IBM Data Science Experience (DSX) (Legacy) Alternatives

Data Science and Machine Learning Platforms...

Considering alternatives to IBM Data Science Experience (DSX) (Legacy)? See what this market IBM Data Science Experience (DSX) (Legacy) users also considered in their purchasing decision. When evaluating different solutions, potential buyers compare competencies in categories such as evaluation and contracting, integration and deployment, service and support, and specific product capabilities.

Check out real reviews verified by Gartner to see how IBM Data Science Experience (DSX) (Legacy) compares to its competitors and find the best software or service for your organization.

Reviewed in Last 12 Months

How Alternatives Are Selected

1. Dataiku

4.7

Dataiku is an enterprise AI development tool designed to expedite data preparation and machine learning model development. It offers low-code/no-code, visual components for model creation, while simultaneously providing advanced coding environments (Python, R, SQL). This makes it the ultimate tool for data scientists, enabling them to use a single platform for all aspects of data science projects, from model development to production deployment, significantly speeding up the process. Dataiku also supports mesh LLM, facilitating the integration of data science projects with LLM and GenAI development. Recently, an agentic framework has been added to the tool. It also has GenAI-enabled capabilities to create workflows and ETL pipelines, which will speed up the development significantly. As an enterprise-ready platform, Dataiku encompasses all essential aspects of security, scalability, development to product management, and AI governance.Read all insights and reviews for Dataiku

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Better evaluation and contracting

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2. Alteryx One Platform

4.4

This platform has been a strong addition to our analytics and data presentation workflow. It significantly reduces the time required to clean blend , and analyse data especially for teams that won't advanced analytics without heavy Reliance on custom coding.Read all insights and reviews for Alteryx One Platform

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Easier to integrate and deploy
Better evaluation and contracting

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3. DataRobot Agent Workforce Platform

4.6

Really like the product, it is intuitive and helpful. The new UX isn't my favorite and I keep switching to "classic UX" whenever I go in. I like that I can set it and forget it (for the most part). Finding additional use cases for the system is the challenge and that is how we add value to the expensive annual contract.Read all insights and reviews for DataRobot Agent Workforce Platform

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

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4. Amazon SageMaker AI

By Amazon Web Services (AWS)

4.4

Using AWS Sagemaker has been a gamechanger for my organization's data science workflows delivering seamless end to end automation prioritizing streamlined collaboration and rapid iteration. Huge focus on governance and training makes it a robust choice for scalable MLOps.Read all insights and reviews for Amazon SageMaker AI

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Better at service and support
Easier to integrate and deploy
Better evaluation and contracting

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5. MATLAB

4.4

Matlab is very powerful software for solving and graphing mathematic equations. Great use for linear programming and algorithmic equations. It presents data via the GUI graphing plots and matrixes Read all insights and reviews for MATLAB

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Easier to integrate and deploy
Better evaluation and contracting

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6. Altair RapidMiner

4.5

The team we worked with at Altair did a great job of addressing our use case and upskilling end users.Read all insights and reviews for Altair RapidMiner

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Easier to integrate and deploy
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7. IBM SPSS Statistics

By IBM

4.3

Our use case for spss is deployment in courses. we want as close to what students will experience in industry as possible. We like to offer virtualization if possible, but understand where cloud solutions exist why that is difficult. we need instructors to have access to the same version of the software. we had a lot of trouble finding a workable solution for SPSS at scale i. our academic programs.Read all insights and reviews for IBM SPSS Statistics

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Better at service and support
Easier to integrate and deploy
Better evaluation and contracting

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8. Databricks Data Intelligence Platform

4.5

My organization up until just before 2021 was by and large an on premise shop. So most of our ETL tools, reporting and business intelligence tech stack was all based on premise. That all changed in the last few years as there has been a major shift towards embracing more of what cloud providers can enable our organization. Our journey began with Azure and talking about reporting, data science, machine learning and ELT/ETL you have to look at Azure Databricks. Databricks can seem a bit daunting at first as there is a lot of features packed into it but after using it for a month you will definitely get the hang of things and how to find things. Its definitely been a tool that has become our go-to when looking towards any sort of data integration or analysis Read all insights and reviews for Databricks Data Intelligence Platform

Where IBM Data Science Experience (DSX) (Legacy) Scored Higher

Better evaluation and contracting

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