firm
18%
Educational Organization
16%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
15%
Computer Software Company
12%
Manufacturing Company
9%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...
What needs improvement with IBM SPSS Statistics?
IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...
What needs improvement with Dataiku Data Science Studio?
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integratin...
What is your primary use case for Dataiku Data Science Studio?
We use the solution for data science and machine learning.
What needs improvement with IBM Watson Studio?
From an improvement perspective, I would say that if the deployment environment and IBM Watson Studio's environment a...
 

Also Known As

SPSS Statistics
Dataiku DSS
Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
 

Learn More

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Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
GroupM, Accenture, Fifth Third Bank
Find out what your peers are saying about Dataiku vs. IBM Watson Studio and other solutions. Updated: December 2024.
824,067 professionals have used our research since 2012.