Dataiku Trial (Sandbox)
Dataiku | 13.2.2 20241114Linux/Unix, Other 8 - 64-bit Amazon Machine Image (AMI)
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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.
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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.
Robust tool for data science engineer
What do you like best about the product?
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.
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.
What do you dislike about the product?
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.
Cost: cost is also high .this is not suitable for small organization .
Limited free version:there are limitations of free version.
What problems is the product solving and how is that benefiting you?
The problem is solving of data integration.
It's robust data integration tool for it integrate data from various data sources
It's robust data integration tool for it integrate data from various data sources
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
Dataiku for super interpretable pipelines
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
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.
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.
Dataiku DSS Data Science Platform
What do you like best about the product?
Visual Recipes and Code Recipes and AutoML
What do you dislike about the product?
Almost all features are nice, may be somehow expensive
What problems is the product solving and how is that benefiting you?
Regression and Classification
Dataiku DSS - One Stop Solution For Data Science Community
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
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.
Recommendations to others considering the product:
Anaconda, RStudio
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