--- 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 & Product Details Visit Website 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. * * * Product Website Dataiku Seller [Dataiku](https://www.g2.com/sellers/dataiku) Discussions [Dataiku Community](https://www.g2.com/products/dataiku/discuss) Languages Supported German, English, French, Japanese, Korean, Spanish Solution Type All-in-One Show More ## Value at a Glance Averages based on real user reviews. ### Time to Implement 6 months [ View More Pricing Information ](https://www.g2.com/products/dataiku/pricing) ## Dataiku Integrations (19) What do users say about integrations? Verified by Dataiku [ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Alation ](https://www.g2.com/products/alation/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Alteryx Designer Cloud ](https://www.g2.com/products/alteryx-alteryx-designer-cloud/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Amazon S3 Glacier ](https://www.g2.com/products/amazon-s3-glacier/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Anthropic SDK ](https://www.g2.com/products/anthropic-sdk/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") AWS Bedrock ](https://www.g2.com/products/aws-bedrock/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") AWS Cloud Development Kit (AWS CDK) ](https://www.g2.com/products/aws-cloud-development-kit-aws-cdk/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Azure ](https://www.g2.com/products/hopem-azure/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Azure Blob Storage ](https://www.g2.com/products/azure-blob-storage/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Databricks ](https://www.g2.com/products/databricks/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Google Cloud BigQuery ](https://www.g2.com/products/google-cloud-bigquery/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Google Vertex AI SDK ](https://www.g2.com/products/google-vertex-ai-sdk/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") KaTe GCP Adapter for SAP PO ](https://www.g2.com/products/kate-gcp-adapter-for-sap-po/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") MySQL ](https://www.g2.com/products/mysql/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") OpenAI SDK ](https://www.g2.com/products/openai-sdk/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") PostgreSQL ](https://www.g2.com/products/postgresql/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Python ](https://www.g2.com/products/python/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") RedShift ](https://www.g2.com/products/redshift-redshift/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Snowflake ](https://www.g2.com/products/snowflake/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Tableau ](https://www.g2.com/products/tableau/reviews) Show More ![Ravindra N.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Ravindra N.") RN Ravindra N. SDET - 2 Oil & Energy Enterprise (\> 1000 emp.) 7/18/2026 "Unified, Low-Code Platform That Boosts End-to-End Data & AI Productivity" 4.5/5 What do you like best about Dataiku? What I like most about Dataiku is its ability to bring data preparation, analytics, machine learning, and deployment into a single collaborative platform. It enables both technical and non-technical users to work together, making it easier to build end-to-end data and AI workflows. Visual, low-code interface for building data pipelines and machine learning workflows. Support for Python, SQL, and R, allowing advanced users to customize projects when needed. Strong collaboration features with versioning and project sharing. Seamless integration with databases, cloud platforms, and big data technologies. Built-in tools for model deployment, monitoring, and governance. For me, the most valuable feature is the combination of visual workflows and code-based flexibility. I can quickly prototype data pipelines visually while still using code for advanced transformations or custom machine learning logic. The biggest benefit is improved productivity. Dataiku reduces the time needed to prepare data, develop models, and deploy AI solutions, while enabling better collaboration between data scientists, analysts, and business teams. Review collected by and hosted on G2.com. What do you dislike about Dataiku? The biggest drawback is the complexity of large projects. As workflows grow, managing dependencies, pipelines, and multiple collaborators can become challenging without careful project organization. Complex projects with many datasets and workflows can become difficult to organize and navigate. Some advanced capabilities require a solid understanding of data engineering or machine learning concepts. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku solves the challenge of managing the entire data and machine learning lifecycle in one place. Instead of relying on separate tools for data preparation, model development, deployment, and monitoring, Dataiku provides a unified platform that enables teams to collaborate more efficiently. Simplifies data preparation and transformation through visual workflows. Centralizes analytics, machine learning, and model deployment in a single platform. Enables collaboration between data scientists, analysts, engineers, and business users. Integrates with cloud platforms, databases, and big data ecosystems. Supports governance, version control, and monitoring for production AI models. In my workflow, Dataiku helps accelerate data analysis and machine learning projects by reducing the effort needed to build pipelines and manage data. Its visual interface allows quick prototyping, while the ability to use Python and SQL provides the flexibility needed for more advanced use cases. The biggest benefit is improved efficiency and collaboration. Dataiku reduces the time required to move from raw data to production-ready insights, enabling teams to deliver analytics and AI solutions faster while maintaining better governance and reproducibility. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![Adalberto G.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Adalberto G.") AG Adalberto G. Development and Automation Coordinator at Pricing and Revenue Management Intelligence Enterprise (\> 1000 emp.) 7/16/2026 "Build Faster Workflows with Connected Data from many providers or distinct data sources" 4.5/5 What do you like best about Dataiku? The interface is lightweight and enables me to quickly see the entire process (even the big ones). It allows me to connect to many data sources, from many distinct providers, having an unified repo for all the external connections. The client/designer performance is really cool, since it runs on the web/cloud, so it don't require a lot of resources from my machine, even when I am processing million of rows. The license pays itself after a few workflows, since tasks that usually would take weeks to be developed (or executed by an analist), could be deployed on production in just a few days. The Data Science team of the company uses it for forecasting, running LLM models, Machine Learning and all the cool stuff. I use it for data engineering and for running python code in the between, and it is really cool! I would recommend it for anyone. There are many tutorials on the platform, with starting demo projects that in a few hours you 'll feel empowered, or invited, to start your own projects. Review collected by and hosted on G2.com. What do you dislike about Dataiku? The interface for selecting fields of a datasource or maybe creating calculated fields should be simpler. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? It helps me validating ideas and creating data pipelines with just a few clicks. Developing all of that stuff by hand coded solutions would take 10x more time. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: Seller invite ![jimena m.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "jimena m.") JM jimena m. Data Analyst Airlines/Aviation Enterprise (\> 1000 emp.) 7/16/2026 "Intuitive and Powerful for Machine Learning Experiments" 4.5/5 What do you like best about Dataiku? I like that Dataiku is intuitive. What I appreciate the most is when I conduct an experiment, whether testing different machine learning models at the same time, it offers the results in a simple and visual way. This provides an understanding of how the models are behaving and how well they performed. Review collected by and hosted on G2.com. What do you dislike about Dataiku? I find it complex to perform joins because first I have to change the data types to strings in order to join them, when I should be able to join the data if they are of the same type. It would also be good to have an option that allows joining all fields with the same names and another option to join by position. Additionally, it should allow joining by multiple data sources. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? With Dataiku, I centralize different data sources into a single tool, allowing me to work with Big Data quickly and perform effective ETL processes. It also helps me with data quality in migration flows. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: Seller inviteAI Translated ![Marco J.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Marco J.") MJ Marco J. Senior Software Engineer - Pricing & Revenue Management Intelligence Enterprise (\> 1000 emp.) 6/29/2026 "Dataiku: No-Code ETL Powerhouse — Collaborative, Visual, and Python/SQL Friendly" 4.5/5 What do you like best about Dataiku? What I like the most about Dataiku is that it is mostly a no-code platform, and allows technical, and non-technical users to collaborate in an easy way. It is extremely easy to share workbooks between coworkers, easy to set-up (using the web version with any browser - Edge, Chrome, etc.). The visual recipes make it easy to understand the flow of the pipeline, while also having the flexibility of adding Python or SQL when necessary. For data preparation, automation, and building repeatable workflows, I can say it's the best ETL platform I have used. We use Alteryx in our company, but we are starting to implement our workflows and apps inside Dataiku instead of Alteryx. Review collected by and hosted on G2.com. What do you dislike about Dataiku? The main thing I dislike about Dataiku is that the learning curve can be a little steep at the beginning. There are many features, menus, recipes, and project settings available, so it can feel overwhelming until you understand how everything is organized. Some tasks that seem simple at first may require learning the Dataiku specific way of doing things, especially around flows, datasets, automation, and deployment. Once you get more familiar with the platform, it becomes much easier to use, but the onboarding phase could be smoother with more user-friendly examples and tutorials. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku helps solve the business problem of automating data workflows that would otherwise require manual work across different tools. This is useful when working with APIs, because we can extract data from external or internal systems, transform it, and schedule the process to run automatically. In the airline industry, having a platform with schedulers is extremely necessary. Many processes depend on updated data, fixed execution times, and reliable automation. Dataiku makes it easier to organize these workflows in one place, reduce manual steps, and monitor the process when something fails. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: Seller invite ![Bill C.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bill C.") BC Bill C. Group Operations Manager Enterprise (\> 1000 emp.) 6/16/2026 "From idea to model in minutes: Dataiku accelerates the team's work" 4.5/5 What do you like best about Dataiku? The best thing about Dataiku is how easy it is to go from an idea to a working model. I can clean the data, create variables, test models, and deploy them without having to switch tools. Additionally, it keeps everything well organized and helps the team move faster. Review collected by and hosted on G2.com. What do you dislike about Dataiku? What I like least about Dataiku is that some heavier workflows can feel slow, especially when several users are working simultaneously with large datasets. Additionally, some functions require more clicks than I expected to get to what I need. It's nothing critical, but there is room to simplify and streamline the experience. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku helps us solve the problem of having data scattered across different tools and teams. It centralizes our workflows, reduces manual work, and greatly facilitates collaboration. By automating repetitive tasks and providing us with a consistent way to prepare data, analyze it, and deploy models, it accelerates our projects and improves the quality of our decisions. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerSource: G2 inviteAI Translated DG Diego G. Enterprise (\> 1000 emp.) 6/19/2026 "VisualML Potente con Limitaciones en Procesamiento Masivo" 5/5 What do you like best about Dataiku? Me gusta el VisualML porque me permite seleccionar visualmente los modelos necesarios o que quiero probar, lo que me ayuda a sacar prototipos más rápido y agilizar mis proyectos de trabajo. Además, valoro la parte híbrida, que me permite usar el Python Recipe para tareas más complicadas o modelos más complejos. Esto me da la flexibilidad de no estar limitado a los modelos de VisualML, pudiendo programar los míos propios o utilizar librerías externas. También aprecio la capacidad de evaluar múltiples modelos al mismo tiempo con el autoML, así como la facilidad para procesar datos con los flujos low-code. Review collected by and hosted on G2.com. What do you dislike about Dataiku? Lo que no me encanta de Dataiku es que para datasets muy grandes o masivos, tarda muchísimo en realizar las lecturas o procesos de los recipes. En la parte de ML, me gustaría tener alguna forma de unir Python Recipes con VisualML, o tener un centro donde pueda monitorear ambas cosas, no solo los modelos deployed en VisualML, así evitar tener que entrar a los logs de cada Python recipe a ver si algo falló o no. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku me ayuda en proyectos de data science, entrenar y evaluar múltiples modelos simultáneamente, agilizar la generación de features y facilitar la revisión de parámetros, todo con flujos low-code. Review collected by and hosted on G2.com. Show More 6/23/2026 Validated ReviewerIncentivizedSource: Seller invite ![Alec P.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Alec P.") AP Alec P. Data Science Capstone Enterprise (\> 1000 emp.) 6/19/2026 "Streamlined Data Management with Stellar Support" 5/5 What do you like best about Dataiku? I really like Dataiku's graphical interface. I'm a huge fan of that visual flow showing how joins happen and where data is moving. As a visual person, it helps me get a better map of our complex projects, making it easy to understand what I'm doing and where I'm going. I think the ease of setup was impressive too. I don't recall the implementation being a headache at all; it was pretty straightforward connecting to our Databricks. We love how easy it is to work with different data types in Dataiku. I also enjoy cleaning data there when I get the chance, even though I'm often in Databricks. We love how much our team enjoys using Dataiku, and we're really happy customers. The tag-ups and consulting services have always been really on point and helpful for us. Due to the enthusiasm at Santee Cooper, we've expanded our Dataiku licenses significantly. Review collected by and hosted on G2.com. What do you dislike about Dataiku? Sometimes working with your own custom code can be challenging. I will hit weird runtime errors when trying to run scripts I wrote. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku solves our shadow IT problem by allowing us to control and curate data access with role-based permissions. It uses our centralized hub (Databricks) and allows us to track data lineage and output validation. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: Seller invite LS Luciana S. IT Manager Health, Wellness and Fitness Mid-Market (51-1000 emp.) 6/12/2026 "Centralized Data Prep and Collaboration in One Powerful Platform" 4.5/5 What do you like best about Dataiku? Dataiku makes us appreciate the centralized data preparation capabilities, governance, deployment, machine learning and analytics , all in a single platform The program allows all stakeholders, from analysts, data scientists, engineers and information users to collaborate and work together Dataiku is non technical, and supports both coders and non technical teams, making the business workflow efficient The program has a fast development cycle, and it allows faster data exploration for efficient operations The interface for Dataiku is straightforward and it makes complex data projects to be easily executed We experience seamless data visualization, something that explains in details users about data structures and analytics Review collected by and hosted on G2.com. What do you dislike about Dataiku? Dataiku gets complicated, more so when users explore advanced features and this overwhelms them There is slow performance from Dataiku, more so when handling larger projects Dataiku is expensive and enterprise focused, something that affects small organizations Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku ensures the data fragmentation issues have been resolved, centralizing data preparation, monitoring and analytics for accurate reporting The software supports users to transform, clean, and prepare database for improved performance There is brilliant collaboration with all company stakeholders, from analysts, data scientists, business users, among others The program foster the concept of machine learning, which gives remarkable visual tools and deployment features There is efficient model governance from the software, compliance management and this makes all business processes more effective Dataiku helps our company in analytics initiatives and Scale AL and no additional technical burdens The software streamlines advanced data analytics, where even low code users faces no operational challenges Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Rakshith N.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Rakshith N.") RN Rakshith N. Analyst Retail Enterprise (\> 1000 emp.) 3/12/2026 "Dataiku:A plug in tool for Data Science" 4.5/5 What do you like best about Dataiku? What I like most about Dataiku is how it brings the entire data workflow into one place. It allows teams to easily prepare data, build machine learning models, and deploy them without switching between multiple tools. The visual interface makes it easy to understand data pipelines, while still allowing advanced users to write code when needed. This balance between visual tools and coding flexibility makes collaboration between data scientists, analysts, and engineers much smoother. It helps teams move faster from raw data to real insights and production-ready models. Review collected by and hosted on G2.com. What do you dislike about Dataiku? One thing I dislike about Dataiku is that it can feel a bit heavy and complex, especially when working with very large datasets or many workflows. Sometimes the interface becomes slower, and managing multiple projects can get confusing. Also, while the visual tools are helpful, certain advanced customizations still require coding, which might be challenging for non-technical users. Overall, it’s a powerful platform, but there is a bit of a learning curve when you first start using it. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku helps solve the problem of managing the entire data and machine learning workflow in one platform. Instead of using separate tools for data preparation, analysis, model building, and deployment, Dataiku brings everything together. This makes it easier to organize projects, track data pipelines, and collaborate with other team members. For me, it has been helpful because it simplifies the process of turning raw data into useful insights and models. It also improves collaboration between technical and non-technical teams, since analysts can use the visual interface while data scientists can still write code when needed. Overall, it helps speed up the development process and makes data projects more structured and easier to manage. Review collected by and hosted on G2.com. Show More 3/18/2026 Current UserValidated ReviewerIncentivizedSource: G2 invite ![Lokesh S.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Lokesh S.") LS Lokesh S. Senior Data Scientist Mid-Market (51-1000 emp.) 6/2/2026 "A powerful central hub for our data science and analytics teams" 5/5 What do you like best about Dataiku? In our mid-sized company, we use Dataiku as the central hub for all our machine learning and advanced analytics projects. Before this, our data workflows were a mess of isolated Python scripts and disconnected spreadsheets. Now, we use it to build end-to-end pipelines, specifically focusing on customer churn prediction models and automated inventory forecasting. It acts as the bridge where our data engineering, data science, and business analytics teams actually collaborate on the same exact projects without stepping on each other's toes.As a senior data scientist, the biggest win for me is the flexibility between visual tools and actual coding. I do not want to be boxed into a pure drag-and-drop interface, and Dataiku gets that. I can dive into a code recipe and write custom Python or SQL when I need to do something highly complex, while our business analysts can use the visual recipes to handle basic data joining and cleaning. This hybrid approach saves me countless hours of doing repetitive data prep. I also really appreciate how straightforward it makes model deployment. Pushing a model into production used to require a massive handoff meeting with IT, but now we can package and deploy our models with just a few clicks, making our iteration cycles much faster. Review collected by and hosted on G2.com. What do you dislike about Dataiku? Despite being marketed heavily as a tool for everyone, the learning curve for completely non-technical users is still pretty steep. When I onboard new business analysts, it takes them a solid few weeks to truly get comfortable navigating the flow and understanding the logic of the visual recipes. Another frustration is that the version control, while functional, feels a bit clunky and restrictive if you are used to a traditional Git workflow. Lastly, when you are dealing with very heavy, complex flows with dozens of datasets, the visual interface can sometimes lag or feel a bit cluttered to navigate. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? The main problem Dataiku solved for us was the massive bottleneck between the data science team and the business stakeholders. We used to build predictive models, like our churn risk scorer, and then struggle to make those insights easily accessible to the sales team on a daily basis. By keeping everything in Dataiku, we automated the entire pipeline. Now, the model scores new data overnight, and the sales team can just check a built-in dashboard every morning to see which accounts need immediate attention. It took us out of the business of manually running scripts and sending CSVs, freeing up my team to actually focus on researching and building better models. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ## Questions about Dataiku? Ask real users or explore answers from the community Get practical answers, real workflows, and honest pros and cons from the G2 community or share your insights. [ Ask about Dataiku ](https://www.g2.com/products/dataiku/discussions/new) ![Verified User in Financial Services](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Financial Services") G2 Verified User in Financial Services Review provider 0 Upvotes 0 [ Join the conversation ](https://www.g2.com/discussions/dataiku-review-provider) ![Verified User](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User") G2 Verified User • Last activity over 4 years ago Can I securely work on my sensitive data? 2 Upvotes 2 [ Join the conversation ](https://www.g2.com/discussions/can-i-securely-work-on-my-sensitive-data) [ View all Discussions ](https://www.g2.com/products/dataiku/discuss) ## Pricing Insights Averages based on real user reviews. ### Time to Implement 6 months ### Return on Investment 14 months ### Perceived Cost $$$$$ [ View More Pricing Information ](https://www.g2.com/products/dataiku/pricing) Dataiku Comparisons ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/small_square/small_square_4392df8f60987b58908bcb30c16818bc/datarobot.jpeg "Product Avatar Image") DataRobot 4.4/5(32) [ Compare Now ](https://www.g2.com/compare/datarobot-vs-dataiku) ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/small_square/small_square_2c6c77d8284b2f6609c2f9dc0ba6b5a9/alteryx.png "Product Avatar Image") Alteryx 4.6/5(893) [ Compare Now ](https://www.g2.com/compare/alteryx-vs-dataiku) ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/small_square/small_square_13aba37ae908d9cf29a2452925257ccc/azure-databricks.jpeg "Product Avatar Image") Azure Databricks 4.5/5(239) [ Compare Now ](https://www.g2.com/compare/azure-databricks-vs-dataiku) ##### ##### Dataiku Features Reports Reports Interface Steps to Answer Dashboards Self Service Calculated Fields Building Reports Data Transformation Data Modeling WYSIWYG Report Design Model Development Language Support Drag and Drop Pre-Built Algorithms [ View More Features ](https://www.g2.com/products/dataiku/features) ## 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