H2O.ai vs SAP Predictive Analytics comparison

H2O.ai and SAP are both solutions in the Data Science Platforms category. H2O.ai is ranked #22, while SAP is ranked #24. H2O.ai holds a 1.5% mindshare in Data Science Platforms, compared to SAP’s 0.4% mindshare. Additionally, 100% of H2O.ai users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

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Executive Summary

We performed a comparison between H2O.ai and SAP Predictive Analytics 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 H2O.ai vs. SAP Predictive Analytics Report (Updated: October 2024).

Buyer's Guide

H2O.ai vs. SAP Predictive Analytics

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 H2O.ai is 1.5%, up from 1.5% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.4%, down from 0.5% 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

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.

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Kashif Yaseen

Trainee Decision Scientist at a tech services company with 1,001-5,000 employees

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…

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Gary Cook

Executive at Empowered Analytics

Enables us to forecast and pull trends and has an easy installation

My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

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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

"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 into multidimensional setup space. It's the multidimensional space facility that is most useful."

"It offers very good visualization."

"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

"SPSS is quite robust and quicker in terms of providing you the output."

"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."

"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."

"It has the ability to easily change any variable in our research."

More IBM SPSS Statistics pros

"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."

"The ease of use in connecting to our cluster machines."

"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."

"It is helpful, intuitive, and easy to use. The learning curve is not too steep."

"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."

"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."

"The most valuable feature of H2O.ai is that it is plug-and-play."

"The most valuable features are the analytics and reporting."

"I think the features of the actual ability to forecast and pull trends and correlations has been really good."

Cons

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

"The reports could be better."

"I think the visualization and charting should be changed and made easier and more effective."

"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."

"The statistics should be more self-explanatory with detailed automated reports."

"The technical support should be improved."

"Technical support needs some improvement, as they do not respond as quickly as we would like."

"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."

More IBM SPSS Statistics cons

"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."

"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."

"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."

"H2O.ai can improve in areas like multimodal support and prompt engineering."

"I would like to see more features related to deployment."

"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."

"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."

"The model management features could be improved."

"This solution works for acquired data but not live, real-time data."

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."

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

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

"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."

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

"More affordable training for new staff members."

More IBM SPSS Statistics pricing and cost advice

"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."

"A free trial version is available for testing out this solution."

"The pricing is reasonable"

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816,406 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

University

Computer Software Company

Manufacturing Company

Financial Services Firm

20%

Computer Software Company

11%

Manufacturing Company

10%

Insurance Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

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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...

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Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 14% of the time

Alteryx vs IBM SPSS Statistics

Compared 14% 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

Databricks vs H2O.ai

Compared 21% of the time

Dataiku vs H2O.ai

Compared 19% of the time

Amazon SageMaker vs H2O.ai

Compared 16% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 14% of the time

KNIME vs H2O.ai

Compared 11% of the time

More H2O.ai Competitors

IBM SPSS Modeler vs SAP Predictive Analytics

Compared 56% of the time

Microsoft Azure Machine Learning Studio vs SAP Predictive Analytics

Compared 44% of the time

More SAP Predictive Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

November 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Data Science Platforms

November 2024

Download H2O.ai product report

Buyer's Guide

Data Science Platforms

November 2024

Download SAP Predictive Analytics product report

Also Known As

SPSS Statistics

No data available

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

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IBM

H2O.ai

SAP

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.”

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

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

mBank

Buyer's Guide

H2O.ai vs. SAP Predictive Analytics

October 2024

Free Report: H2O.ai vs. SAP Predictive Analytics

Find out what your peers are saying about H2O.ai vs. SAP Predictive Analytics and other solutions. Updated: October 2024.

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