Dataiku for Enterprise AI
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Dataiku Streamlines End-to-End AI at Scale with Intuitive, Collaborative Workflows
What do you like best about the product?
Dataiku streamlines building, training, and deploying AI models at scale, offering end-to-end automation, seamless orchestration of compute resources, and collaborative pipelines that make generative AI projects faster and more reliable. It unifies the entire data workflow from preparation and analysis to model deployment, into a single, collaborative platform that’s surprisingly intuitive for both data scientists and business users.
What do you dislike about the product?
Full capabilities can be overwhelming for new users, and scaling extremely large generative AI models sometimes requires complex customization.
What problems is the product solving and how is that benefiting you?
Dataiku solves the problem of fragmented AI workflows by unifying data preparation, model training, and deployment in a single platform. This benefits me by accelerating generative AI projects, reducing infrastructure complexity, and enabling seamless collaboration across data engineers, scientists, and business teams. It ensures models are production-ready faster while maintaining scalability and reliability.
Centralized, Organized Data Platform with Powerful AutoML and Integrations
What do you like best about the product?
Dataiku demonstrates a satisfactory environment where data is centralized and organized
The program supports both coders and non coders, allowing them to use data in their different levels
Dataiku has a successful data lifecycle, something that collects, ingest, prepare and even analyze data
The program consists of an inbuilt Auto ML tools that speed u most of the operations
Dataiku has extensible APIs and plugins, all supporting success integrations
The program supports both coders and non coders, allowing them to use data in their different levels
Dataiku has a successful data lifecycle, something that collects, ingest, prepare and even analyze data
The program consists of an inbuilt Auto ML tools that speed u most of the operations
Dataiku has extensible APIs and plugins, all supporting success integrations
What do you dislike about the product?
Dataiku has challenges in cost management and estimating, where small companies fail to secure the app
The app demands extensive computer resources, something that amplifies the infrastructure costs
The app demands extensive computer resources, something that amplifies the infrastructure costs
What problems is the product solving and how is that benefiting you?
Dataiku ensure solid data collaboration, where analysts, engineers and even business players access data in a centralized environment
Most of complex data workflows are significantly supported by this app, ensuring that no manual code needed to conduct a specific task
The presence of machine learning and AI support s the effectiveness of data processing and analysis
The app accommodates both technical and non technical users due to it’s effectiveness and simplicity
Most of complex data workflows are significantly supported by this app, ensuring that no manual code needed to conduct a specific task
The presence of machine learning and AI support s the effectiveness of data processing and analysis
The app accommodates both technical and non technical users due to it’s effectiveness and simplicity
A Unified Platform That Bridges Data Experts and Business Teams Seamlessly
What do you like best about the product?
Its greatest strength is enabling true collaboration between data experts and business teams on a single platform. It seamlessly bridges technical work like coding and ML engineering with visual and no-code interfaces. This breaks down silos, accelerates project delivery and ensures AI solutions are built with crucial business context, making them more impactful and sustainable.
What do you dislike about the product?
For smaller teams or simpler projects, Dataiku will be premium. The platform's extensive features come with inherent complexity, which can lead to a steeper learning curve. Its pricing model is often seen as enterprise-focused, potentially making it less accessible for startups or individual users who don't need its full collaborative scale.
What problems is the product solving and how is that benefiting you?
Dataiku solves the critical challenges of fragmented data science workflows. It provides a unified, collaborative platform that connects data preparation, experimentation and deployment into one governed environment. This directly benefits us by drastically reducing project lead times, improving model governance and reproducibility and enabling both technical and business users to contribute effectively to data-driven outcomes.
End-to-End Data Science Platform That Makes Collaboration Easy
What do you like best about the product?
What I like best about Dataiku is its end-to-end data science and machine learning platform that brings data preparation, analysis, model building, and deployment into a single environment. The visual workflows combined with code-based options make it accessible for both technical and non-technical users. It also supports strong collaboration between data scientists, analysts, and business teams, which helps speed up model development and improve decision-making.
What do you dislike about the product?
While Dataiku is a powerful platform, it can feel complex for first-time users because of its extensive feature set. The initial setup and learning curve may take time, especially for non-technical users. In some cases, performance can slow down when handling very large datasets, and the pricing structure may not be ideal for smaller teams or limited use cases.
What problems is the product solving and how is that benefiting you?
It's solves the challenge of managing the entire data science and machine learning lifecycle in one platform. It brings together data preparation, analysis, model development, deployment, and monitoring, reducing the need for multiple disconnected tools. This benefits me by improving collaboration between teams, speeding up model development, and making it easier to turn data into actionable insights while maintaining consistency and governance across projects.
Effortless Data Collaboration with Robust Features
What do you like best about the product?
I like that Dataiku lets me handle data projects and build machine learning models by pulling in data from different sources, cleaning and organizing it, and experimenting with models all in one place. The combination of a visual interface with coding options makes it accessible for both technical and non-technical team members, smoothing out data project management. I love how it reduces repetitive tasks, decreases mistakes, and keeps complex projects organized and running smoothly. It's great that everyone on the team can contribute, no matter their technical skills, making data work easier and less stressful.
What do you dislike about the product?
One thing I’ve noticed about Dataiku is that it can feel a bit overwhelming at first because there are so many features and options. Working with really large datasets or complex workflows can sometimes be a little slow. I also think it could be a bit easier for new users to get started. Overall, it’s a great tool, but a little more guidance and smoother performance would make it even better.
What problems is the product solving and how is that benefiting you?
I use Dataiku to streamline data projects by integrating data sources, cleaning data, and building models in one platform. It allows team collaboration regardless of technical skills, saves time on repetitive tasks, reduces mistakes, and keeps complex projects organized.
Intuitive Visual Interface, Powerful pipelines, but Needs Better History Management
What do you like best about the product?
I really appreciate how the graphical user interface handles paths and threads. It allows you to manage all your code and datasets visually, and everything is automatically aligned, which makes the experience very soothing to use.
What do you dislike about the product?
There isn't anything in particular that I dislike about Dataiku. However, one area for improvement would be better management of the history and recent code I've worked on. It would be helpful if this information were more easily accessible and visually highlighted.
What problems is the product solving and how is that benefiting you?
Managing large datasets was my primary challenge. Having access to a unified portal for both geospatial and other data, along with the required processing power, has been crucial for achieving my objectives as a data scientist. The ability to test various machine learning models in one shot is simply revolutionary. I cannot imagine ever going back to working on my PC for these tasks.
Dataiku : Making your Data Science work easy
What do you like best about the product?
I find the platform very easy to use, which makes it great for quickly prototyping and getting your MVP out as soon as possible. It's also simple to plug and play, which really speeds up the process.
What do you dislike about the product?
I find the documentation somewhat incomplete, with few tutorials available. It can be a struggle to find solutions when I need help.
What problems is the product solving and how is that benefiting you?
Both MVP and end-to-end approaches allow for rapid use case development, but when it comes to building large-scale, scalable solutions with real impact, the process can be more challenging.
Dataiku review
What do you like best about the product?
I like that its basically ran by Ai and you don't have to do a whole lot
What do you dislike about the product?
Nothing its a great app maybe a little costly but worth it
What problems is the product solving and how is that benefiting you?
It solved my issue with keeping track of all my paperwork it does it all for me
Dataiku for Data Science/AI projects
What do you like best about the product?
SImple to use & scale. Flexibity & integrated well into the any infra.
What do you dislike about the product?
The main drawbacks of Dataiku is cost, scalability limitations, integration complexity, performance issues, and the need for user training.
What problems is the product solving and how is that benefiting you?
Dataiku addressed critical issues in data quality, operational efficiency, analytics collaboration, AI scalability, compliance, and business-user empowerment, serving as a unified platform for enterprise data innovation and value generationtion.
A Powerful Platform for End-to-End Data Science & Collaboration
What do you like best about the product?
Dataiku is excellent for managing the entire data pipeline from data preparation to machine learning and deployment. The best part is it easy to implement. The best part is how it allows both technical and non-technical users to collaborate on the same platform. Visual workflows make it easy to build projects without heavy coding, while advanced users can still dive deep with Python, R, or SQL. The integration with cloud platforms and version control is also very smooth.
What do you dislike about the product?
The platform can feel heavy for smaller projects, and the initial learning curve is a bit steep for beginners. Also, the licensing costs can be high for small companies or startups.
What problems is the product solving and how is that benefiting you?
For me, Dataiku mainly solves the problem of collaboration between technical and non-technical teams. Earlier, a lot of time used to get wasted when data scientists, analysts, and business teams worked separately and had to constantly exchange files and reports. With Dataiku, we can all work on the same platform data cleaning, model building, and visualization happen in one place. It also saves me from doing repetitive manual tasks since a lot of workflows can be automated. Overall, it has made our data projects faster, more transparent, and easier to manage.
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