Likelihood to Recommend Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
Read full review Saturn Cloud is a powerful data science platform that offers numerous benefits to organizations. It simplifies and streamlines the development, deployment, and scaling of data science and machine learning models. The platform addresses common business problems such as scalability, collaboration, efficiency, and cost-effectiveness. With Saturn Cloud, organizations can easily handle large datasets and complex computations, collaborate effectively among data science teams, automate repetitive tasks, optimize workflows, and utilize flexible and cost-efficient cloud resources. By leveraging Saturn Cloud, organizations can accelerate their data science projects, improve productivity, and achieve better outcomes in areas such as predictive modeling, recommendation systems, fraud detection, and more.
Read full review Pros The intuitiveness of this tool is very good. Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals The way you can control things, the set of APIs gives a lot of flexibility to a developer. Read full review Parallel Computing: Saturn Cloud helps us do multiple tasks at the same time, making our work faster and more efficient. Easy Scalability: Saturn Cloud lets us adjust our computer power depending on our project's needs, without any hassle. GPU Support: Saturn Cloud helps us work better with powerful machines, especially when we need them for complex tasks. Read full review Cons Read full review While Saturn Cloud offers a range of pre-built templates and workflows, there is currently limited support for customization. For example, users may not be able to modify the pre-configured environments that come with the templates, or may find it difficult to integrate their own custom libraries and tools. Offering more flexibility in this area could help users tailor the platform to their specific needs and workflows. While Saturn Cloud offers a variety of pre-built environments for data science and machine learning workloads, some users may prefer to use custom Docker images instead. However, the platform currently has limited support for Docker, which can be a limitation for users who need to work with specific dependencies or custom libraries. Adding more robust support for Docker could help to make the platform more versatile and adaptable to a wider range of use cases. Read full review Usability As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
Read full review Support Rating The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
Read full review Alternatives Considered Strictly for Data Science operations,
Anaconda can be considered as a subset of Dataiku DSS. While
Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
Read full review Saturn Cloud provides an R server, that's super important. Even you can write R on
CoLab with different settings, but it is inconvenient and slow. Saturn Cloud can give me a different IDE environment that I'm more used to, even if I'm using Python. Whereas
CoLab is more dedicated to Jupyter notebook
Read full review Return on Investment Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration. Platform also ease tracking of data processing workflow, unlike Excel. Build-in data visualizations covers many use cases with minimal customization; time saver. Read full review Faster experimentation and model iteration: Saturn Cloud's scalability and user-friendly interface can help organizations to reduce the time required to set up and run experiments, as well as to iterate on models more quickly. This can help to speed up the development cycle and get products to market more quickly. Increased productivity and efficiency: Saturn Cloud's built-in tools and pre-built environments can help to streamline data science workflows and reduce the time required to set up and configure environments. This can help data scientists to focus on higher-value tasks and improve overall productivity. Read full review ScreenShots