Try our new research platform with insights from 80,000+ expert users

H2O.ai vs SAS Visual Analytics comparison

Sponsored
 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd), Data Science Platforms (10th)
H2O.ai
Average Rating
7.6
Number of Reviews
8
Ranking in other categories
Data Science Platforms (22nd), Model Monitoring (8th)
SAS Visual Analytics
Average Rating
8.2
Number of Reviews
39
Ranking in other categories
Data Visualization (9th)
 

Mindshare comparison

Data Science Platforms
Data Visualization
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Enhancing survey analysis that provides valued insightfulness
I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.
Kashif Yaseen - PeerSpot reviewer
Plug-and-play convenience enhances productivity but needs better multimodal support
We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI The solution was plug-and-play, meaning most of the components were handled by the solution itself rather than building them from scratch. This was useful for our banking…
Robert Heck - PeerSpot reviewer
A great solution for big organizations, complex business requirements, and highly sophisticated and specialized statistics
There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else. For instance the system does not come with a pre-defined accounting, budgeting or planning model for a particular industry. Some competitors come with such a model (e.g. for retail companies) which makes the implementation of course easier if the customer can comproise with this predefined model. SAS does not provide such models but does not demand customers to comply with a foreign business model.

Quotes from Members

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

Pros

"It has the ability to easily change any variable in our research."
"The most valuable features are the small learning curve and its ability to hold a lot of data."
"You can quickly build models because it does the work for you."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"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."
"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 ease of use in connecting to our cluster machines."
"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"The most valuable feature of H2O.ai is that it is plug-and-play."
"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."
"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"The technical support services are good."
"The tool's most valuable features are its ease of use and advanced data visualization capabilities."
"I use Visual Analytics for enterprise reporting."
"Great for handling complex data models."
"Data handling is one of the best features of SAS Visual Analytics."
"It's quite easy to learn and to progress with SAS from an end-user perspective."
"It provided the capability to visualize a bunch of data in an organized way."
 

Cons

"I think the visualization and charting should be changed and made easier and more effective."
"Better documentation on how to use macros."
"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"The design of the experience can be improved."
"Needs more statistical modelling functions."
"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."
"It could provide even more in the way of automation as there are many opportunities."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"H2O.ai can improve in areas like multimodal support and prompt engineering."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability."
"I would like to see more features related to deployment."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"The model management features could be improved."
"The product is expensive and needs the integration of more languages."
"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."
"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."
"The charts and tables could use better sorting, primarily using other variables than the ones on the figure. If they could implement views like in the older version (previous to Viya), it would be very nice."
"There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else."
"The licensing ends up being more expensive than other options."
"It is not as mature as competitors such as Tableau and QlikView."
"A bit more flexibility in the temperatization will be helpful."
 

Pricing and Cost Advice

"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."
"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."
"I rate the tool's pricing a five out of ten."
"It's quite expensive, but they do a special deal for universities."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"More affordable training for new staff members."
"We think that IBM SPSS is expensive for this function."
"We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff."
"Licensing is simple."
"$10,000 per annum for an enterprise license."
"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."
"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
"The product is quite expensive."
"The cost of the solution can be expensive. There is an additional cost for users."
"It's approximately $114,000 US dollars per year."
"It was licensed for corporate use, and its licensing was on a yearly basis."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
816,406 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
9%
University
9%
Manufacturing Company
8%
Financial Services Firm
20%
Computer Software Company
11%
Manufacturing Company
10%
Insurance Company
7%
Financial Services Firm
20%
Government
13%
Computer Software Company
10%
University
7%
 

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...
Ask a question
Earn 20 points
What do you like most about SAS Visual Analytics?
The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced...
What is your experience regarding pricing and costs for SAS Visual Analytics?
It's about an average of five. It's easy to scale, but it comes with cost.
What needs improvement with SAS Visual Analytics?
Some capabilities are missing compared to Power BI, especially when working with spreadsheet types. Furthermore, Exce...
 

Also Known As

SPSS Statistics
No data available
SAS BI
 

Learn More

Video not available
Video not available
 

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
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
Find out what your peers are saying about Databricks, Knime, Microsoft and others in Data Science Platforms. Updated: November 2024.
816,406 professionals have used our research since 2012.