3 citations · 6 across the 6 of their papers we have counts for
7 papers
How Wrangling Tools Shape Wrangling: A Technical Dimensions Analysis
Shiyi He, El Kindi Rezig, Paul Rosen +1
Wrangling consumes a disproportionate share of the effort associated with any data project. While a variety of tools support it, relatively little is known about how their differin…
Stress-Testing Causal Claims via Cardinality Repairs
Yarden Gabbay, Haoquan Guan, Shaull Almagor +3
Causal analyses derived from observational data underpin high-stakes decisions in domains such as healthcare, public policy, and economics. Yet such conclusions can be surprisingly…
Towards Scalable Visual Data Wrangling via Direct Manipulation
El Kindi Rezig, Mir Mahathir Mohammad, Nicolas Baret +3
Data wrangling, the process of cleaning, transforming, and preparing data for analysis, is a well-known bottleneck in data science workflows. A wide range of data wrangling techniq…
Buckaroo: A Direct Manipulation Visual Data Wrangler
Annabelle Warner, Andrew McNutt, Paul Rosen +1
Preparing datasets -- a critical phase known as data wrangling -- constitutes the dominant phase of data science development, consuming upwards of 80% of the total project time. Th…
Technical Report on Data Integration and Preparation
El Kindi Rezig, Michael Cafarella, Vijay Gadepally
AI application developers typically begin with a dataset of interest and a vision of the end analytic or insight they wish to gain from the data at hand. Although these are two ver…
Human-Centric Data Cleaning [Vision]
El Kindi Rezig, Mourad Ouzzani, Ahmed K. Elmagarmid +1
Data Cleaning refers to the process of detecting and fixing errors in the data. Human involvement is instrumental at several stages of this process, e.g., to identify and repair er…