English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Data wrangling tasks such as obtaining and linking data from various sources,transforming data formats, and correcting erroneous records, can constitute upto 80% of typical data engineering work. Despite the rise of machine learningand artificial intelligence, data wrangling remains a tedious and manual task.We introduce AI assistants, a class of semi-automatic interactive tools tostreamline data wrangling. An AI assistant guides the analyst through aspecific data wrangling task by recommending a suitable data transformationthat respects the constraints obtained through interaction with the analyst.  We formally define the structure of AI assistants and describe how existingtools that treat data cleaning as an optimization problem fit the definition.We implement AI assistants for four common data wrangling tasks and make AIassistants easily accessible to data analysts in an open-source notebookenvironment for data science, by leveraging the common structure they follow.We evaluate our AI assistants both quantitatively and qualitatively throughthree example scenarios. We show that the unified and interactive design makesit easy to perform tasks that would be difficult to do manually or with a fullyautomatic tool.

AI Assistants: A Framework for Semi-Automated Data Wrangling