10 citations · 29 across the 15 of their papers we have counts for
15 papers
Auto-BI: Automatically Build BI-Models Leveraging Local Join Prediction and Global Schema Graph
Yiming Lin, Yeye He, Surajit Chaudhuri
Business Intelligence (BI) is crucial in modern enterprises and billion-dollar business. Traditionally, technical experts like database administrators would manually prepare BI-mod…
Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines
Dezhan Tu, Yeye He, Weiwei Cui +5
Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications. Crucially, these pipelines are \em…
Auto-Tag: Tagging-Data-By-Example in Data Lakes
Yeye He, Jie Song, Yue Wang +5
As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e.g., files and databases) in data lakes with addition…
COMPARE: Accelerating Groupwise Comparison in Relational Databases for Data Analytics
Tarique Siddiqui, Surajit Chaudhuri, Vivek Narasayya
Data analysis often involves comparing subsets of data across many dimensions for finding unusual trends and patterns. While the comparison between subsets of data can be expressed…
Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search
Junwen Yang, Yeye He, Surajit Chaudhuri
Recent work has made significant progress in helping users to automate single data preparation steps, such as string-transformations and table-manipulation operators (e.g., Join, G…
Auto-FuzzyJoin: Auto-Program Fuzzy Similarity Joins Without Labeled Examples
Peng Li, Xiang Cheng, Xu Chu +2
Fuzzy similarity join is an important database operator widely used in practice. So far the research community has focused exclusively on optimizing fuzzy join \textit{scalability}…