Skip to main content
Search Icon Expand Search Input Field
close
Altair_Blog_hero_1920x225

Featured Articles

Six Key Requirements of Self-Service Data Preparation

Data preparation is a critical part of any data science project, but it can also be time-consuming. Choosing the right tools can really make a difference in streamlining this process. Here are six key areas to focus on when planning your data transformation workflow.

Six key requirements of self-service data preparation.Ensure your requirements cover these six key areas.Access to semi-structured and structured data sources.Data masking creates modified versions of original datasets.Automating data preparation saves time and reduces errors.Reduce risk with improved data governance.Ensure access to pre-built models with minimal support.Efficiently use your organized data in analytics.Read our eGuide about the self-service approach to data preparation.


Focusing on these key areas will help streamline your data prep and make analysis more efficient. With the right tools in place, you can save time and get better results.

To learn more about Altair's data prep capabilities, visit https://altair.com/altair-rapidminer. 

 


1. "Data Preparation: A Technological Perspective and Review"

 

Related Articles