We investigate the problem of building least squares regression models over training
datasets defined by arbitrary join queries on database tables. Our key observation is that …

We study two succinct representation systems for relational data based on relational algebra
expressions with unions, Cartesian products, and singleton relations: f-representations …

Enterprise data analytics is a booming area in the data management industry. Many
companies are racing to develop toolkits that closely integrate statistical and machine …

Datasets and workloads of popular applications that use graph database management
systems (GDBMSs) require a set of storage and query processing features that RDBMSs do …

The Social Network Benchmark's Business Intelligence workload (SNB BI) is a
comprehensive graph OLAP benchmark targeting analytical data systems capable of …

Two decades ago, one of us co-authored a paper commenting on the previous 40 years of
data modelling research and development [188]. That paper demonstrated that the relational …

This paper overviews factorized databases and their application to machine learning. The
key observation underlying this work is that state-of-the-art relational query processing …

Providing machine learning (ML) over relational data is a mainstream requirement for data
analytics systems. While almost all the ML tools require the input data to be presented as a …

This paper introduces LMFAO (Layered Multiple Functional Aggregate Optimization), an in-
memory optimization and execution engine for batches of aggregates over the input …

Data provenance has evolved from a niche topic to a mainstream area of research in
databases and other research communities. This article gives a comprehensive introduction …