Dataiku DSS - One-Stop Solution for All Data Science Applications
November 09, 2021
Dataiku DSS - One-Stop Solution for All Data Science Applications
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Dataiku DSS
Dataiku DSS is being used in my team to perform various tasks which ranges from data preprocessing to machine learning model creation. It provides a one-stop solution to fetch data from different sources such as Amazon S3, SQL Server databases, etc. and merge them onto a single platform. We use Dataiku DSS to perform data imputations, data cleaning and feature engineering to prepare datasets for creating machine learning models. We also extract business insights (data analytics) using various statistical methods and visual representations such as scatter plots, histograms, boxplots, etc. Furthermore, optimized ML models are created which are used to predict/forecast target variables and drive business decisions.
- Allows users to collaborate and monitor individual tasks
- Caters to both types of analysts, coders and non-coders, alike
- Integrate graphs and plots with visualization tools such as Tableau
- Its community support is very limited at the moment
- Complex to integrate with automation tools such as Blue Prism
- Very friendly interface for users
- All data analytics services provided on a single platform
- Keeps track of all models created and every actions performed on a dataset
- Customer satisfaction
- Timely project delivery
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
Do you think Dataiku delivers good value for the price?
Yes
Are you happy with Dataiku's feature set?
Yes
Did Dataiku live up to sales and marketing promises?
Yes
Did implementation of Dataiku go as expected?
Yes
Would you buy Dataiku again?
Yes