SAS Analytics vs Weka comparison

SAS and Weka are both solutions in the Data Mining category. SAS is ranked #5 with an average rating of 8.0, while Weka is ranked #2 with an average rating of 8.0. SAS holds a 6.6% mindshare in DM, compared to Weka’s 21.2% mindshare. Additionally, 94% of SAS users are willing to recommend the solution, compared to 78% of Weka users who would recommend it.

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Executive Summary

We performed a comparison between SAS Analytics and Weka based on real PeerSpot user reviews.

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

To learn more, read our detailed SAS Analytics vs. Weka Report (Updated: December 2024).

Buyer's Guide

SAS Analytics vs. Weka

December 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of December 2024, in the Data Mining category, the mindshare of IBM SPSS Statistics is 15.1%, up from 12.7% compared to the previous year. The mindshare of SAS Analytics is 6.6%, down from 10.1% compared to the previous year. The mindshare of Weka is 21.2%, up from 19.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Mining

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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Tanin U

Assistant Vice President at AEON Thana Sinsap

Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks

SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency. While our current setup operates smoothly, certain partners still rely on another platform, specifically the virtualization dashboard. I believe it's a significant improvement compared to the traditional approach I've been using for the past ten years. Previously, when management had inquiries, they would create documents or memos, and IT would then track down the data, interpret it, and provide feedback. This process involved explaining the data structure, database, and definitions in the data warehouse. Now, with SAS Analytics, the workflow is much smoother and faster. IT is more streamlined, allowing for quicker access to data, and managers can directly access and utilize the sales reports.

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AwaisAnwar

Treasury Management in Finance Department at National University of Pakistan

Open source, good for basic data mining use cases except for the visualization results

I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results. Moreover, a new user interface would be great, especially for beginners. Something that guides them through the available tools and helps them achieve their goals. I haven't seen anything like that myself, though maybe it's there and I missed it.

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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

"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."

"The most valuable feature is the user interface because you don't need to write code."

"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."

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

"You can quickly build models because it does the work for you."

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

"It is perfectly adequate if all you need are the results and not the trail of evidence."

"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

"I use it to replicate our entire financial system to verify/duplicate calculations."

"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."

"The technical support is okay."

"It is able to connect to all major platforms, and all the smaller platforms that I have come across."

"The team immediately resolves the issues."

"I use SAS daily to analyze data, produce reports, and other outputs."

"It has improved the level of efficacy and validity of our reports."

"SAS Analytics plays a vital role in enhancing our decision-making processes, particularly in areas such as customer segmentation and operational efficiency."

More SAS Analytics pros

"Working with complicated algorithms in huge datasets is really easy in Weka."

"Weka is a very nice tool, it needs very small requirements. If I want to implement something in Python, I need a lot of memory and space but Weka is very lightweight. Anyone can implement any kind of algorithm, and we can show the results immediately to the client using the one-page feature. The client always wants to know the story. They want the result."

"The path of machine learning in classification and clustering is useful. The GUI can get you results. No programming is needed. No need to write down your script first or send to your model or input your data."

"I mainly use this solution for the regression tree, and for its association rules. I run these two methodologies for Weka."

"Weka's best features are its user-friendly graphic interface interpretation of data sets and the ease of analyzing data."

"Weka eliminates the need for coding, allowing you to easily set parameters and complete the majority of the machine learning task with just a few clicks."

"There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way."

"It is a stable product."

More Weka pros

Cons

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

"It could allow adding color to data models to make them easier to interpret."

"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."

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

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

"It could provide even more in the way of automation as there are many opportunities."

"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."

More IBM SPSS Statistics cons

"This solution should be made more user-friendly."

"Support at universities used to be limited, but I hear this is changing."

"They could enhance the AI capabilities of the product."

"The installation could also be easier, and the price could be better."

"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."

"The natural language querying and automated preparation of dashboards should be improved."

"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."

"I would like to see their interface to R added to either Base SAS or SAS Analytics."

More SAS Analytics cons

"I believe is there are a few newer algorithms that are not present in the Weka libraries. Whereas, for example, if I want to have a solution that involves deep learning, so I don't think that Weka has that capability. So in that case I have to use Python for ... predict any algorithms based on deep learning."

"Weka is a little complicated and not necessarily suited for users who aren't skilled and experienced in data science."

"A few people said it became slow after a while."

"If you have one missing value in your dataset and this missing value belongs to a specific attribute and the attribute is a numeric attribute and there is only one missing data, whenever you import this data, the problem is that Weka cannot understand that this is a numeric field. It converts everything into a string, and there is no way to convert the string into numerical math. It's really very complicated."

"Weka could be more stable."

"The filter section lacks some specific transformation tools. If you want to change a variable from a numeric variable to a categorical variable, you don't have a feature that can enable you to change a variable from a numeric variable to a categorical variable."

"Within the basic Weka tool, I don't see many tools that are available where we can analyze and visualize the data that well."

"The visualization of Weka is subpar and could improve. Machine learning and visualization do not work well together. For example, we want to know how we can we delete empty cells or how can we fill in the empty cells without cleaning the data system and putting it together."

More Weka cons

Pricing and Cost Advice

"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."

"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."

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

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

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

"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."

More IBM SPSS Statistics pricing and cost advice

"Prices were comparable with alternative solutions."

"The pricing tends to be higher, and there are additional expenses involved."

"The cost for SAS Business Intelligence can prove to be a little prohibitive."

"Setup costs were quite reasonable."

"Our licensing covers the usage for around 50 data analysts."

"I rate the product’s pricing a one out of ten."

"I think that the cost-benefit ratio is okay."

"Licensing was rather straightforward."

More SAS Analytics pricing and cost advice

"Currently, I am using an open-source version so I don't know much about the price of this solution."

"We use the free version now. My faculty is very small."

"As far as I know, Weka is a freeware tool, and I am not aware if they have an online solution or if it is a commercial product."

"The solution is free and open-source."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

Financial Services Firm

13%

Computer Software Company

11%

Educational Organization

10%

University

19%

Educational Organization

14%

Computer Software Company

10%

Financial Services Firm

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?

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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What do you like most about SAS Analytics?

I like that it is quickly embedding interactive reports and dashboards into a website, Outlook Mail, or even a mobile...

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What needs improvement with SAS Analytics?

The natural language querying and automated preparation of dashboards should be improved. The cost and accessibility ...

See all answers

What is your primary use case for SAS Analytics?

This is an application I use for data prep, data exploration, BI reporting, and some basic automated analytics.

See all answers

What do you like most about Weka?

It is a stable product.

See all answers

What is your experience regarding pricing and costs for Weka?

Weka is free and open-source software. That is why I used it over KNIME.

See all answers

What needs improvement with Weka?

I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might ...

See all answers

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

Dataiku vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

KNIME vs SAS Analytics

Compared 36% of the time

IBM SPSS Modeler vs SAS Analytics

Compared 14% of the time

More SAS Analytics Competitors

KNIME vs Weka

Compared 62% of the time

IBM SPSS Modeler vs Weka

Compared 7% of the time

Splunk User Behavior Analytics vs Weka

Compared 6% of the time

Elastic Search vs Weka

Compared 3% of the time

More Weka Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Data Mining

November 2024

Download SAS Analytics product report

Buyer's Guide

Weka

November 2024

Download Weka product report

Also Known As

SPSS Statistics

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Weka

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.”

SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

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

Aegon, Alberta Parks, Amway China, Axel Springer, Bank of America, Belgium Special Tax, CAP Index, CareSource, CBE Group, Cemig, Center for Responsible Lending, CESCE, Ceska sporitelna, Chantecler, Chico's, Chubb Group of Insurance Companies, CIGNA Thailand, City of Wiesbaden, Germany, Confused.com, Creditreform, Des Moines Area Community College, Deutsche Lufthansa, Directorate of Economics and Statistics, DIRECTV, Dow Chemical Company, Dow Chemical Company, Dun & Bradstreet, EDF Energy, Electrabel GDF SUEZ, ERGO Insurance Group, Erste Bank Croatia, Farmers Mutual Group, Finnair, Florida Department of Corrections, Geneia, Generali Hellas, Genting Malaysia Berhad, Grameenphone, Grandi Salumifici Italiani, HealthPartners, Highmark, Hong Kong Efficiency Unit, HP, Hyundai Securities, Illinois Department of Healthcare and Family ServicesInc Research, ING-DiBa, Institut Pertanian Bogor, InterContinental Hotels Group (IHG), IOM, Kelley Blue Book, Lenovo, Lillebaelt Hospital, Los Angeles County, Maspex Wadowice Group, National Bank of Greece, New Zealand Ministry of Health, New Zealand Ministry of Social Development, Nippon Paper, NMIMS, North Carolina Department of Transportation, North Carolina Office of Information Technology Services, Northern Virginia Electric Cooperative (NOVEC), Oberweis Dairy, ODEC, Ohio Mutual Insurance Group, Oklahoma State University, OneBeacon, Orange Business Services, Orange County Child Support Services, Organic, Orlando Magic, OTP Bank, Plano Independent School District, Project Odyssey, Royal Society for the Protection of Birds, RSA Canada, SCAD, Scotiabank, Singapore National Library Board, Sobeys Inc., SRA International, Staples, Statistics Estonia, Swisscom, SymphonyIRI Group, Telecom Italia, Telef‹nica O2, Town of Cary, Transitions Optical, TrueCar, Turkcell Superonline, UniCredit Bank Serbia, University of Alabama, University of Missouri, USDA National Agricultural Statistics Service

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Buyer's Guide

SAS Analytics vs. Weka

December 2024

Free Report: SAS Analytics vs. Weka

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