IBM Watson Studio and Dataiku are data science platforms with IBM Watson Studio known for its advanced AI integration and scalability, while Dataiku is favored for its collaborative environment and ease of use, enhancing team collaboration and data processing.
Features: IBM Watson Studio offers sophisticated machine learning and deep learning tools, collaboration features for seasoned data professionals, and seamless AI capability integration. Alternatively, Dataiku provides a user-friendly drag-and-drop interface, integration with various data sources, and powerful data connectors, suitable for technical and non-technical users.
Room for Improvement: IBM Watson Studio could enhance its user interface to cater to less technical users and improve cost efficiency. Dataiku could expand its AI feature set, increase scalability for larger enterprises, and incorporate more advanced coding options for expert users.
Ease of Deployment and Customer Service: IBM Watson Studio supports comprehensive cloud integration, backed by extensive customer resources and tailored solutions. Dataiku's straightforward deployment model and guided support ensure smooth integration for teams with diverse skill levels.
Pricing and ROI: IBM Watson Studio has a premium pricing structure reflecting its advanced capabilities, making it suitable for organizations needing deep AI functionality. Dataiku offers cost-effective solutions with a quick ROI, focusing on usability and efficient onboarding, ideal for businesses optimizing resource allocation.
The market is competitive, and Dataiku must adopt a consumption-based model instead of the current monthly model.
The product offers a significant return on investment through its scalability and integration capabilities.
My customers have seen returns on investment through increased efficiency, automated calculations, improved accuracy in pricing, and reduced staffing needs due to the automation.
Dataiku partners with local industry experts who understand the business better and provide support.
The support team does not provide adequate assistance.
The customer service team is helpful and responsive, more or less on time.
The support quality depends on the SLA or the contract terms.
The community access is weak, which limits the ability to engage in discussions and find documentation and examples of similar cases effectively.
Watson Studio is very scalable.
I rate IBM Watson Studio seven out of ten for scalability because while it scales, it requires significant resources to do so, making it expensive compared to some competitors.
In terms of stabilization, if my data has no outlier creation in the raw data, then it is quite stable.
Expertise in optimization is necessary to manage such issues effectively.
I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend it by developing and integrating custom components easily with existing ones.
Dataiku's pricing is very high, and commercial transparency is a challenge.
The license is very expensive.
IBM should work on optimizing the user interface and enhancing the product's accessibility for medium and small enterprises.
One area that could be improved is the backup and restoration of the database and the overall database configuration.
There are no extra expenses beyond the existing licensing cost.
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies.
The pricing for Dataiku is very high, which is its biggest downside.
IBM Watson Studio is considered rather expensive, with a rating of six or seven.
Dataiku primarily enhances the speed at which our customers can develop or train their machine learning models because it is a drag-and-drop platform.
This feature is useful because it simplifies tasks and eliminates the need for a data scientist.
It offers most of the capabilities required for data science, MLOps, and LLMOps.
This capability saves a significant amount of time by automating processes that typically involve manual work, such as data cleaning, feature engineering, and predictive analytics.
It integrates well with other platforms and offers good scalability.
| Product | Market Share (%) |
|---|---|
| Dataiku | 11.7% |
| IBM Watson Studio | 2.1% |
| Other | 86.2% |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 1 |
| Large Enterprise | 4 |
Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
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