# Red Hat OpenShift Data Science Reviews **Vendor:** Red Hat **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.4/5.0 **Total Reviews:** 25 ## About Red Hat OpenShift Data Science Red Hat® OpenShift® AI is a flexible, scalable artificial intelligence (AI) and machine learning (ML) platform that enables enterprises to create and deliver AI-enabled applications at scale across hybrid cloud environments. Built using open source technologies, OpenShift AI provides trusted, operationally consistent capabilities for teams to experiment, serve models, and deliver innovative apps. ## Red Hat OpenShift Data Science Reviews ### 1. Allows you to explore and discover valuable insights **Rating:** 5.0/5.0 stars **Reviewed by:** kelly R. | Digital Media Manager, Marketing and Advertising, Mid-Market (51-1000 emp.) **Reviewed Date:** January 03, 2024 **What do you like best about Red Hat OpenShift Data Science?** My overall experience with Red Hat OpenShift Data Science has been excellent. The software has exceeded my expectations in terms of its performance and ease of use. Additionally, the support and documentation provided by Red Hat has been extremely helpful in resolving any issues or concerns that have arisen. It is especially suitable for research and development projects, as well as for companies that require real-time data analysis. Its ability to process large volumes of data and its integration with other tools allows users to efficiently. **What do you dislike about Red Hat OpenShift Data Science?** I can only say from my experience that some advanced features may require more specialized technical knowledge, which may limit their use for those who are less familiar with data analysis. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** It has allowed me to perform complex data analysis efficiently and obtain valuable insights for my organization. This software allows us to access advanced tools and functions to process large amounts of data and extract valuable insights. Its use case ranges from data analysis and visualization to the creation of predictive models and the implementation of real-time solutions. ### 2. Transforming Business Analysis: Containerization for Agile Collaboration **Rating:** 4.5/5.0 stars **Reviewed by:** Adrian Andres J. | Accounting and Reporting Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** September 21, 2023 **What do you like best about Red Hat OpenShift Data Science?** Containerization offers unrivaled scalability and flexibility in the area of finance, where working with large datasets and complicated algorithms is standard. It enables us to containerize our data science workloads, ensuring reliable performance in a range of settings. This feature greatly speeds up the creation and deployment of financial models. Our financial analysis team benefits greatly from the collaboration that Red Hat OpenShift Data Science fosters. We can work on projects at the same time, keep track of changes, and smoothly combine contributions thanks to its interaction with Git and other version control systems. When working with several stakeholders that need to analyze and contribute to financial models and studies, this skill is important. **What do you dislike about Red Hat OpenShift Data Science?** Scalability-enabling containerization may also need a lot of resources. Running numerous containers at once might place a burden on hardware resources and demand a lot of processing power. Hardware changes might be required as a result, which would raise the overall implementation cost. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** My responsibilities include managing crucial financial analysis, risk evaluations, and modeling. We have changed our strategy with the help of Red Hat OpenShift Data Science. Finance is based on collaboration, which Red Hat OpenShift Data Science excels at fostering. Our financial assessments now have better quality because of version control, collaboration on projects, and traceability of changes. Now, our team can work together to develop intricate models while utilizing the unique skills of each team member. We got answers more quickly, which allowed us to decide on our investment portfolio in real time. Now that we have complete transparency into the contributions and modifications made by each team member, we can work together to construct complex financial models. This has increased the precision of our models while also speeding up project completion. ### 3. Real-Time Data Processing and Collaboration: The Key to Business Success with OpenShift Data Science **Rating:** 4.5/5.0 stars **Reviewed by:** Jaime M. | Senior Accounting and Finance Manager, Market Research, Mid-Market (51-1000 emp.) **Reviewed Date:** September 18, 2023 **What do you like best about Red Hat OpenShift Data Science?** Hat Red With containerization, OpenShift Data Science offers a distinctive method for managing data science workflows. We may use this capability to package up our financial models, algorithms, and data pipelines, assuring consistency and reproducibility throughout different phases of research. It streamlines the creation and application of sophisticated financial models, improving the effectiveness of our job. Data that is current is essential for financial analysis. We can evaluate and respond to financial data as it is generated or received thanks to OpenShift Data Science's capability for real-time data processing, which distinguishes it from many other platforms. For monitoring market trends, adapting investment plans to shifting economic conditions, and tracking market movements, this real-time capability is crucial. **What do you dislike about Red Hat OpenShift Data Science?** The platform can become quite demanding when dealing with large amounts of data. A robust hardware infrastructure is necessary to take full advantage of its capabilities. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** By enabling us to containerize complex models, OpenShift Data Science and Machine Learnig platform has substantially enhanced my job and sped up our financial modeling and forecasting procedures. The transition from development to production is made easier and results are guaranteed to be consistent. Our approach to handling financial data has changed as a result of its containerization, real-time data processing, and collaborative capabilities. I and other finance professionals can make quick, accurate judgments based on data thanks to this platform. Financial success depends on staying ahead of market trends and economic upheavals. We have the ability to quickly make educated decisions thanks to real-time data processing capabilities. As a result, we are better able to predict the financial future, which helps us plan out our resource allocation and investment strategies more effectively. ### 4. The powerfulness of model deployment **Rating:** 4.5/5.0 stars **Reviewed by:** Marcos P. | Financial Analyst, Market Research, Mid-Market (51-1000 emp.) **Reviewed Date:** September 01, 2023 **What do you like best about Red Hat OpenShift Data Science?** When it comes to effortlessly incorporating containerization into the machine learning workflow, Red Hat OpenShift Data Science excels. This functionality makes sure that machine learning models created in one environment can be reliably applied during other production and development stages. It makes the transition from development to production seamless and gets rid of the compatibility problems sometimes connected with model deployment. It offers a central platform where analysts, engineers, and data scientists can easily cooperate. This collaborative setting encourages knowledge exchange, quickens project turnaround times, and improves the caliber of machine learning models. **What do you dislike about Red Hat OpenShift Data Science?** Red Hat OpenShift Data Science shines as a reliable platform in the field of machine learning. It has excellent orchestration of ML pipelines. Nonetheless, there is still potential for improvement in terms of streamlining the deployment procedure and providing a more seamless conversion from model development to practical use. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** For predictive maintenance, we had to implement a sophisticated machine learning model. The model performed consistently in our production environment thanks to the containerization characteristics of Red Hat OpenShift Data Science. This not only helped us save time, but it also increased the model's dependability, enabling us to take preventative maintenance measures to minimize downtime. ### 5. Innovative and powerful solution for advanced analytics. **Rating:** 4.5/5.0 stars **Reviewed by:** miguel g. | Small-Business (50 or fewer emp.) **Reviewed Date:** August 28, 2023 **What do you like best about Red Hat OpenShift Data Science?** Excellent platform that combines the flexibility and scalability of Red Hat OpenShift with the capabilities of data science. This solution offers a centralized, integrated environment that makes it easy to develop, deploy, and manage data science applications. The ability to transform large volumes of data into relevant and actionable information has fueled the growth and success of many companies. **What do you dislike about Red Hat OpenShift Data Science?** There is nothing that I dislike about this platform since it allows data scientists to work with the best tools that fit each need and the best preferences in the best way. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** This platform makes it easy to integrate with popular tools and languages like Jupyter Notebooks, Python, and R. This best enables data scientists to work with the tools that best fit their needs and preferences, allowing for easy scalability and flexibility of data science environments. This ensures that applications can grow with the changing needs of the organization. ### 6. Data Science on Your Terms **Rating:** 4.5/5.0 stars **Reviewed by:** Bertha A. | Mid-Market (51-1000 emp.) **Reviewed Date:** July 06, 2023 **What do you like best about Red Hat OpenShift Data Science?** Because Red Hat OpenShift Data Science is an open-source platform, it is free to use and change. It makes it an excellent choice for enterprises wishing to tailor the platform to their requirements. Jupyter Notebooks, TensorFlow, and PyTorch are among the integrated tools on the forum. It makes it simple for data scientists to use machine learning tools they are currently familiar with. It allows enterprises to select the deployment environment that best suits their requirements. **What do you dislike about Red Hat OpenShift Data Science?** Red Hat OpenShift Data Science documentation may be enhanced. Some documentation is out of date or incomplete. The community surrounding Red Hat OpenShift Data Science is still tiny. It can make finding help and support for the platform challenging. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** For the past few months, I've been using Red Hat OpenShift Data Science, and I've found it to be a helpful tool for my work as a data scientist. The platform made it simple to start with machine learning and gave me the tools to construct and deploy machine learning models. I've also found the Red Hat OpenShift Data Science community helpful and encouraging. Overall, Red Hat OpenShift Data Science has wowed me. It is a sophisticated and adaptable tool that has aided my work as a data analyst. ### 7. Simplifying machine learning workflows **Rating:** 4.5/5.0 stars **Reviewed by:** Matias A. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** July 06, 2023 **What do you like best about Red Hat OpenShift Data Science?** Encourages teams of data scientists and machine learning experts to work together seamlessly. It provides a single platform for sharing code, data, models, and experiments among team members. It enables more effective cooperation, knowledge sharing, and increased production. Furthermore, the platform automates the deployment and management of machine learning models, allowing teams to develop, experiment, and provide results more quickly. It offers a unified platform for data scientists to execute operations like data intake, exploration, visualization, preprocessing, model training, validation, and deployment. It eliminates the need to transfer between tools or environments, optimizing the workflow and saving time and effort. **What do you dislike about Red Hat OpenShift Data Science?** The interpretability and transparency of machine learning models is one area that could benefit from future research. Currently, the platform lacks built-in tools or functionalities for model interpretation. It might make it difficult for data scientists to comprehend why a model generated a specific prediction, which is essential when explaining and justifying model decisions to users. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** One area where the software has proven to be beneficial is model deployment and management. I've been able to effortlessly deploy and upgrade machine learning models in production scenarios with its smooth interface with version control systems and automated deployment features. It saves me significant time and effort, allowing me to concentrate on refining and enhancing the models rather than dealing with time-consuming deployment processes. ### 8. Revolutionizing the world of data science with Red Hat Openshift Data Science **Rating:** 4.5/5.0 stars **Reviewed by:** Javier V. | It Reporting & Analytics, Market Research, Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2023 **What do you like best about Red Hat OpenShift Data Science?** One of the most notable features of Red Hat Openshift Data Science is its versatility. The platform allows users to easily build and deploy machine learning models in any programming language. In addition to having the possibility of working together on a single project allows for more fluid communication, avoiding duplication of efforts and increasing efficiency in data management. **What do you dislike about Red Hat OpenShift Data Science?** Although overall Red Hat Openshift Data Science is an impressive tool, there are areas that could be improved. One of them is the initial learning curve. Despite its simple interface, some of the more advanced functionality can be a bit overwhelming for newcomers. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Red Hat Openshift Data Science emerges as an invaluable ally in solving a variety of business and scientific problems. Among them, the ability to perform predictive and generative analysis stands out, improve decision-making in real time, identify hidden patterns in large data sets, and optimize processes by detecting anomalies and automating repetitive tasks. ### 9. Automating Data Science Workflow with Red Hat OpenShift **Rating:** 4.5/5.0 stars **Reviewed by:** Diego V. | Mid-Market (51-1000 emp.) **Reviewed Date:** July 04, 2023 **What do you like best about Red Hat OpenShift Data Science?** Unlike similar applications, Red Hat OpenShift Data Science has a unique feature that allows data scientists, engineers, and IT teams to collaborate seamlessly. Stakeholders can install machine learning models, access and share real-time information, and collaborate on projects using its intuitive interface, all inside a secure and centralized environment. This collaborative functionality significantly improves productivity, communication, and decision-making, distinguishing Red Hat OpenShift Data Science in the industry. The application transforms the data science workflow by enabling automated lifecycle management. That means that the software streamlines the entire process, from model creation to deployment, removing the need for manual interventions and lowering the chance of errors. Data engineers and scientists may focus more on innovation with a single platform that automates model versioning, monitoring, and scaling. **What do you dislike about Red Hat OpenShift Data Science?** Red Hat OpenShift Data Science's testing capabilities could be expanded by delivering a comprehensive and user-friendly automated testing framework. It would aid in model validation and assure optimal performance in various settings, allowing data engineers to confidently deploy their models in production systems. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** As a data engineer, Red Hat OpenShift Data Science has helped us accelerate our data-driven projects. My team and I have seamlessly combined the experience of data scientists and IT teams by exploiting its collaborative model deployment capability and rapidly deploying complex predictive models into our production environment. The automatic lifecycle management tool guarantees that models are efficiently versioned, monitored, and scaled, removing the need for manual intervention and enhancing our team's productivity. This program has proven to be an incredible asset, allowing me to focus more on extracting relevant insights from massive amounts of data and delivering significant outcomes to our firm. ### 10. A platform for Seamless Data Science Workflow **Rating:** 4.5/5.0 stars **Reviewed by:** Camila C. | Digital Marketing Specialist, Enterprise (> 1000 emp.) **Reviewed Date:** July 04, 2023 **What do you like best about Red Hat OpenShift Data Science?** It provides a unified workflow for data exploration, model construction, deployment, and administration. This integrated solution reduces the need for different tools and simplifies the data science process, allowing teams to concentrate on providing insights and driving innovation. Red Hat OpenShift uses containerization technology, allowing simple deployment and scalability. The platform offers consistency across diverse environments and simplifies the management of complex deployments by encapsulating data science workloads in containers. Because of its scalability, it is suited for enterprise-level applications that require large-scale data processing and analysis. **What do you dislike about Red Hat OpenShift Data Science?** The platform offers powerful model-building and deployment capabilities, but more comprehensive tools and features are available to monitor model performance, track model versions, and assure regulatory compliance. Enhancing the platform with built-in model monitoring tools, such as real-time performance metrics and anomaly detection, would allow data scientists to proactively discover and address deployed models. Incorporating model governance elements such as model versioning, auditing, and explainability would give enterprises more control and insight over their machine-learning models. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Red Hat OpenShift Data Science has dramatically influenced my job. Our data science workflows have been optimized due to the platform's seamless integration of tools and services, allowing us to offer insights and solutions more efficiently. Thanks to the containerized design, we could scale our models, manage enormous datasets, and generate maintenance models for a client. The platform's end-to-end capabilities, ranging from feature consistency across several platforms to scalability, allow us to handle large-scale data requirements. ### 11. A complete solution for our organization **Rating:** 4.5/5.0 stars **Reviewed by:** Barbara I. | Marketing Specialist, Marketing and Advertising, Mid-Market (51-1000 emp.) **Reviewed Date:** June 19, 2023 **What do you like best about Red Hat OpenShift Data Science?** What I like most about this tool is that it offers a huge number of tools and services that make it easy to integrate and analyze data from different sources and formats. It also allows you to run machine learning models both internally and in hybrid cloud environments. **What do you dislike about Red Hat OpenShift Data Science?** Since we are using this tool, we can say that it is one of the great ones that we have used, besides that we have not found any fault with this product since it is very easy to manage container applications and the problems related to them, such as the Scanning of container images and related values before production deployment. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** I have been using OpenShift for over 2 years. I have seen many improvements in Openshift and it just keeps getting better. Most importantly, it provides a free lifetime account that can be used as part of OpenShift. Most importantly, you can attach your own domain to your app, even with a free account. ### 12. Innovative Solutions and Full Potential of Data Science with Red Hat OpenShift **Rating:** 4.5/5.0 stars **Reviewed by:** Antonella S. | Digital Marketing Manager, Enterprise (> 1000 emp.) **Reviewed Date:** June 19, 2023 **What do you like best about Red Hat OpenShift Data Science?** The robust Red Hat OpenShupblueift Data Science platform has completely transformed how we approach data science and machine learning. It offers a variety of distinctive features that make it stand out from other media, and I have found it to be a valuable tool in my job. Every process stage, from data discovery and model building to testing and deployment, is integrated into a user-friendly platform. It has dramatically decreased the time and effort needed to create and implement machine learning models, enabling us to provide outcomes more quickly and effectively. Multiple team members may work on the same project concurrently using Red Hat OpenShift Data Science, exchanging ideas and collaborating in real-time. As a result, our team's productivity has significantly increased, creating a more inclusive and collaborative work atmosphere. **What do you dislike about Red Hat OpenShift Data Science?** The process of integrating external AI models is one such topic. The platform offers integration, but it can be complicated and drawn out. Users could use AI-powered automation if the procedure were made more accessible, increasing the platform's functionality. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Many of the duties that used to consume a significant amount of my time have been automated and simplified, allowing me to concentrate on more complicated issues. The platform's collaborative capabilities have also enhanced our team's communication and cooperation, which has increased performance and made the office atmosphere more fun. We have been able to experiment with novel ideas and methodologies, pushing the limits of what is feasible in data science thanks to access to a wide variety of cutting-edge tools and technology. ### 13. Unleash the Power of Data Science with Red Hat OpenShift **Rating:** 4.5/5.0 stars **Reviewed by:** Elena D. | Mid-Market (51-1000 emp.) **Reviewed Date:** June 15, 2023 **What do you like best about Red Hat OpenShift Data Science?** By providing a seamless platform for collaboration for data scientists, developers, and IT operators, Teams can collaborate effectively on this single platform, speeding up the creation and deployment of AI/ML models in hybrid cloud settings, in the public cloud, or at the edge. Its ecosystem incorporates various well-known data science tools and applications from business partners, giving customers access to extensive data lifecycle capabilities. Red Hat OpenShift Data Science allows users to quickly construct and deploy containerized machine learning pipelines powered by data. **What do you dislike about Red Hat OpenShift Data Science?** Red Hat OpenShift Data Science offers some data storage options; however, reducing the procedure for connecting to and importing data from outside sources will improve the user experience and make acquiring data for modeling and analysis easier. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** My work has been considerably influenced by Red Hat OpenShift Data Science's ability to streamline the creation and deployment of machine learning models. My team has collaborated more effectively because of the platform's easy-to-use features, which have helped us finish developing and deploying our models faster. Additionally, the extensive partner ecosystem has given us access to cutting-edge tools and technologies, enabling us to try out novel strategies and keep up with the latest developments in our data science activities. It has produced more accurate and perceptive models, resulting in better business decisions. ### 14. Excellent essential tool for current companies **Rating:** 4.5/5.0 stars **Reviewed by:** Alexander S. | Marketing Specialist, Enterprise (> 1000 emp.) **Reviewed Date:** June 09, 2023 **What do you like best about Red Hat OpenShift Data Science?** I like this platform because in the best way it offers Ease of Use, it offers an intuitive user interface and easy to use, which makes it easy and effective to use, it allows an integration of open source tools that offers it to be a flexible and scalable solution to handle large volumes of data, it also offers us a secure environment for data management, which is essential to guarantee privacy and the protection of confidential information **What do you dislike about Red Hat OpenShift Data Science?** I don't dislike this platform at all because it is complete for business data management and analysis. Although it can be a bit expensive, its features, functionality and benefits make it a value-added solution, which is a great advantage in terms of efficiency and time. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** This is a platform that will help you manage and analyze data more easily, in addition to offering you better incredible solutions for managing your business data, thus allowing you to help you transform your data into added value for your company. This platform is an excellent solution ideal for those organizations that seek to obtain greater value from their data, especially when it comes to data analysis. ### 15. Allows data to be handled more efficiently **Rating:** 4.5/5.0 stars **Reviewed by:** Margaret Z. | Salesforce Developer, Enterprise (> 1000 emp.) **Reviewed Date:** June 13, 2023 **What do you like best about Red Hat OpenShift Data Science?** I love this instrument because this platform gives automatic learning tools and models for prototypes quickly of study models and apply them to the data of your organization, it is a cloud application containers platform that allows you to produce, carry out and rule Container applications. It also allows you to minimize waiting times, promote innovation and increase the cost of the data **What do you dislike about Red Hat OpenShift Data Science?** It could be more expensive than other data science platforms, especially if you need to use extra services, however there are no bad operations in terms of functionality of this solution, being one of the most efficient of its kind **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** It allows you to simply share your data science projects with other assistants and work together more positively. It is also simple to use and has entry to each of the instruments, which accelerates the process of creating data study models. ### 16. Enables business development in IT **Rating:** 4.5/5.0 stars **Reviewed by:** Lucia R. | Sales Analyst, Market Research, Enterprise (> 1000 emp.) **Reviewed Date:** May 30, 2023 **What do you like best about Red Hat OpenShift Data Science?** I like it because it is all in one in application management, it is a system that allows organizations to be able to develop new applications or even be able to manage existing ones, modernizing them to their requirements in an easy-to-use interface, this system allows the workflow to be more fast and efficient since it allows the codes to be more easily managed, from the cloud or even in a hybrid way, there are many functions that are new and necessary in this system **What do you dislike about Red Hat OpenShift Data Science?** I have no criticism, since Red Hat has been constantly improving to offer good solutions, this one in particular helps companies to develop advanced technology according to what they require and even take their applications and systems to a new level safely **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Allows applications to be used in business systems, allowing many more tools to help complete tasks efficiently in a safe environment for the organization's system ### 17. A tool to analyze functional data **Rating:** 4.5/5.0 stars **Reviewed by:** Thobias B. | Technology Consultant, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 08, 2023 **What do you like best about Red Hat OpenShift Data Science?** I like this tool because it offers unique possibilities for data collection with artificial intelligence advice, which guarantees greater precision and speed, this solution is also compatible with different types of languages used in programming, so the adaptation in the organization is ensured, in addition allows to have even data patterns in an updated way for better process creations **What do you dislike about Red Hat OpenShift Data Science?** I have no problems, it is necessary to know what this system is about if you want this system to be technologically usable in the organization, but I do not consider that they are negative aspects when using this system **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** It allows complete processing of business data, it is usually ideal for more advanced statistics regarding business data and since its platform is easily manageable, it does not correspond to large costs for its deployment ### 18. Accelerate Your Data Science Workflows with Red Hat Openshift **Rating:** 4.0/5.0 stars **Reviewed by:** Niranjan2 S. | Mid-Market (51-1000 emp.) **Reviewed Date:** March 10, 2023 **What do you like best about Red Hat OpenShift Data Science?** Secure and scalable deployment: OpenShift Data Science allows data scientists to deploy their models at scale in a safe and scalable environment. The platform includes features such as automated scaling and data encryption to ensure data security and availability **What do you dislike about Red Hat OpenShift Data Science?** The potential challenge is that Red Hat OpenShift Data Science is a complex platform requiring some technical expertise to set up and use effectively. Users may need to spend some time learning how to use the platform and configuring it to meet their specific needs **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Scalability: OpenShift Data Science enables data scientists to scale their workloads quickly and efficiently.Collaboration: Data scientists often work in teams and require a collaborative environment to share their work and collaborate effectively. Data scientists spend a significant amount of time managing data. OpenShift Data Science provides tools for managing data efficiently, including data storage, data processing. Data science workflows can be complex and time-consuming. OpenShift Data Science automates many of the repetitive tasks involved in the data science workflow, freeing up time for data scientists to focus on more complex tasks ### 19. Amazing Application **Rating:** 4.5/5.0 stars **Reviewed by:** Samar D. | Associate Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 10, 2023 **What do you like best about Red Hat OpenShift Data Science?** The programme provides a collaborative workspace in which data scientists and analysts may collaborate on projects, discuss ideas, and write code together. The software comes with a comprehensive data science toolset that includes popular programming languages such as Python and R, data visualisation tools, machine learning techniques, and data preparation tools. The software is straightforward to use, having a user-friendly interface that enables data scientists and analysts to operate rapidly and effectively. **What do you dislike about Red Hat OpenShift Data Science?** While the programme is intended to be user-friendly, it can nevertheless be difficult for non-technical users, particularly those unfamiliar with container-based platforms. Because Red Hat OpenShift Data Science software is a commercial product, it might be costly for smaller enterprises or individual users. Users may need to put in time and effort to learn how to utilise the programme efficiently, especially if they are unfamiliar with container-based platforms or data science. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Red Hat OpenShift Data Science software is a fantastic alternative for enterprises that demand a versatile, collaborative, and secure data science platform. It provides a comprehensive data science platform, including machine learning methods, data visualisation tools, and data preparation tools. But, organisations should be aware of the software's complexity and cost, and be prepared to invest time and effort in learning how to utilise it effectively. Overall, Red Hat OpenShift Data Science software offers a powerful and dependable option for data science applications. ### 20. Powering Machine Learning Workflows with Red Hat OpenShift **Rating:** 4.5/5.0 stars **Reviewed by:** Harshit A. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 21, 2023 **What do you like best about Red Hat OpenShift Data Science?** I really like how efficient and secure Red Hat OpenShift Data Science is, and the interface is easy to use. Plus, being open source gives me more control over my data and reduces vendor lock-in. **What do you dislike about Red Hat OpenShift Data Science?** While I really like it. But since community is still growing, the documentation and technical support could be better, and I'd love to see more options for auto-scaling based on statistics. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Red Hat OpenShift Data Science is making my life easier by simplifying deployment management, providing a framework for deploying containers over different systems, and improving team productivity through better workflow management. ### 21. Self-Healing, auto scaling and easy cluster management function product **Rating:** 4.0/5.0 stars **Reviewed by:** Kishore M. | Associate Technical Consultant, Small-Business (50 or fewer emp.) **Reviewed Date:** March 17, 2023 **What do you like best about Red Hat OpenShift Data Science?** The default security setup is top-notch, the automation process is straightforward and scalable in the future and an alert mechanism that notifies when overutilization of an application **What do you dislike about Red Hat OpenShift Data Science?** Document and technical support could be improved. Even though the auto-scaling feature is there, it would have been great if it came with more options based on statistics. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** Easy to manage deployment across the environments.With code-ready workspaces, we can develop, start the test run, start the container, drop the container and repeat in short period still it offers sustainability better than Kubernetes. ### 22. Good product **Rating:** 4.5/5.0 stars **Reviewed by:** Shruti S. | CSM, Small-Business (50 or fewer emp.) **Reviewed Date:** March 07, 2023 **What do you like best about Red Hat OpenShift Data Science?** The user experience is good. Easy to navigate and learn. Document and reporting is easy **What do you dislike about Red Hat OpenShift Data Science?** None as on today. Maybe be more training content. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** It's helping to manage the workflow for the functionality of team production . ### 23. Automatic installation and good developee experience **Rating:** 3.5/5.0 stars **Reviewed by:** Vishakha K. | Senior Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 10, 2023 **What do you like best about Red Hat OpenShift Data Science?** Red hat openshift data science is helping is reducing developers turn around time. Deploying and running is efficient. **What do you dislike about Red Hat OpenShift Data Science?** I do not have anything to dislike as such. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** This is helpful when deploying containers over different frameworks. ### 24. Red Hat OpenShift Data Science **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Automotive | Small-Business (50 or fewer emp.) **Reviewed Date:** March 11, 2022 **What do you like best about Red Hat OpenShift Data Science?** Open source, no vendor lock-in and it is also very secure platform **What do you dislike about Red Hat OpenShift Data Science?** Not dislike, it's still a growing community, so sometimes, I do not find major online support when I search **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** I encountered it for data science projects I needed to work on. It was easy to use and not so bad to set up. I used the public cloud platform ### 25. Testing made easy. **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Transportation/Trucking/Railroad | Small-Business (50 or fewer emp.) **Reviewed Date:** October 04, 2021 **What do you like best about Red Hat OpenShift Data Science?** Smooth use and integration of third party ML tools like Anaconda, IBM Watson Studio etc. **What do you dislike about Red Hat OpenShift Data Science?** Nothing much to dislike, its a really rapid tool and is a must for every data scientist to try once. **Recommendations to others considering Red Hat OpenShift Data Science:** It is a must try especially for prototyping with Flask, uWSGI, NGINX and docker. **What problems is Red Hat OpenShift Data Science solving and how is that benefiting you?** I had a prototype built for demand allocation, wanted to test it out on various different containers. The most important benefit was the iteration time, it was amazingly fast. ## Red Hat OpenShift Data Science Discussions - [What is Red Hat OpenShift Data Science used for?](https://www.g2.com/discussions/what-is-red-hat-openshift-data-science-used-for) - [View Red Hat OpenShift Data Science pricing details and edition comparison](https://www.g2.com/products/red-hat-openshift-data-science/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-12+12%3A55%3A58+-0500&secure%5Bsession_id%5D=03dacce3-9d09-4886-bc31-6d377d1583e3&secure%5Btoken%5D=e11992745fb72d918a5fdfbffe67d7319aba7a59c91d1eed53a9dacb8b5f26d1&format=llm_user) ## Red Hat OpenShift Data Science Features **System** - Data Ingestion & Wrangling **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Model Development** - Feature Engineering **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Deployment** - Managed Service - Application - Scalability **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top Red Hat OpenShift Data Science Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (781 reviews) - [IBM watsonx.ai](https://www.g2.com/products/ibm-watsonx-ai/reviews) - 4.4/5.0 (133 reviews) - [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews) - 4.2/5.0 (51 reviews)