Home/ New SaaS Software/ Dataiku DSS/ Reviews
AI-based Centralized Data Platform For Enterprise
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Overall, reviewers praise Dataiku DSS for its user-friendly interface, extensive features, and ability to handle large datasets efficiently. They commend its intuitive drag-and-drop functionality, visual modeling capabilities, and seamless integration with various data sources. Additionally, reviewers appreciate the platform’s scalability, flexibility, and robust security features. However, some users mention occasional performance issues, a steep learning curve for advanced features, and limited customer support.
AI-Generated from the text of User Reviews
Dataiku helps to make your hefty data pipelines readable and easier to manage. There are a lot of inbuilt recipes which helps you make your pipeline modular. It is definitely one of the nest place to productionise your systems.
Not all recipes help you do the exact thing you want to do. For that you have to code the entire pipeline in a say, python recipe which again makes it less modular. Also there is less documentation available.
Dataiku is beneficial in breaking your entire code into pieces called zones which makes it super interpretable for the client to understand what each piece actually does. Also, it has a good UI which makes easy to track the flow of your pipeline.
Visual Recipes and Code Recipes and AutoML
Almost all features are nice, may be somehow expensive
Regression and Classification
Dataiku DSS allows users to collaborate with each other and also track every users work progress. It integrates seamlessly with other tools such as Amazon S3, MS SQL Server database, etc.
Being a recently launched product (2013), Dataiku DSS has minimal customer support at the moment. It can currently be installed only on Windows operating systems.
Anaconda, RStudio
Dataiku DSS provides a one-stop solution for all data science applications. It integrates well with external data sources like Amazon S3 and MS SQL Server database. It also provides several data analysis options such as statistical tools, graphs and plots for data visualization, etc. The significant benefit of Dataiku DSS lies in its flexibility to allow coders and non-coders to create optimized machine learning models. Other essential features include tracking user performances and contributions in a collab environment.
The clean design of the application and the ease of use for anyone to pick up no matter their level of knowledge
You have to install on linux if you don't know how to install virtual machines
Data analytics, data wrangling and ETL
1.Dataiku is one place tool where we can do work with data like
Data Preparation
Data Exploration
automated AI
Model Deployment
AI Monitoring
APP Management
2. Best tool to Data transformation from any resource and analysis the data in different view
3. Best tool to generate report and model of the data in pictorial and table representation.
Does not scale well for more number of users
Could have better support on platform installation and maintenance
the statistics data can be better
Not giving tableau plugin
It is best tool for transformation data into different dimension and analysis the data.
it is best tool for data cleaning and transformation according to different business requirement.
data analyst and data scientist enthusiasm use this tool and make your decision more easy.
We are promoting the product to our client as best analytical tool
As a trainer, i delivery the training about this product.
The flows make it very easy to visualize my data flow, instead of having multiple files everywhere. It saves me a lot of time when cleaning data and mixing different languages and technologies such as SQL, Python and R in the same project.
The plugin feature also gives me a lot of flexibility.
The fact that you can insert new data to your database from DSS, automate flows insert checks, etc. makes the whole process very intuitive and saves a lot of time.
Support is also great, very quick in answering our questions and very proactive in solving issues.
Some minor bugs exist and some features are still needed.
I have faced bugs when integrating with Snowflake, but no major issues.
Since it is a new tool, we often face issues due to missing features, but the support team is always willing to help and add those features to their development pipeline.
Support for IT infrastructure could be a bit more proactive too, sometimes we feel a bit lost with technical issues such as storage space and how DSS uses it.
I use it for pretty much everything at work now, from recommender systems to forecasting. It saves me a huge amount of time.
I was able to collaborate with other teammates by sharing tables between projects, and automate reports and dashboards, including notifications in other tools, such as Microsoft Teams, to inform of any issues when updating those reports.
I like the flexibility to ingest different data sources. The user interface is intuitive and allows you to upload data into a project with a few clicks. Also, the portfolio of recipes and algorithms help expedite the development of different algorithms. One exercise that I'd like to do is to test the time-saving opportunities that I can have with this type of tool.
This might sound picky, but I didn't like the drag and dropped functionality within the flow, it's hard to move things around.
I'd recommend getting the certification. That's a good way to get your hands one using real-world problems to explore in detail the different functionalities of the software. Also, have a data catalog to understand all the components of your data
I'm using Dataiku mostly for use cases within the Healthcare Industry
Scalability, Availability of various Pre processing Steps/Algorithms . And also the flexibility to tweak the algorithm parameters really helpful and useful
Nothing to dislike about this product, was useful till date
Excellent option if you are not hands on with coding but have the knowledge skills of Machine Learning/Data Science
To design and compare various models, customize the models as per my need and also scale it up without having to code allot!
Easy of use,We are using it to build data pipeline for our data lake.It takes care of all the configuration things ,engineers just need to concentrate on scripting
Some of the restrictions on the platform,a better scheduler would be a good one
Data pipelining made simple
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Frequently Use: this tool we use very frequently for data analysis and optimise an d filtering.
Easy to use: this tool is easy to use.
It's very user friendly
Easy to integration: this tool is easy to integration with other platforms.
So that we could collaborate with other team.
No of features: there are no of features .like
1.robust data integration
2. scalability
3. Visual data preparation
4.modelmonitering
Etc
Easy to implementation: dataiku dss is easy to implementation
Customer support: this is very good customer support.
Although this tool is very easy to use nd user friendly but some people who are new in data science get some challenging to use.
Cost: cost is also high .this is not suitable for small organization .
Limited free version:there are limitations of free version.
The problem is solving of data integration.
It's robust data integration tool for it integrate data from various data sources