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DataikuExternal reviews
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Data science for non data scientists
What do you like best about the product?
Very intuitive interface, easy to configure and build intelligent models with.
What do you dislike about the product?
It sometimes just doesn’t work when you are executing models.
What problems is the product solving and how is that benefiting you?
Improving marketplace approvals
Platform suitable for both - Advanced Data Scientists and Analysts as well as Beginners
What do you like best about the product?
The capability to use custom code besides its built-in features that help augment the outcome. Also, the timely response from its Customer Support to address questions and blockers is a huge plus.
What do you dislike about the product?
The use of inferred data-types in several of its built-in recipes - that may cause downstream issues when the original data type mismatches the inferred type.
What problems is the product solving and how is that benefiting you?
Custom coding in modular form augmented by its built-in features
Very organized and informative
What do you like best about the product?
Elastic and agnostic to supplemental technology.
What do you dislike about the product?
Dataiku is still not as well known in the technology sector.
What problems is the product solving and how is that benefiting you?
Predictive models and customer segmentation.
Great product with many flexibility and plug-ins
What do you like best about the product?
End-to-end platform: From data ingestion and preparation to model deployment and monitoring, Dataiku covers the entire lifecycle of a data project. This eliminates the need for disparate tools and streamlines the entire workflow.
Collaborative environment: The platform fosters seamless collaboration through shared projects, commenting, and version control. This ensures everyone is on the same page and contributes their unique expertise. My coworkers share their projects with each other and work together on some projects.
Extensive integrations: Dataiku integrates seamlessly with a wide range of databases, cloud platforms, and machine learning libraries. This flexibility allows us to leverage our existing infrastructure and resources. I just learned that a new R library was added recently which could make our life easier on data manipulation.
Robust model management: The platform provides comprehensive tools for tracking model performance, managing versions, and ensuring compliance. This is critical for maintaining the accuracy and reliability of our data-driven decisions.
Collaborative environment: The platform fosters seamless collaboration through shared projects, commenting, and version control. This ensures everyone is on the same page and contributes their unique expertise. My coworkers share their projects with each other and work together on some projects.
Extensive integrations: Dataiku integrates seamlessly with a wide range of databases, cloud platforms, and machine learning libraries. This flexibility allows us to leverage our existing infrastructure and resources. I just learned that a new R library was added recently which could make our life easier on data manipulation.
Robust model management: The platform provides comprehensive tools for tracking model performance, managing versions, and ensuring compliance. This is critical for maintaining the accuracy and reliability of our data-driven decisions.
What do you dislike about the product?
The running engine could be tricky, there is no one engine can run it all. Sometimes I have to try different engines to make it work.
What problems is the product solving and how is that benefiting you?
We have data lives in different platforms, such as Google Cloud BigQuery, Helix, Microsoft Excel etc. Our team need to get data from those different data sources and run the ETL process, manipulate the data and generate a single analytical data file for different uses. Dataiku can help use to achieve that goal by the visualized receipts.
Another problems is our team has different Data Science skillsets, such as Python and R. Each member created their piece of logic using their preferred coding language. We need to put all their pieces of logic together and generated a unified logic to generate an analytical dataset. We can use Dataiku as a single platform to incorporate Python and R codes together.
Another problems is our team has different Data Science skillsets, such as Python and R. Each member created their piece of logic using their preferred coding language. We need to put all their pieces of logic together and generated a unified logic to generate an analytical dataset. We can use Dataiku as a single platform to incorporate Python and R codes together.
An innovative approach to data analytics
What do you like best about the product?
The platform seems very user friendly. The data visualizations are easy to select and implement using the data.
What do you dislike about the product?
although it is user friendly for the beginner data analyst, it is clear that a basic or fundamental understanding of programming and data analytics is important for full benefit of the product.
What problems is the product solving and how is that benefiting you?
Text analysis from scanned documents and converting to data to be analyzed, predicting values given a set of conditions, creating data visualizations / dashboards
great analytics and data science tool!
What do you like best about the product?
The software is very easy to use and has great learning materials
What do you dislike about the product?
Some of the user interfaces are a bit unintuitive, but can quickly be learned.
What problems is the product solving and how is that benefiting you?
Exploratory analytics, streamlining workflows and automating manual efforts
A Complete and Intuitive Platform for Data Science Projects
What do you like best about the product?
Dataiku stands out for its ease of use — the drag-and-drop interface combined with the option to code when necessary makes it accessible to a wide range of users. Implementation was smooth and well-supported by the customer success team. I use Dataiku frequently because it offers a vast number of features, from data preparation to model deployment. Integration with other tools like databases, cloud services, and APIs is straightforward, making the platform even more powerful for end-to-end projects.
What do you dislike about the product?
While overall the platform is excellent, some advanced settings and options could be a bit overwhelming for new users. Additionally, the pricing structure can be a limiting factor for smaller companies or teams.
What problems is the product solving and how is that benefiting you?
Dataiku is helping to solve the complexity of managing the full data science workflow, from data ingestion and preparation to model development and deployment. It centralizes collaboration between data scientists, analysts, and business users, ensuring that projects move faster and with better governance. The platform also reduces dependency on purely manual coding, making advanced analytics more accessible. This is benefiting me by significantly increasing productivity, improving project visibility, and enabling faster decision-making based on reliable, well-structured data pipelines.
Great one-stop shop for all Data Science needs
What do you like best about the product?
The plethora of data plug-in sources, tons of options for ready-made recipes (for EDAs, data engineering, & quick-and-dirty analyses). Along with that, we have code-based recipes too to write our own codes. And cherry on top is the collaborative environment without us having to explicitly handle any of that!
What do you dislike about the product?
Wish there was more customization available to some of the visual recipes. Another thing is version control - although Dataiku does handle version control, it is very non-intuitive and difficult to go back to a previous version, or even understand the changes made between different versions. We need to have commit comments and other git-like features for that to work better.
What problems is the product solving and how is that benefiting you?
Dataiku is solving the biggest problem of providing us with computing bandwidth to develop, test, and deploy complex ML-models in a collaborative environment. It is providing us with an end-to-end solution for all our project related needs - right from bringing in data, cleaning and processing it, developing a model, deploying it, and even visualizing results.
On the GenAI front, my team and I have been able to spin out multiple pilots and MVPs because of Dataiku's Streamlit + VS Code integration - saving us critical time in deployment and integration ourselves.
On the GenAI front, my team and I have been able to spin out multiple pilots and MVPs because of Dataiku's Streamlit + VS Code integration - saving us critical time in deployment and integration ourselves.
Agentic AI
What do you like best about the product?
Great use cases of Agentic AI were demostrated
What do you dislike about the product?
Nothing I can think of, I liked everything about the conference
What problems is the product solving and how is that benefiting you?
Troubleshooting becomes a lot easier when you have a visual interface
It's automation feature makes repetitive tasks seem less painful
It's automation feature makes repetitive tasks seem less painful
Data for everyone
What do you like best about the product?
I love the web platform that decreases peoples adversity to getting to explore. I love the visual recipes to make it easier to see what happening
What do you dislike about the product?
Getting organized from project to prokect
What problems is the product solving and how is that benefiting you?
Providing solutions to my business
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