

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms.
The market is competitive, and Dataiku must adopt a consumption-based model instead of the current monthly model.
I consider the return on investment with Dataiku valuable because for us, it is one single platform where all our data scientists come together and work on any model building, so it is collaboration, plus having everything in one place, organized, having proper project management, and then built-in capabilities which help to facilitate model building.
In terms of ROI, the use of Dataiku simplifies the architecture of customers, which helps them to decommission some of their existing tools;
The enterprise subscription offers more benefits, ensuring valuable outcomes.
They should not take the complaints so lightly.
The support team does not provide adequate assistance.
Dataiku partners with local industry experts who understand the business better and provide support.
They provide callbacks to ensure clarity and resolution of any queries.
Dataiku is quite scalable, as long as I can pay for more licenses, there is no technical limitation.
As for stability and reliability, so far so good; after the installation, I really had no problems.
In terms of stabilization, if my data has no outlier creation in the raw data, then it is quite stable.
SAS Visual Analytics is stable and manages data effectively without crashing.
Someone who needs to do coding can do it, and someone who does not know coding can also build solutions.
Dataiku's pricing is very high, and commercial transparency is a challenge.
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.
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI.
I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies.
There are no extra expenses beyond the existing licensing cost.
The pricing for Dataiku is very high, which is its biggest downside.
It offers most of the capabilities required for data science, MLOps, and LLMOps.
I have used Dataiku's AutoML tools, and they definitely shorten the process; they have a lot of built-in intelligence which we can use, and they help to automate a lot of things.
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.
The ability to query information from our Excel data into SAS to view specific data is invaluable.
| Product | Market Share (%) |
|---|---|
| Dataiku | 8.0% |
| Databricks | 9.6% |
| KNIME Business Hub | 8.7% |
| Other | 73.7% |
| Product | Market Share (%) |
|---|---|
| SAS Visual Analytics | 2.1% |
| Tableau Enterprise | 11.3% |
| Qlik Sense | 5.6% |
| Other | 81.0% |

| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 2 |
| Large Enterprise | 9 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 8 |
| Large Enterprise | 19 |
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.
SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.
SAS Visual Analytics Features
SAS Visual Analytics has many valuable key features. Some of the most useful ones include:
SAS Visual Analytics Benefits
There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.
A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.
PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.
Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.