Darwin vs IBM Watson Studio comparison

SparkCognition and IBM are both solutions in the Data Science Platforms category. SparkCognition is ranked #27, while IBM is ranked #12 with an average rating of 8.2. SparkCognition holds a 0.3% mindshare in Data Science Platforms, compared to IBM’s 2.1% mindshare. Additionally, 100% of SparkCognition users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

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Executive Summary

We performed a comparison between Darwin and IBM Watson Studio based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Darwin vs. IBM Watson Studio Report (Updated: October 2024).

Buyer's Guide

Darwin vs. IBM Watson Studio

October 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Darwin is 0.3%, up from 0.3% 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

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Sep 21, 2023

Enhancing survey analysis that provides valued insightfulness

I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…

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AaronCooke

Founder at Helio Summit

Jun 11, 2021

Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.

There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.

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Abilio Duarte

Senior Solutions Architect at Self-employed

Oct 5, 2023

A highly robust and well-documented platform that simplifies the complex world of AI

It is used to enhance user experience in an e-commerce setting. By leveraging data on user clicks, browsing behavior, and past interactions with the platform, we can create models that enable personalized product recommendations. These models can identify products that align with the customer's…

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Quotes from Members

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

Pros

"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."

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

"The most valuable features are the small learning curve and its ability to hold a lot of data."

"One feature I found very valuable was the analysis of variance (ANOVA)."

"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."

"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."

More IBM SPSS Statistics pros

"The thing that I find most valuable is the ability to clean the data."

"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."

"In terms of streamlining a lot of the low-level data science work, it does a few things there."

"The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science."

"The most valuable feature is the model-generation. With a nice dataset, Darwin gives you a nice model. That's a really nice feature because, if we're doing that ourselves, it's trial and error; we change the parameters a little and try again. We save time by just giving the dataset to Darwin and letting Darwin generate a model. We find the models it generates are good; better than we can generate."

"I find it quite simple to use. Once you are trained on the model, you can use it anyway you want."

"I liked the data checking feature where it looks at your data and sees how viable it is for use. That's a really cool feature. Automatic assessment of the quality of datasets, to me, seems very valuable."

"Darwin has increased efficiency and productivity for our company. With our risk management team, there were models that took them more than three days to process each, only to see the outcome. Now, it takes minutes for Darwin to process the current model. So, we can have it in minutes. We don't have to wait three days for all the models to be tested, then make a decision."

"Watson Studio is very stable."

"The solution is very easy to use."

"It is a stable, reliable product."

"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."

"It is a very stable and reliable solution."

"It has a lot of data connectors, which is extremely helpful."

"The scalability of IBM Watson Studio is great."

"IBM Watson Studio consistently automates across channels."

More IBM Watson Studio pros

Cons

"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."

"IBM SPSS Statistics does not keep you close to your data like KNIME."

"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."

"The reports could be better."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

"This solution is not suitable for use with Big Data."

"There is a learning curve; it's not very steep, but there is one."

More IBM SPSS Statistics cons

"The Read Me's and the tutorials need to be greatly improved to get customers to understand how things work. It might be helpful to have some sample data sets for people to play around with, as well as some tutorial videos. It was very hard to find information on this in the time crunch that we had, to see how it worked and then make it work, while interfacing with folks at SparkCognition."

"The analyze function takes a lot of time."

"An area where Darwin might be a little weak is its automatic assessment of the quality of datasets. The first results it produces in this area are good, but in our experience, we have found that extra analysis is needed to produce an extra-clean set of data."

"There are issues around the ethics of artificial intelligence and machine learning. You need to have a lot of transparency regarding what is going on under the hood in order to trust it. Because so much is done under the hood of Darwin, it is hard to trust how it gets the answers it gets."

"Our main data repository is on AWS. The trouble we are having is that we have to download the data from our repository to bring it into Darwin. It would be great if there was an API to connect our repository to Darwin."

"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."

"The challenge is very big toward making models operational or to industrialize them. E.g., what we want to do is to make unique credit models for each customer. So, we are preparing the types of customers who we can try new credit models on Darwin. But, I see this still very challenging to be able to get the data sets so Darwin can work. At this point, we are working it to get the data sets ready for Darwin."

"Something they are working on, which is great, is to have an API that can access data directly from the source. Currently, we have to create a specific dataset for each model."

"So a better user interface could be very helpful"

"I want IBM's technical support team to provide more specific answers to queries."

"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."

"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."

"The initial setup was complex."

"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."

"We would like to see it more web-based with more functionality."

"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."

More IBM Watson Studio cons

Pricing and Cost Advice

"The price of this solution is a little bit high, which was a problem for my company."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"We think that IBM SPSS is expensive for this function."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"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."

"It's quite expensive, but they do a special deal for universities."

"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."

"I rate the tool's pricing a five out of ten."

More IBM SPSS Statistics pricing and cost advice

"The license cost is not cheap, especially not for markets like Mexico. But sometimes, you do have to make these leap of faith for some tools to see if they can get you the disruption that you are aiming for. The investment has paid off for us very well."

"As far as I understand, my company is not paying anything to use the product."

"In just six months, we calculated six million pesos that we have prevented in revenue from going away with another customer because of this solution. Thanks to Darwin, we didn't lose those six million pesos."

"I believe our cost is $1,000 per month."

"IBM Watson Studio is a reasonably priced product"

"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."

"Watson Studio's pricing is reasonable for what you get."

"IBM Watson Studio is an expensive solution."

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814,763 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

16%

University

10%

Computer Software Company

Manufacturing Company

Computer Software Company

24%

Government

12%

Real Estate/Law Firm

12%

Educational Organization

11%

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

University

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.

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What is your experience regarding pricing and costs for IBM SPSS Statistics?

While the pricing of the product may be higher, the accompanying service and features justify the investment. However...

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What needs improvement with IBM SPSS Statistics?

In some cases, the product takes time to load a large dataset. They could improve this particular area.

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What do you like most about IBM Watson Studio?

Stability-wise, it is a great tool.

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What is your experience regarding pricing and costs for IBM Watson Studio?

IBM Watson Studio is an expensive solution.

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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...

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Comparisons

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Compared 14% of the time

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

Weka vs IBM SPSS Statistics

Compared 11% of the time

More IBM SPSS Statistics Competitors

No data available

Databricks vs IBM Watson Studio

Compared 27% of the time

Azure OpenAI vs IBM Watson Studio

Compared 16% of the time

Google Vertex AI vs IBM Watson Studio

Compared 16% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 13% of the time

Dataiku vs IBM Watson Studio

Compared 2% of the time

More IBM Watson Studio Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

October 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Darwin

November 2024

Download Darwin product report

Buyer's Guide

IBM Watson Studio

October 2024

Download IBM Watson Studio product report

Also Known As

SPSS Statistics

No data available

Watson Studio, IBM Data Science Experience, Data Science Experience, DSx

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IBM

SparkCognition

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IBM

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

SparkCognition builds leading artificial intelligence solutions to advance the most important interests of society. We help customers analyze complex data, empower decision making, and transform human and industrial productivity with award-winning machine learning technology and expert teams focused on defense, IIoT, and finance.

IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

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

Hunt Oil, Hitachi High-Tech Solutions

GroupM, Accenture, Fifth Third Bank

Buyer's Guide

Darwin vs. IBM Watson Studio

October 2024

Free Report: Darwin vs. IBM Watson Studio

Find out what your peers are saying about Darwin vs. IBM Watson Studio and other solutions. Updated: October 2024.

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