H2O.ai vs SAP Predictive Analytics comparison

H2O.ai and SAP are both solutions in the Data Science Platforms category. H2O.ai is ranked #20 with an average rating of 7.0, while SAP is ranked #25. 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 SummaryUpdated on Dec 5, 2024

SAP Predictive Analytics and H2O.ai compete in predictive analytics, each with distinct strengths. H2O.ai seems to have an edge with advanced machine learning frameworks and flexibility, providing better value in feature-rich environments.

Features: SAP Predictive Analytics integrates well within the SAP ecosystem, facilitating workflow simplification and automated predictive model creation for SAP users. H2O.ai offers open-source machine learning, scalability with big data, and integration support with R and Python, allowing for customizable machine learning operations.

Ease of Deployment and Customer Service:SAP Predictive Analytics provides cohesive integration within its suite, making deployment smoother for existing SAP users. H2O.ai offers flexible deployment options on various platforms with strong community and support, yielding more adaptability in diverse environments compared to SAP's integrated approach.

Pricing and ROI:SAP Predictive Analytics involves higher setup costs but offers high ROI for SAP-invested businesses by reducing operational disruptions. H2O.ai has a lower entry cost, appealing to organizations with established analytical infrastructures, achieving strong ROI through scalability and a comprehensive feature set, often proving more cost-efficient with better long-term returns.

To learn more, read our detailed H2O.ai vs. SAP Predictive Analytics Report (Updated: December 2024).

Buyer's Guide

H2O.ai vs. SAP Predictive Analytics

December 2024

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Categories and Ranking

IBM SPSS Statistics

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 H2O.ai is 1.5%, down from 1.6% 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

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

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.

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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 features that I have found most valuable are the Bayesian statistics and descriptive statistics."

"The most valuable feature is its robust statistical analysis capabilities."

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

"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 best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."

"It is a modeling tool with helpful automation."

More IBM SPSS Statistics pros

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

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

"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."

"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 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."

"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

"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."

"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."

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

"The solution needs more planning tools and capabilities."

"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."

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

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

"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

"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."

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

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

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

"The model management features could be improved."

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

"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."

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

Pricing and Cost Advice

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

"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."

"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."

"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."

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

"More affordable training for new staff members."

"The price of IBM SPSS Statistics could improve."

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."

"The pricing is reasonable"

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

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

Financial Services Firm

20%

Computer Software Company

11%

Manufacturing Company

11%

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.

See all answers

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...

See all answers

What needs improvement with H2O.ai?

H2O.ai can improve in areas like multimodal support and prompt engineering. They are already working on updates and c...

See all answers

What is your primary use case for H2O.ai?

We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversa...

See all answers

What advice do you have for others considering H2O.ai?

It is important to address data privacy concerns and ensure you're choosing the right vendor that meets your use case...

See all answers

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Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 16% of the time

Alteryx 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 11% of the time

Weka vs IBM SPSS Statistics

Compared 10% of the time

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Databricks vs H2O.ai

Compared 21% of the time

Amazon SageMaker vs H2O.ai

Compared 17% of the time

Dataiku vs H2O.ai

Compared 17% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 14% of the time

KNIME vs H2O.ai

Compared 12% of the time

More H2O.ai Competitors

IBM SPSS Modeler vs SAP Predictive Analytics

Compared 50% of the time

Microsoft Azure Machine Learning Studio vs SAP Predictive Analytics

Compared 50% of the time

More SAP Predictive Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Data Science Platforms

December 2024

Download H2O.ai product report

Buyer's Guide

Data Science Platforms

December 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

December 2024

Free Report: H2O.ai vs. SAP Predictive Analytics

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