6 citations · 16 across the 5 of their papers we have counts for
8 papers
The Data Station: Combining Data, Compute, and Market Forces
Raul Castro Fernandez, Kyle Chard, Ben Blaiszik +7
This paper introduces Data Stations, a new data architecture that we are designing to tackle some of the most challenging data problems that we face today: access to sensitive data…
ARDA: Automatic Relational Data Augmentation for Machine Learning
Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen +3
Automatic machine learning (\AML) is a family of techniques to automate the process of training predictive models, aiming to both improve performance and make machine learning more…
Data Market Platforms: Trading Data Assets to Solve Data Problems
Raul Castro Fernandez, Pranav Subramaniam, Michael J. Franklin
Data only generates value for a few organizations with expertise and resources to make data shareable, discoverable, and easy to integrate. Sharing data that is easy to discover an…
Dataset-On-Demand: Automatic View Search and Presentation for Data Discovery
Raul Castro Fernandez, Nan Tang, Mourad Ouzzani +2
Many data problems are solved when the right view of a combination of datasets is identified. Finding such a view is challenging because of the many tables spread across many datab…
Starling: A Scalable Query Engine on Cloud Function Services
Matthew Perron, Raul Castro Fernandez, David DeWitt +1
Much like on-premises systems, the natural choice for running database analytics workloads in the cloud is to provision a cluster of nodes to run a database instance. However, anal…
Termite: A System for Tunneling Through Heterogeneous Data
Raul Castro Fernandez, Samuel Madden
Data-driven analysis is important in virtually every modern organization. Yet, most data is underutilized because it remains locked in silos inside of organizations; large organiza…