My current client has Dataiku. We do sentiment analysis and some small large language models right now. We use Dataiku as a Jupyter Notebook.
We use it a lot for marketing and analytics. The marketing and sales team uses Dataiku.
Dataiku Trial
DataikuExternal reviews
188 reviews
from
and
External reviews are not included in the AWS star rating for the product.
Data okie for Project Management
What do you like best about the product?
Great for building and refining project management documents and data analysis in consulting work to help business grow
What do you dislike about the product?
Relative standing as compared to other well known platforms
What problems is the product solving and how is that benefiting you?
Project management
Streamlining Data Science Workflows
What do you like best about the product?
The ability to automate repetitive tasks like model deployment and report generation is a game-changer. Dataiku frees up data scientists to focus on higher-level analysis and innovation, which is what I find most valuable.
What do you dislike about the product?
While Dataiku excels at streamlining many aspects of the data science workflow, optimizing workflows involving large datasets can be cumbersome. When dealing with a massive number of data partitions, I encountered processing issues that caused delays. A more efficient way to handle big data within the platform would be ideal for streamlining workflows with these complex datasets.
What problems is the product solving and how is that benefiting you?
Communication and collaboration between data scientists and business users were clunky. Dataiku's intuitive interface and collaborative features bridge this gap, allowing everyone to stay on the same page and contribute effectively.
Helpful for project collaboration
What do you like best about the product?
It allows us to apply current project workflow to new data without any need of low level abstarction of project.
What do you dislike about the product?
It is very useful software but processing charges are a little high.
What problems is the product solving and how is that benefiting you?
Dataiku simplifies data integration, enhances collaboration, and automates machine learning workflows, allowing users to efficiently prepare, analyze, and model data, thereby accelerating insights and improving decision-making.
Gives different aspects of modeling approaches and good for multiple teams' collaboration
What is our primary use case?
What is most valuable?
It's got good feature selection and creation of feature stores, and it also gives different aspects of modeling approaches. There are a lot of similarities with DataRobot.
So feature selection, different modeling, and financial metrics are good aspects.
What needs improvement?
The no-code/low-code aspect, where DataRobot doesn't need much coding at all.
Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku because you still have to code and use either Python or R, or Scala. However, with DataRobot, you don't have to do that at all.
For how long have I used the solution?
I've used Dataiku for about four years.
How are customer service and support?
The company is based in France. But they're more and more in America as well.
So, the support was okay.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I used DataRobot. Dataiku has a different kind of structure to it. It's not financially heavy like DataRobot, which caters more to financial companies, like banks. Dataiku doesn't have that yet. I think they are also working on that area. But yeah, there are some key differences between the two products.
DataRobot has an additional feature with financial firms that it creates all these financial metrics when you run a time series analysis. Those things I have not seen in Dataiku.
If any financial company is choosing between DataRobot and Dataiku, they will definitely go for DataRobot because it creates all these financial metrics. It creates deltas, time series, time difference fields, and things like that. So, that is an added feature that DataRobot has.
What's my experience with pricing, setup cost, and licensing?
Pricing is pretty steep. Dataiku is also not that cheap. It depends on the client and how much they want to spend towards a tool.
What other advice do I have?
Overall, I would rate it an eight out of ten, except for some coding things that are there, which some people may not want to do, like certain business data scientists.
Dataiku is good for multiple teams' collaboration. If many teams are collaborating and sharing Jupyter notebooks, it's very useful. It has a good data processing structure and includes most of the models. I haven't checked the large language models in it yet, but it's a pretty good tool. It does well with analytics and has a sound structure on the back end.
Some coding aspects are necessary, but it generates SQL code, which is an added feature. A lot of data engineers like Dataiku because it generates SQL code on the right side.
Best tool to Analysis and Presenting data in different Dimention
What do you like best about the product?
It is the best tool to analyze huge data based on the level of organization for decision-making.
Dataiku is the best tool to present data different views and representation data.
Dataiku is the best tool to present data different views and representation data.
What do you dislike about the product?
The tool can be more user friendly where citizen developers can analyze the data of their own business data.
It can made available with other tool where they can connect the date to analyze it.
It can made available with other tool where they can connect the date to analyze it.
What problems is the product solving and how is that benefiting you?
We are using dataiku to integrate with our own product to analyze the data and present it dashboard for decision making quickly and present in more GUI representation
All-in-one data pipeline management tool
What do you like best about the product?
Dataiku DSS provides a central platform to manage your data pipelines, ML models and more.
What do you dislike about the product?
UI could use some work. Also, the support for using multi-file projects as a recipe or pipeline is limited.
What problems is the product solving and how is that benefiting you?
Dataiku shows the flow diagram as a DAG which provides a good visualization. Moreover, its recipe build features allow you to create most data pipelines without writing any code.
Its recently added features like ML Notebooks are very useful for running Machine Learning classification or regression tasks on a dataset. Dataiku has complete support for training and evaluating Machine Learning models.
Its recently added features like ML Notebooks are very useful for running Machine Learning classification or regression tasks on a dataset. Dataiku has complete support for training and evaluating Machine Learning models.
Recipes for everything to everyone
What do you like best about the product?
The way that Dataiku can use tools like Python, R, SQL and the built-in tools to make even the most unorganized data source to information with a lot of value, undestandable for anyone that can read a dashboard.
What do you dislike about the product?
Sometimes the processing time can be prolonged for multi-user purposes; even with training data and a reduced number of users, it could be a very stressful task, going from 10 seconds to 1:30 minutes.
What problems is the product solving and how is that benefiting you?
The day-to-day information that we use in the manufacturing, marketing and salesforce are crucial for decision-making; having all the information stored on the same platform with prediction models included is a must-have combined with Qlik sense, tableau or similar softwares
DSS Flow zone feature greatly helps with dataset alignment & provide Lab for Visual & Code recipes
What do you like best about the product?
Dataiku DSS enables me to work with both structured data, which has a standard schema, & unstructured data, which has diverse schema records. It aids with dataset manipulation at a distinct level as it's analogous to our SQL tables and custom SQL query. It supports data files present in our application servers & Hadoop clusters and provides DSS recipes whenever we perform transformations on our datasets. It can also execute our Python scripts with the inclusion of Pandas library, Pig scripts, and Hive queries.
What do you dislike about the product?
None actually. Dataiku DSS even reads external datasets and helps create new ones with recipes on Hadoop HDFS, SQL database, and Amazon S3. Partition approaches followed for Discrete & Time partitioning dimensions are also well defined in Dataiku DSS.
What problems is the product solving and how is that benefiting you?
Working with predictive maintenance for our data science model is complex as it involves multiple datasets & difficult to navigate. Dataiku DSS creates a simplified view through its Flow Zone features in which we can divide our super-sized project into managable zones. We can also isolate a specific branch for Model Training and share those datasets across projects with its share to a flow zone option. Flow refactoring is also effortless as Dataiku DSS provides view only nodes option in which the zones are hidden and we can move nodes and apply tags to them as per our requirement.
Great user experience for experienced and non experienced Machine Learning users
What do you like best about the product?
User interface, good learning materials enabling the fast introduction to the platform. An easy way to understand and present the data preparation flow.
What do you dislike about the product?
Could have better support on platform installation and maintenance/tunning. Still small community, when it increases would be great to take care of small doubts and tips and tricks.
What problems is the product solving and how is that benefiting you?
Better data preparation visualization, allowing a more visual way to show the process to business
Dataiku Core Designer Certification
What do you like best about the product?
Dataiku DSS is a complete data science tool with wide range of applications. It practically have everything you can ask for.
What do you dislike about the product?
The statistics tab can be way better and interactive.
What problems is the product solving and how is that benefiting you?
I am planning to use Dataiku tool to manipulate data in Entertainment and media industry. Using DSS it gave me some fresh insights
Recommendations to others considering the product:
I would pick DSS over other tools in the industry any day if you are looking for a tool that can check all the boxes
showing 71 - 80