--- title: Dataiku Reviews meta_title: 'Dataiku Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 224 reviews by the users' company size, role or industry to find out how Dataiku works for a business like yours. aggregate_rating: rating_value: 4.4 review_count: 224 scale: '5' date_modified: '2026-08-10' parent_category: name: Generative AI url: https://www.g2.com/categories/generative-ai --- # Dataiku Reviews **Vendor:** Dataiku **Category:** [Generative AI Infrastructure Software](https://www.g2.com/categories/generative-ai-infrastructure) **Average Rating:** 4.4/5.0 **Total Reviews:** 224 ## About Dataiku Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI. Governance is part of the build rather than something bolted on afterward, so teams ship faster while keeping performance, cost, and risk under control. The result: AI that moves from experimentation to trusted, measurable execution now, not in 18 months. ## Dataiku Pros & Cons **What users like:** - Users appreciate how Dataiku facilitates **easy ML development** , allowing focus on building models without the complexity. (80 reviews) - Users love the **ease of use** in Dataiku, simplifying complex tasks and enhancing their data analysis experience. (79 reviews) - Users appreciate the **ease of usability** in Dataiku, enabling collaboration for both technical and non-technical users. (45 reviews) - Users appreciate the **easy integrations** of Dataiku, facilitating smooth collaboration and deployment across various analytics tools. (43 reviews) - Users benefit from the **productivity improvement** of Dataiku, enabling faster project development and enhanced career growth. (41 reviews) - Collaboration (40 reviews) - Users value the **wide range of integrations** in Dataiku, facilitating collaboration and diverse analytics capabilities. (40 reviews) - Performance (40 reviews) - Data Visualization (38 reviews) - Time-Saving (38 reviews) **What users dislike:** - Users find the **steep learning curve** of Dataiku challenging, making it tough for beginners to master the platform. (43 reviews) - Users find the **steep learning curve** challenging for beginners, impacting their ability to effectively use Dataiku. (25 reviews) - Users find the **difficult learning** curve challenging, particularly for beginners navigating advanced features. (23 reviews) - Users experience **slow performance** with Dataiku when handling large datasets, affecting efficiency and productivity. (23 reviews) - Users find Dataiku **expensive** , especially for smaller organizations and projects, impacting accessibility and affordability. (22 reviews) - Complexity (20 reviews) - Users find the **complexity issues** in Dataiku's tools and documentation can hinder their overall experience. (19 reviews) - Users face **performance issues** that disrupt workflow, complicate data preparation, and limit access to plugins for testing. (18 reviews) - Data Management Issues (14 reviews) - Missing Features (14 reviews) ## Dataiku Reviews ### 1. User-Friendly and Well-Integrated, but Data Prep and ML Training Can Be Inconsistent **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Airlines/Aviation | Enterprise (> 1000 emp.) **Reviewed Date:** July 01, 2026 **What do you like best about Dataiku?** It’s very user-friendly. New members of our team can quickly get started, whether they’re picking up pre-existing projects or creating their own. I also really like that you can mix different coding languages within the same flow. Another strong point for me is the range of integrations with most major platforms: Databricks, AWS, Teradata, SharePoint, etc. Performance-wise, it’s good. It’s not the best, although that may be related to our current cluster configuration. I’ve also noticed that training ML models can sometimes fail for different reasons, and it can be a bit daunting to figure out exactly why and debug the issue. Dataiku support is quite good. I wasn’t a fan of customer support being limited to email, but I have to say the responses are fast and the attention has been solid. Pricing is also quite competitive. Fixed pricing tied to licenses works well for our team. Finally, I’ve been enjoying the latest AI features they’ve added. Being able to easily describe recipes or generate documentation is definitely a plus. **What do you dislike about Dataiku?** Data prep tools can sometimes be too slow to run, which can be frustrating. This is a problem we haven’t seen with competitors like Alteryx. Also, training ML models sometimes fails even with a reasonable number of samples, and the behavior feels a bit inconsistent in that regard. **What problems is Dataiku solving and how is that benefiting you?** I mostly work on ML projects—forecasting, classifiers, and similar tasks—especially when they’re tied to commercial problems. It's also pretty decent at version control amongst the team. ### 2. Great for Automating Data Workflows, Looking Forward to Gen AI Integration **Rating:** 3.5/5.0 stars **Reviewed by:** Meghu D. | Manager, Quantitative Analytics & Monitoring, Enterprise (> 1000 emp.) **Reviewed Date:** June 25, 2026 **What do you like best about Dataiku?** As a data analyst, it makes it easier to automate repetitive data processes and workflows. I also like the visual recipes/workflows. But I am looking forward to all the upcoming features as mentioned in the enablement session. **What do you dislike about Dataiku?** A couple of downsides I’ve noticed with Dataiku are the lack of Gen AI integration. I understand it will be added soon, and I’m looking forward to that, but it’s still a gap for now. **What problems is Dataiku solving and how is that benefiting you?** As someone who works at a bank, a lot of my analysis involves financial data, especially in fraud management. Dataiku helps me work through and analyze fraud-related data, including calculating the impact and benefits of our data science models. ### 3. Intuitive and Effective with Some Challenge in Speed **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Airlines/Aviation | Enterprise (> 1000 emp.) **Reviewed Date:** June 25, 2026 **What do you like best about Dataiku?** I like how intuitive Dataiku is, how easy it is to learn to use, and the fluidity of the software. It makes pipelines much more understandable, facilitating their creation and maintenance. I also like that the changes I make mostly propagate throughout the flow; for example, if I change the name of a table, the recipe that uses it updates automatically. Additionally, if I connect a table somewhere else in the flow, the flow adjusts automatically to maintain a certain order. **What do you dislike about Dataiku?** I think the speed. Many times I have to wait a long time for a simple recipe to even start executing. **What problems is Dataiku solving and how is that benefiting you?** Dataiku makes it easy to create and maintain pipelines, making them more understandable. It is intuitive and allows automatic changes in the flow, which improves organization. ### 4. Flexible AI Platform with Stellar UI, Needs Better Visualization and Deployment Support **Rating:** 4.0/5.0 stars **Reviewed by:** Xiaoguang D. | Principal Adviser Data Science | Senior RioExpert, Small-Business (50 or fewer emp.) **Reviewed Date:** April 13, 2026 **What do you like best about Dataiku?** I think the user interface of Dataiku is very user-friendly. Even if you don't have a strong data science or data engineering background, you can still use it by drawing boxes, which makes it accessible for many people. I also like that you can customize your solutions by writing your own code to cater to specific business needs. Additionally, with its fast-paced development, Dataiku regularly updates and upgrades the system to include the latest AI features, which I find awesome. The graphical, no-code environment significantly reduces my development life cycle, saving at least 50% of my time. It also makes interaction with end users easy because they can access our development environment to see progress and give quick feedback. **What do you dislike about Dataiku?** So first of all, I think I got some limitation that you to be honest with you, because let's say, if you want to display and visualize a large dataset, it always has some limitation. And, also, I find out the dashboard in built by the API is not super fancy and super user friendly. Comparing to Power BI or the other visualization tools like Tableau, I think that's something that you can improve as well. Other main pinpoint for us is about the deployment. Because, you need to link to the different development, the requirements, how to deploy our AI solution, particularly to another cloud form. For example, AWS Azure, I think that we need a little bit more support on this. **What problems is Dataiku solving and how is that benefiting you?** Dataiku helps me build AI solutions like multi-agent systems, handling both test images and numerical data. It significantly reduces my development life cycle by 50% and enhances collaboration by allowing quick user feedback, leading to faster project iterations. ### 5. Streamlined Data Transformation with Ease **Rating:** 4.0/5.0 stars **Reviewed by:** Khalid S. | Enterprise Data Architect, Enterprise (> 1000 emp.) **Reviewed Date:** June 01, 2026 **What do you like best about Dataiku?** I like how Dataiku helps us identify some data quality issues and correct them before presentation. It's really important because, without data quality, the data is almost worthless, and you can't really make any insight out of it if it's not good quality. I also found the setup process to be very easy. We integrated with our intra authentication system, set up connections to Snowflake, and then started working on it. **What do you dislike about Dataiku?** It's the ability to actually be able to extract data, look at it, evaluate, transform it, and present it. **What problems is Dataiku solving and how is that benefiting you?** I use Dataiku for data transformation, making it easy to manipulate and present data. It helps us identify and correct data quality issues before presentation. ### 6. Powerful Governance, Needs Better UI Integration **Rating:** 4.0/5.0 stars **Reviewed by:** Samridhi G. | Cybersecurity Specialist, Enterprise (> 1000 emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Dataiku?** I really like the Orchestrator level, as it helps with my tasks. The UI is another aspect that I find valuable, especially for various use cases. Dataiku is also helpful in AI governance, agent traces, and token aspects. Additionally, I appreciate the model evaluation and prompt monitoring features, which make my workflow more efficient. **What do you dislike about Dataiku?** The UI can be improved with more integration. **What problems is Dataiku solving and how is that benefiting you?** I use Dataiku for AI governance, agent traces, model evaluation, and prompt monitoring. It's great for orchestrator-level tasks, but the UI could be improved with more integration. ### 7. Easy Low-Code Workflow Creation That Just Works **Rating:** 4.0/5.0 stars **Reviewed by:** Brad S. | Business Intelligence Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** June 18, 2026 **What do you like best about Dataiku?** The low code environment and workflow creation plus ease of use **What do you dislike about Dataiku?** There nothing o can think of that I dislike **What problems is Dataiku solving and how is that benefiting you?** Dataiku has helped us reduce the dependency on technical teams for analytics and data preparation. Business users can access, prepare, and analyze data more efficiently, which has accelerated decision-making and improved collaboration across departments. The platform’s governance, automation, and AI capabilities have also helped us scale data initiatives while maintaining consistency and control. ### 8. Intuitive Visual Interface, Powerful pipelines, but Needs Better History Management **Rating:** 4.0/5.0 stars **Reviewed by:** Akshay B. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** October 14, 2025 **What do you like best about Dataiku?** 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 Dataiku?** 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 Dataiku 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. ### 9. Visually Appealing Low-Code Platform with Easy Cross-Team Collaboration **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Airlines/Aviation | Enterprise (> 1000 emp.) **Reviewed Date:** June 25, 2026 **What do you like best about Dataiku?** low-code option that is visually appealing that has easy collaboration between various teams of different technical levels **What do you dislike about Dataiku?** it takes a while to get used to the UI and find due to some auto documentation can be misleading **What problems is Dataiku solving and how is that benefiting you?** Dataiku was a possible solution for our analytics migration out of Alteryx ### 10. Visual Flow Ease, Coding Pilot Needs Work **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User **Reviewed Date:** June 17, 2026 **What do you like best about Dataiku?** I really like probably seeing the flow visually with Dataiku. It's helpful having the visual recipes too if I don't wanna write code. **What do you dislike about Dataiku?** The coding pilot doesn't work for me. I don't know if that's just a Boeing restriction that we don't have it activated. So I have to go to a third party AI tool if I wanna use the coding agent. **What problems is Dataiku solving and how is that benefiting you?** I use Dataiku to build a part recommender pipeline, and it solves the problem of explaining the code easily to customers because of its visual flow. ### 11. Single Pane of Glass for Data & AI Agents with Built-In Observability **Rating:** 4.0/5.0 stars **Reviewed by:** Chandrakanth K. | Lead Advanced Data Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** June 18, 2026 **What do you like best about Dataiku?** Having a single pane of glass for data and AI agents, with built-in observability, makes it much easier to monitor everything in one place. **What do you dislike about Dataiku?** It could be an overhead to maintain, especially if the customer is already migrating to Databricks. **What problems is Dataiku solving and how is that benefiting you?** We haven’t had the chance to explore the use cases yet. ### 12. User-Friendly Interface, Needs Better Handling of Unstructured Data **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User | Small-Business (50 or fewer emp.) **Reviewed Date:** June 16, 2026 **What do you like best about Dataiku?** I appreciate Dataiku for its interface and ease of use, making the initial setup very easy. I also found the low code data pipeline setup beneficial when I used it in my past job. **What do you dislike about Dataiku?** Customized pipelines or use cases, like dealing with semi-structured or unstructured data, are hard to tackle. **What problems is Dataiku solving and how is that benefiting you?** I appreciated Dataiku for its low code data pipeline setup and ease of use, though dealing with semi-structured or unstructured data could be improved. ### 13. Powerful Dataiku Integrations, Though I Haven’t Used It Yet **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Banking | Small-Business (50 or fewer emp.) **Reviewed Date:** April 14, 2026 **What do you like best about Dataiku?** All the integrations you can add in Dataiku are really powerful. **What do you dislike about Dataiku?** Im not a user but i have an interest in dataiku **What problems is Dataiku solving and how is that benefiting you?** As a data scientist, I feel the next update in June 2026 would transform my job and make it much easier and more efficient, especially for doing PoCs. ### 14. Dataiku : Making your Data Science work easy **Rating:** 4.0/5.0 stars **Reviewed by:** palbha n. | Data Science Specialist, Enterprise (> 1000 emp.) **Reviewed Date:** October 03, 2025 **What do you like best about Dataiku?** 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 Dataiku?** 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 Dataiku 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. ### 15. Great Informaion. Gave me Perspectives on IA and how use by real companies **Rating:** 4.0/5.0 stars **Reviewed by:** Kevin F. | Website Admin and AI Expert, Small-Business (50 or fewer emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** What I liked most about the Dataiku AI Conference was how down-to-earth it all felt, even with all the high-tech talk. They made big ideas like Generative AI and machine learning easy to understand and actually useful for real businesses. The hands-on demos were solid, and you could tell they put thought into making sure folks from all walks of life felt welcome. It wasn’t just smart—it was practical, and that’s what really stuck with me. **What do you dislike about Dataiku?** One thing they could do better is cut down a bit on the buzzwords and tech lingo—sometimes it felt like they were talking to a room full of data scientists only. It’d be great if they offered more sessions geared toward small business folks or hands-on pros who want to use AI without needing a PhD. Also, a few more real-world case studies from regular companies—not just the big guys—would help show how this stuff works in the everyday world. Keep it smart, but make it more relatable. **What problems is Dataiku solving and how is that benefiting you?** The real estate model was very impressive. makes me think of what could be possible for me. ### 16. Informational and Exciting Experience **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Manufacturing | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Dataiku offers a multitude of benefits that make it an invaluable tool for organizations looking to leverage their data effectively. My favorite things is that its collaborative environment, which fosters teamwork among data scientists, analysts, and business users, enabling them to share insights and work together seamlessly. **What do you dislike about Dataiku?** A couple of things that I dislike about Dataiku, specifically within my organization is that we have had many unannounced errors arise. We could have a flow working for a lengthy period of time then one day it no longer works due to an error. These random errors can stop normal daily tasks to have to investigate errors that were not originally an issue. **What problems is Dataiku solving and how is that benefiting you?** Dataiku has allowed for me to take large forms of data and conduct calculations as well as summarize to use in business each day. Dataiku also allows for me to take this data and add even more information to be able to calculate forecasts and future possible outcomes. ### 17. Great tool for performing Everyday Data Science & AI **Rating:** 4.0/5.0 stars **Reviewed by:** Tirth S. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** The features and capabilities of the Dataiku. I find Dataiku as a one stop shop for doing everyday analytics, data science and AI. **What do you dislike about Dataiku?** The infrastructure setup to host Dataiku stack on-premise was very painful. It took over 2 months just to setup the infrastructure to get Dataiku running on our cloud. **What problems is Dataiku solving and how is that benefiting you?** 1) It provides access to some of the most challenging to implement ML algorithms with just a click. 2) Helps fast track our journey through Data Science and ML use cases. 3) The low code and no code capabilities helps non programmers to get started with ML development and deployment quickly and efficiently. ### 18. The closest thing to end-to-end data analytics available. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Manufacturing | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Dataiku combines the best features on data exploration, data pipelines, Dev Ops, data visualization, web apps development, machine learning, and generative AI. They are always adding new features, and they are constantly taking feedback and requests from the development community for new features. **What do you dislike about Dataiku?** There can be some translation issues with the terminology used in the product. I would also like to see a semantic layer feature instead of every transformation step writing a new table **What problems is Dataiku solving and how is that benefiting you?** Dataiku allows me to move from prototype to production quickly. During problem solving sessions, I can pull in data from many different sources to analyze and create a report or dashboard to monitor the situation without leaving the tool. ### 19. Reduction of time to value **Rating:** 3.5/5.0 stars **Reviewed by:** Logan S. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Visual layout makes data transformation more clear. Built in tools speed up development time in particular with tools like the LLM recipes and ML model "battle" **What do you dislike about Dataiku?** I have noticed inconsistencies with how code is executed in a python notebook vs a python recipe. Sometimes that works in a recipe doesn't work in a notebook. Refusal to add global dark mode. **What problems is Dataiku solving and how is that benefiting you?** Simplifying the use and deployment of LLM projects in friendly interface. **Official Response from Taylor MECHAM:** > We're glad to hear that you find the visual layout and built-in tools helpful for data transformation and improved development time. We appreciate your feedback about the inconsistencies with code execution between Python notebooks and recipes—we'll share this with our team for further review and improvement. ### 20. Accelerating Data Workflows with Dataiku **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Commercial Real Estate | Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** It strikes a good balance between no-code workflows and also helps integrate code when required. It's a visual tool that handles the whole lifecycle of the data, it has the visual workflow style of KNIME and FME with the depth and flexibility of custom coding and cloud-based architecture. Great customer support by the way! It's also an intuitive platform to have new users onboarded on. **What do you dislike about Dataiku?** Performance can lag with large datasets, and partitioning isn't intuitive. Version controlling is great, but the roll back does not always work as intended especially within the coding environments. **What problems is Dataiku solving and how is that benefiting you?** Collaboration, versioning and non-local infrastructure. Those were the major pain-points that Dataiku alleviated. ### 21. Functionality **Rating:** 3.5/5.0 stars **Reviewed by:** Stacey Leveille-Casseus S. | Ecommerce Specialist, Small-Business (50 or fewer emp.) **Reviewed Date:** August 20, 2025 **What do you like best about Dataiku?** Strong version control, shared projects, and role-based access enhance teamwork across data and business teams **What do you dislike about Dataiku?** Some powerful capabilities are only available in higher-tier or enterprise versions, which may not be cost-effective for smaller teams **What problems is Dataiku solving and how is that benefiting you?** Covers the full data lifecycle: ingestion, preparation, modeling, deployment, and monitoring ### 22. Dataiku is a great low-code solution **Rating:** 4.0/5.0 stars **Reviewed by:** Josh B. | Sr Principal Analyst, People Analytics and Employee Experience, Enterprise (> 1000 emp.) **Reviewed Date:** April 17, 2025 **What do you like best about Dataiku?** I like how Dataiku supports low-code operations, but we can also create custom code in the environment and share it easily within our group. **What do you dislike about Dataiku?** Knowledge transfer for use of PromptStudio was a bit of a lift. The UI is a little less intuitive than other parts of Datiku **What problems is Dataiku solving and how is that benefiting you?** We have been using PromptStudio to test prompt ins multiple LLMs. Dataiku streamlines and simplifies this process once it is setup ### 23. Rapid AI with DataIku **Rating:** 4.0/5.0 stars **Reviewed by:** John W. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** March 14, 2025 **What do you like best about Dataiku?** DataIku allows me to quickly train and evaluate multiple models on given data. The results immediately reveal dominant features. This allows me to better understand the data that I'm dealing with. DataIku accepts many data formats and sources. **What do you dislike about Dataiku?** In DataIku, Chart styling is not as intuitive as I'd expect. Feedback loops are not allowed/implemented. DataIku does not allow CTEs in sql queries, which has consequential unwanted data processing. **What problems is Dataiku solving and how is that benefiting you?** DataIku speeds up my selection of AI strategies and dominant feature discovery. ### 24. We work closely with dataiku with our data scientist in ou AI Factory **Rating:** 4.0/5.0 stars **Reviewed by:** agnes m. | Data Architect, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Things are easy, it boosts productivity and honestly it hasn't been this easy building with ai anywhere else **What do you dislike about Dataiku?** I don't think i have any remark for now it is very hands on with the new topics so i am fine for now **What problems is Dataiku solving and how is that benefiting you?** we use it for many usecase integrating ai in the bank ### 25. Review of dataiku as a developer **Rating:** 3.5/5.0 stars **Reviewed by:** melika v. | Data Scientist- Advanced AI and Analytics, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Bringing everything into one place, from data to model development and deployment. **What do you dislike about Dataiku?** Clusters shutting down for no reason, not that much stability in connections and the time it takes to add a library to a template cluster and rebuilding it. **What problems is Dataiku solving and how is that benefiting you?** It is benefiting prototyping an app and delivering it to clients ### 26. Very user friendly **Rating:** 4.0/5.0 stars **Reviewed by:** Pratik M. | Data Strategy, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** I think super friendly. And best part about it it’s all in one. You do not have to navigate to multiple applications to from building the model or creating a flow. **What do you dislike about Dataiku?** So far I don’t have any complaints about Dataiku it’s working fine for me. **What problems is Dataiku solving and how is that benefiting you?** It’s providing me a platform where I perform all the data curation as well as analysis of data in single platform. And provide insights to stakeholders. ### 27. Great Orchastation tool **Rating:** 3.5/5.0 stars **Reviewed by:** Arpan N. | Data Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** It is a great tool to use as a data analyst. Great to track data from different sources in a single place **What do you dislike about Dataiku?** Will need more comprehensive material to train new programmers **What problems is Dataiku solving and how is that benefiting you?** We are doing a poc to build a agent to help service center executived of one only our insurance client on different products they offer. Dataiku is being used as pri.arh platform to do the poc **Official Response from Taylor MECHAM:** > Thank you for sharing your experience with Dataiku. We're glad to hear your Data Analysts find value in our Platform! We understand the importance of comprehensive training materials and will take your feedback into consideration for future improvements. ### 28. Good tool for ai and gen ai llm but not etl and enginer **Rating:** 3.5/5.0 stars **Reviewed by:** Nícolas S. | Senior Data Engineer | Ouribank, Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Gen ai possibilities, llm mesh possibilities and the ai stuf **What do you dislike about Dataiku?** ETL and Data Engenireering part, specifically with big data **What problems is Dataiku solving and how is that benefiting you?** ETL Problems **Official Response from Taylor MECHAM:** > We're happy to hear that Dataiku's AI and Generative AI capabilities are beneficial to you. We understand that the ETL and data engineering aspects may not fully meet your needs, and we appreciate your feedback as we continue to enhance our platform. ### 29. Company with good use cases to support for AI **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Banking | Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Great AI shop for getting to learn about AI and get up to speed on integrating AI in your tech space. **What do you dislike about Dataiku?** Currently could not come across anything which could be disliked. **What problems is Dataiku solving and how is that benefiting you?** We are still in the early stages of integrating AI in the workplace. Dataiku is helping in understanding the different use cases in the IT space ### 30. A comprehensive/complete tool for data science **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Chemicals | Enterprise (> 1000 emp.) **Reviewed Date:** April 03, 2025 **What do you like best about Dataiku?** versatility: visual, low code, API integration (wiki, dashboards, flow, models) connectivity (Databricks) ease of use for basic applications immediate support **What do you dislike about Dataiku?** quite expensive subscription limitations in flow output (images) steep learning curve for specific projects **What problems is Dataiku solving and how is that benefiting you?** Creation Machine learning models for feature analysis and predictions Time series analysis and modeling easy implementation (hyperparameter, comparison models, visualizations) dokumentation (wiki) visibility/visualization via flow ### 31. Dataiku user **Rating:** 4.0/5.0 stars **Reviewed by:** Yaseen B. | VP, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** It’s for beginner to someone who has been in the It industry for several year. The AI features and what we really value and they know what their customers want. **What do you dislike about Dataiku?** The ease of use and the feature rich interface. **What problems is Dataiku solving and how is that benefiting you?** Data wrangling and ML operations. ### 32. Dataiku creates the big picture overview you need for your data projects **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Real Estate | Mid-Market (51-1000 emp.) **Reviewed Date:** April 04, 2025 **What do you like best about Dataiku?** I can step into a project with relative limited knowledge, but because of the flow overview I immediately have rough idea what is going on. This is very valuable and makes it easy for different team members to work on a project. **What do you dislike about Dataiku?** Sometimes proprietory code has to written because you work in Dataiku. But overall this is quite limited. **What problems is Dataiku solving and how is that benefiting you?** We solve Real Estate analysis problems using AI. The setup with Dataiku is helpful because not everyone is very tech savy, and the non-code options make the platform accessible to everyone. ### 33. Dataiku great data science platform **Rating:** 3.5/5.0 stars **Reviewed by:** Savita M. | Administrator, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Dataiku is very user friendly low code/no code platform for AI/ML capabilities **What do you dislike about Dataiku?** More infrastructure compatibility and Flexibility in integrations **What problems is Dataiku solving and how is that benefiting you?** It has really made users to be able to build low code quick prototypes for testing very easy and accessible. ### 34. An innovative approach to data analytics **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Insurance | Mid-Market (51-1000 emp.) **Reviewed Date:** April 25, 2025 **What do you like best about Dataiku?** The platform seems very user friendly. The data visualizations are easy to select and implement using the data. **What do you dislike about Dataiku?** 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 Dataiku 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 **Official Response from Taylor MECHAM:** > Thank you for sharing your feedback on Dataiku! We're glad to hear that you find the platform user-friendly and appreciate the ease of data visualizations. We understand your concern about the need for basic programming and data analytics knowledge for full utilization of the product. We continuously work on improving our resources and support to assist users at all levels of expertise. If you or your team need any assistance or guidance on enhancing your skills with Dataiku, please feel free to reach out. We're here to help! ### 35. Great Product With Tons of Potential **Rating:** 3.5/5.0 stars **Reviewed by:** Maximus P. | Financial Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** I like the ability to easily view data in numerous ways. **What do you dislike about Dataiku?** Dataiku makes frequent updates that can sometimes cause issues to existing workflows. **What problems is Dataiku solving and how is that benefiting you?** It helps to quickly and effectively transform data into useful reports and end uses. ### 36. Great product **Rating:** 4.0/5.0 stars **Reviewed by:** Alice B. | Intern, Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Extremely easy to use and cheap, excellent customer support **What do you dislike about Dataiku?** Difficulty in scalability of the data and feature integration **What problems is Dataiku solving and how is that benefiting you?** Accelerating our AI use cases and their solutions can be easily tailored to the different industries of our clients ### 37. One-stop shop for all analytics and ML needs **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** I love how Dataiku allows for such seamless creation and implementation of ML models. It offers the ability to seamlessly collaborate and integrate with workflow with colleagues. **What do you dislike about Dataiku?** Dataiku has a decent learning curve if you are coming from a non-technical background. **What problems is Dataiku solving and how is that benefiting you?** Dataiku is allowing me to solve data analytics problems that maybe take a few minutes in Python in mere seconds. It saves me a considerable amount of time in the long run. ### 38. Platform suitable for both - Advanced Data Scientists and Analysts as well as Beginners **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Pharmaceuticals | Enterprise (> 1000 emp.) **Reviewed Date:** April 28, 2025 **What do you like best about Dataiku?** 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 Dataiku?** 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 Dataiku solving and how is that benefiting you?** Custom coding in modular form augmented by its built-in features **Official Response from Taylor MECHAM:** > Thank you for sharing your feedback about Dataiku! We're thrilled to hear that you appreciate the flexibility of using custom code alongside our built-in features and that our Customer Support team has been responsive in addressing your questions. We understand your concern about the inferred data types in some built-in recipes and the potential downstream issues it may cause. We will certainly take this feedback into consideration for future improvements. It's great to hear that Dataiku is helping you with custom coding in a modular form. If you have any further questions or need assistance, please don't hesitate to reach out. We're here to help! ### 39. Ease to use tool **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Semiconductors | Enterprise (> 1000 emp.) **Reviewed Date:** April 23, 2025 **What do you like best about Dataiku?** Quick to get started, good user interface. Great customer support. **What do you dislike about Dataiku?** Not the best for coders based developers. Not the cheapest option for doing the job. **What problems is Dataiku solving and how is that benefiting you?** Getting the most of business users advanced analytics. ### 40. Great overall experience **Rating:** 4.0/5.0 stars **Reviewed by:** Vishal D. | Analytics analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** The ease of use low code no code so all users can use **What do you dislike about Dataiku?** Explanation on new capabilities because new ones come out **What problems is Dataiku solving and how is that benefiting you?** Helping different teams connect on different projects regardless of level ### 41. Good **Rating:** 3.5/5.0 stars **Reviewed by:** Nirmala A. | VP, Model Development, Enterprise (> 1000 emp.) **Reviewed Date:** April 30, 2025 **What do you like best about Dataiku?** click and go approaches are easy and efficient **What do you dislike about Dataiku?** I want to extract the code for the click and go operation that we conduct. **What problems is Dataiku solving and how is that benefiting you?** increasing efficiency ### 42. Great program **Rating:** 4.0/5.0 stars **Reviewed by:** Elisha F. | Bi Lead, Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Love that I can combine data from multiple sources in one spot **What do you dislike about Dataiku?** Can be hard if as it is not intuitive without training **What problems is Dataiku solving and how is that benefiting you?** It is giving insights ### 43. Great Event **Rating:** 4.0/5.0 stars **Reviewed by:** Khushi A. | Sr. Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Thanks for hosting us in the AI conference. Got to learn a lot!! **What do you dislike about Dataiku?** Tough to integrate with existing organization tools **What problems is Dataiku solving and how is that benefiting you?** Using analytics to solve business solutions ### 44. Its UI allows me to navigate easily **Rating:** 4.0/5.0 stars **Reviewed by:** Paulina Y. | Global Portfolio Marketing Director, Analytics, Mid-Market (51-1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Allows us to reduce time in model demployment **What do you dislike about Dataiku?** When will it provide a full suite of model risk mgmt products **What problems is Dataiku solving and how is that benefiting you?** Reduce time to market ### 45. Dataiku for Grad Student **Rating:** 4.0/5.0 stars **Reviewed by:** Akhilesh D. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** July 18, 2024 **What do you like best about Dataiku?** Dataiku's interface is intuitive and easy to navigate, making it accessible for students who are new to data science. The drag-and-drop functionality and clear visual representation of data pipelines help in understanding complex workflows. Even with limited coding experience, I was able to build robust data models and analytics pipelines with ease. **What do you dislike about Dataiku?** Can be resource-intensive, requiring robust hardware for optimal performance Advanced features might have a steep learning curve for beginners Pricing can be high for students and small projects **What problems is Dataiku solving and how is that benefiting you?** As an Indian student in the ML domain, I focus on solving business problems such as predicting consumer behavior to improve marketing strategies, performing sentiment analysis for brand monitoring, and optimizing SEO to enhance website visibility. I also work on fraud detection in online transactions, developing personalized recommendation systems to boost user engagement, and optimizing supply chain operations through predictive analytics. These solutions help businesses in the confectionery and CPG sectors drive growth and efficiency. ### 46. Beginner level soon replacing Alteryx with Dataiku **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Health, Wellness and Fitness | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** The ability to democratize data science by making it accessible to teams with varying technical backgrounds, simplifying data access, and enabling collaboration across different roles **What do you dislike about Dataiku?** Challenging to replicate or apply data preparation pipelines in a straightforward manner **What problems is Dataiku solving and how is that benefiting you?** Using to optimize pharmaceutical product positioning based on financial implications ### 47. Data for everyone **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** 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 Dataiku?** Getting organized from project to prokect **What problems is Dataiku solving and how is that benefiting you?** Providing solutions to my business **Official Response from Taylor MECHAM:** > Thank you for sharing what you like best about Dataiku! We're continuously working to enhance project organization and streamline transitions between projects. Your input is valuable to us. ### 48. Citizen DataScience tool **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Manufacturing | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** Low code no code platform for AI and ML. **What do you dislike about Dataiku?** Licenses are very expensive. This is a huge barrier to adoption. **What problems is Dataiku solving and how is that benefiting you?** Easy to use data science tool. Marketing and leagal contract use cases ### 49. Great product **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2025 **What do you like best about Dataiku?** All in one platform to allow other users to stay within the platform **What do you dislike about Dataiku?** Lack of horizontal scaling for a better user experience **What problems is Dataiku solving and how is that benefiting you?** Allowing users to use analytics to solve real world problems ### 50. Data science for non data scientists **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** April 29, 2025 **What do you like best about Dataiku?** Very intuitive interface, easy to configure and build intelligent models with. **What do you dislike about Dataiku?** It sometimes just doesn’t work when you are executing models. **What problems is Dataiku solving and how is that benefiting you?** Improving marketplace approvals ## Dataiku Discussions - [Can I securely work on my sensitive data?](https://www.g2.com/discussions/can-i-securely-work-on-my-sensitive-data) - 2 comments, 2 upvotes - [What data visualization and reporting methods do you support?](https://www.g2.com/discussions/data-visualization) - 2 comments, 1 upvote - [What machine learning algorithms do you support?](https://www.g2.com/discussions/techical-specifications-5dafbb22-fb53-40e6-99ca-920a3000c257) - 1 comment, 1 upvote - [What programming languages do you support?](https://www.g2.com/discussions/techical-specifications-168d61c9-5165-4b3f-bded-0167b92ff8ed) - 1 comment, 1 upvote - [What data wrangling techniques do you support?](https://www.g2.com/discussions/techical-specifications-ab5002f3-fd5f-4acb-8fbd-280592800a16) - 1 comment, 1 upvote - [View Dataiku pricing details and edition comparison](https://www.g2.com/products/dataiku/reviews?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-08-12+11%3A08%3A31+-0500&secure%5Bsession_id%5D=180c8a40-15f6-4e3f-8f3a-1d006137caa3&secure%5Btoken%5D=7823c78856d7387eedf7b0333e92c565465899c211fa3aca4c9e064334d9cb22&format=llm_user) ## Dataiku Integrations - [Alation](https://www.g2.com/products/alation/reviews) - [Alteryx Designer Cloud](https://www.g2.com/products/alteryx-alteryx-designer-cloud/reviews) - [Amazon S3 Glacier](https://www.g2.com/products/amazon-s3-glacier/reviews) - [Anthropic SDK](https://www.g2.com/products/anthropic-sdk/reviews) - [AWS Bedrock](https://www.g2.com/products/aws-bedrock/reviews) - [AWS Cloud Development Kit (AWS CDK)](https://www.g2.com/products/aws-cloud-development-kit-aws-cdk/reviews) - [Azure](https://www.g2.com/products/hopem-azure/reviews) - [Azure Blob Storage](https://www.g2.com/products/azure-blob-storage/reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - [Google Vertex AI SDK](https://www.g2.com/products/google-vertex-ai-sdk/reviews) - [KaTe GCP Adapter for SAP PO](https://www.g2.com/products/kate-gcp-adapter-for-sap-po/reviews) - [MySQL](https://www.g2.com/products/mysql/reviews) - [OpenAI SDK](https://www.g2.com/products/openai-sdk/reviews) - [PostgreSQL](https://www.g2.com/products/postgresql/reviews) - [Python](https://www.g2.com/products/python/reviews) - [RedShift](https://www.g2.com/products/redshift-redshift/reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - [Tableau](https://www.g2.com/products/tableau/reviews) ## Dataiku Features **Reports** - Reports Interface - Steps to Answer - Graphs and Charts - Score Cards - Dashboards - Customizable Reports - Marketing Reports - Sales Reports - Activity Dashboard - Interactive Reports - Customizable Reports - Customizable Reports - Activity Dashboard - Customizable Dashboard **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **Additional Functionality** - Code Generation - Text to Image - Generative AI - API - Natural Language Processing - Virtual Characters and Avatars - Content Generation - Personalization and Recommendation - Conditional Generation - Transformer Model - Automated Image & Video Editing - Interactive and Co-Creative Systems - Text Summarization - Data Augmentation - Variation Autoencoder Models - Adversarial Training - Transfer Learning and Fine-tuning - Simulation and Scenario Generation - Creative Design - AI Copilot - Prompt Engineering - Foundation Model **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **System** - Data Ingestion & Wrangling - Real-Time Data **Data Preparation** - Connectors - Data Governance **Responses** - Personalization - Route To Human - Natural Language Understanding (NLU) - Multi-Language **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Scalability and Performance - Generative AI Infrastructure** - AI High Availability - AI Model Training Scalability - AI Inference Speed **Automation - AI Agents** - Sales Follow-Up - Customer Interaction Automation - Lead Generation - Document Processing - Feedback Collection - Natural Language Processing - Simulation and Scenario Generation **Integration - Machine Learning** - Integration - Third-Party Integrations **Prompt Engineering - Large Language Model Operationalization (LLMOps) ** - Prompt Optimization Tools - Template Library **Inference Optimization - Large Language Model Operationalization (LLMOps)** - Batch Processing Support **Customization - AI Agent Builders** - Natural Language Configuration - Tone Customization - Security Guardrails - API Security - Data Security - Authentication **Agentic AI - AWS Marketplace** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration **Workflow Design & Integration - AI Orchestration** - Dependency Management - Workflow Coordination - Multi-Provider API Connectivity - Multi-Step Workflow Creation - Enterprise System Integration - Real-Time Data Pipelines **Data Ingestion & Preparation - Low-Code Machine Learning Platforms** - Automatic Data Profiling & Quality Assessment - Multi‑Source Connector Support - Schema Drift / Change Detection **Statistical Tool** - Scripting - Data Mining - Algorithms **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training - Database Support - Multi-Language **Data Transformation** - Real-Time Analytics - Data Querying - Reporting/Analytics - Predictive Analytics - Visual Analytics **Management** - Cataloging - Monitoring - Governing - Model Registry **Model Development** - Feature Engineering **Data Modeling and Blending** - Data Querying - Data Filtering - Data Blending - Data Capture and Transfer **Platform** - Conversation Editor - Integration - Human-In-The-Loop - Drag & Drop Editor - Human-in-the-loop (HITL) **Operations** - Metrics - Infrastructure management - Collaboration **Cost and Efficiency - Generative AI Infrastructure** - AI Cost per API Call - AI Resource Allocation Flexibility - AI Energy Efficiency **Autonomy - AI Agents** - Independent Decision Making - Adaptive Responses - Task Execution - Problem Solving **Learning - Machine Learning** - Training Data - Actionable Insights - Algorithm **Model Garden - Large Language Model Operationalization (LLMOps)** - Model Comparison Dashboard **Functionality - AI Agent Builders** - Omni-channel Support - Agent Branding - Proactive Response Capabilities - Seamless Human Escalation - Multimedia Support - Multi-Modal Input Support **Performance Optimization & Analytics - AI Orchestration** - Workflow Performance Dashboards - Workflow Reporting - Resource Utilization Monitoring - Computational Resource Management - Dynamic Scaling - Component Monitoring **Model Construction & Automation - Low-Code Machine Learning Platforms** - Guided Algorithm & Hyperparameter Recommendation - Code Extensibility - Automated Feature Engineering **Additional Functionality** - Predictive Modeling - Configurable Workflow - Tagging - Data Import/Export - API - Predictive Analytics - Data Visualization - Endpoint Management - Multiple Data Sources - No-Code - Data Preparation - Auditing - Collaboration Tools - Big Data Analytics - ML Algorithm Library - Data Management - Activity Dashboard - Data Capture and Transfer - Activity Tracking - Data Connectors - Data Security - Data Extraction - Reporting & Statistics - Workflow Management - AI Copilot **Data Analysis** - Analysis - Data Interaction - Time Series Analysis - Trend Analysis **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Management** - Cataloging - Monitoring - Governing **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **Generative AI** - AI Text Generation - AI Text Summarization **Integration and Extensibility - Generative AI Infrastructure** - AI Multi-cloud Support - AI Data Pipeline Integration - AI API Support and Flexibility **Custom Training - Large Language Model Operationalization (LLMOps)** - Fine-Tuning Interface **Data and Analytics - AI Agent Builders** - Analytics & Reporting - Contextual Awareness - Data Privacy Compliance **Governance & Compliance Controls - AI Orchestration** - Regulatory Compliance - Governance Policy Enforcement - Role-Based Access Control - Audit Trail Management - Security Protocols **Agentic AI - AI Agents** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making **Additional Functionality** - Agent Collaboration - Data Governance - Prompt Engineering - Feedback Management - For No-Code Development - Version Control - Role-Based Permissions - Dynamic Modeling - API - Memory Management - Monitoring - Scalability - Cost Management - Scheduling - Natural Language Interface - Access Controls/Permissions - Multiple LLM Models - Integration Management - Customizable Frameworks - Pre-built Templates - Analytics - Intent Recognition - Contextual Guidance - Rules-Based Workflow - Attended Automation - Drag & Drop - For Sales/Marketing - Generative AI - Business Process Automation - AI Copilot - Third-Party Integrations - Multi-Channel Communication - Sentiment Analysis - Deep Learning - Code-free Development - Compliance Management - Automated Responses - Knowledge Management - Transfers/Routing - Personalization - Activity Dashboard - Customer Experience Management - Virtual Personal Assistant (VPA) - Chatbot - Speech Recognition - Reporting/Analytics - Task Management - Customer Engagement - AI/Machine Learning - Configurable Workflow - Unattended Automation - Conversation Intelligence - Workflow Automation - Proactive Error Detection **Decision Making** - Modeling - Data Visualizations - Report Generation - Data Unification - Customizable Reports **Deployment** - Managed Service - Application - Scalability **Connectivity** - Hadoop Integration - Spark Integration - Multi-Source Analysis - Data Lake - Real-Time Data - Data Capture and Transfer - Trend Analysis - What-if Analysis - Statistical Analysis - Data Blending - Ad hoc Analysis - Third-Party Integrations **Generative AI** - AI Text Generation - AI Text Summarization **Security and Compliance - Generative AI Infrastructure** - AI GDPR and Regulatory Compliance - AI Role-based Access Control - AI Data Encryption **Application Development - Large Language Model Operationalization (LLMOps) ** - SDK & API Integrations **Integration - AI Agent Builders** - Workflow Automation - API Usage - Platform Interoperability - CRM Data Integration - Third-Party Integrations **Agentic AI - Analytics Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making - Third-Party Integrations **Additional Functionality** - Customizable Reports - Collaboration Tools - Data Extraction - Semantic Search - Data Storage Management - Ad hoc Reporting - Reporting/Analytics - Predictive Analytics - Activity Dashboard - Access Controls/Permissions - Visual Analytics - Data Mapping - Data Synchronization - Statistical Analysis - Categorization/Grouping - Trend Analysis - Data Profiling - Linked Data Management - Data Visualization - API - Multiple Data Sources - Sentiment Analysis - Search/Filter - Data Import/Export - Data Capture and Transfer - AI Copilot - Monitoring - Data Connectors - Ad hoc Analysis - Text Mining - Reporting & Statistics - Predictive Modeling - Real-Time Analytics - Configurable Workflow - Tagging - Endpoint Management - No-Code - Data Preparation - Auditing - Big Data Analytics - ML Algorithm Library - Data Management - Activity Tracking - Data Security - Workflow Management **Additional Functionality** - Version Control - Scalability - Personalization - Data Extraction - Webhooks - API - Natural Language Processing - Fallback Handling - Drag & Drop - Multiple LLM Models - Built-in AI Assistant - Automated Testing - Data Governance - Collaboration Tools - Pre-built Templates - Agent Design Tools - Deep Learning - Model Training - Analytics - Single Sign On - Debugging - Deployment Management - Proactive Error Detection **Self Service ** - Calculated Fields - Data Column Filtering - Data Discovery - Search - Collaboration / Workflow - Automodeling - Natural Language Search - Visual Discovery - Data Blending - Data Blending **Operations** - Data Visualization - Data Workflow - Governed Discovery - Embedded Analytics - Notebooks - Data Discovery **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image - Generative AI **Usability and Support - Generative AI Infrastructure** - AI Documentation Quality - AI Community Activity **Model Deployment - Large Language Model Operationalization (LLMOps) ** - One-Click Deployment - Scalability Management **Deployment & Integration - Analytics Platforms** - No-code Dashboard Builder - Report Scheduling and Automation - Embedded Analytics and White-labeling - Data Source Connectivity - Multiple Data Sources - Query Builder **Additional Functionality** - Data Warehousing - Drag & Drop - Activity Dashboard - Data Connectors - Ad hoc Reporting - Customizable Reports - Alerts/Escalation - Templates - Forecasting - Data Migration - Data Transformation - Access Controls/Permissions - API - Data Cleansing - Data Synchronization - AI Copilot - Dashboard Creation - Data Extraction - Data Security - SSL Security - Collaboration Tools - No-Code - High Volume Processing - Database Support - Search/Filter - Generative AI **Additional Functionality** - Demand Forecasting - AI/Machine Learning - Drag & Drop - For Healthcare - Forecasting - Data Extraction - Third-Party Integrations - Decision Support - Modeling & Simulation - Alerts/Notifications - Reporting/Analytics - Multiple Data Sources - For Retail - For Education - Data Discovery - Graphical Workflow Editor - Performance Metrics - Business Rules Management - AI Copilot - Natural Language Processing - Data Transformation - Data Clustering - API - Data Blending - Data Classification - Workflow Management - Workflow Automation **Advanced Analytics** - Predictive Analytics - Data Visualization - Big Data Services - Real-Time Analytics - Reporting/Analytics - Real-Time Analytics - Reporting/Analytics - Visual Analytics **Guardrails - Large Language Model Operationalization (LLMOps)** - Content Moderation Rules - Policy Compliance Checker **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making - Third-Party Integrations **Performance & Scalability - Analytics Platforms** - Large data handling and Query Speed - Concurrent User Support - Database Support **Model Monitoring - Large Language Model Operationalization (LLMOps)** - Drift Detection Alerts - Real-Time Performance Metrics **Advanced Analytics & Modeling - Analytics Platforms** - Data Modeling and Governance - Notebook and Script Integration - Built-in Predictive and Statistical Models **Security - Large Language Model Operationalization (LLMOps)** - Data Encryption Tools - Access Control Management **Agentic AI Capabilities - Analytics Platforms** - Auto-generated Insights and Narratives - Natural Language Queries - Proactive KPI Monitoring and Alerts - AI Agents for Analytical Follow-ups **Gateways & Routers - Large Language Model Operationalization (LLMOps)** - Request Routing Optimization **Personalized Intelligence - Analytics Platforms** - Behavioral Learning for Contextual Query Refinement - Role-based Insight Personalization - Conversational and Prompt-based Analytics - Ad hoc Query - Visual Analytics **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs - Real-Time Data - Real-Time Data - Third-Party Integrations - Third-Party Integrations **Platform** - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications - Mobile Access - Metadata Management **Additional Functionality** - Drag & Drop - Secure Data Storage - Data Import/Export - Customizable Branding - Dashboard Creation - Access Controls/Permissions - Real-Time Reporting - Metadata Management - Forecasting - Data Storage Management - Ad hoc Analysis - Ad hoc Reporting - Data Migration - AI Copilot - Self Service Data Preparation - Search/Filter - Data Mapping - Monitoring - Sentiment Analysis - User Management - Sales Trend Analysis - Charting - Reporting & Statistics - Performance Metrics - Alerts/Notifications - Data Extraction - Widgets - Storytelling - Trend Analysis - Collaboration Tools - Financing Management - Self-service Analytics - KPI Monitoring - Dashboard - API - Data Integration - Scorecards - Data Management - Task Management - Progress Tracking - Data Connectors - Data Visualization - Profitability Analysis - Project Tracking - Strategic Planning - Goal Setting/Tracking - Publishing/Sharing - Predictive Analytics - Real-Time Monitoring - Templates - Mobile Access - Customizable Templates - Workflow Management - Financial Reporting - Audit Management - OLAP - Single Sign On - Data Synchronization ## Top Dataiku Alternatives - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (727 reviews) - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (860 reviews) - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) - 4.6/5.0 (503 reviews)