At VLDB in Boston next week — come find us:
Demo: Tue 13:45 and Wed 15:45, Marina Ballrooms II–IV
Talk: Thu 13:45, Grand Ballroom E (mine is last in the session)
Poster: Thu 17:15, Galleria
And if you think about data platforms for decision-making too, let's talk! #VLDB2026
We are finally coming out of stealth, right in time for VLDB.
What we are building is a Decisionhouse: a new class of data infrastructure that makes prescriptive analytics native to the lakehouse, through its Decision Query Language, DeQL.
Three papers came out of this work:
Decisionhouse — the vision (VLDB 2026)
https://t.co/eR2XUiUcep
DeQL Studio — the demo (VLDB 2026)
https://t.co/kRzluETmFj
DeQL — the language spec
https://t.co/h9fxUfXggT
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@josephmoon_ai Please take a look at our papers on SQL extensions to support decision-making analytics directly in a database. We call these queries "package queries" and they are very powerful (as powerful as ILPs!). The language is called PaQL.
@josephmoon_ai sPaQL also supports combining predictions (as Monte Carlo simulations) with decision-making. An application example is building financial portfolios. With sPaQL we can do it with a SQL-like language and with data directly in a database.
I am so delighted that we won the Best Demo Awards for sPaQLTools https://t.co/RuZNDDhCgR and SuDocu https://t.co/Qpdwn2nmQP at VLDB 2020! I am so grateful to have such amazing collaborators. Thank you @FarihaAnna @MiroMannino@AzzaAbouzied Alexandra Meliou, and Peter J. Haas!
Check out my SIGMOD talk in case you missed it! See how you can use our Package Query system to do Portfolio Optimization and other stochastic constrained optimization problems! https://t.co/U1kei6n4kg
Check out our cool work on stochastic optimization @SIGMOD2020 R4 (W 1:30-3 PM PDT) @MatteoBrucato will present how you can use our DB system to solve optimization problems in an uncertain world. Paper with Nishant Yadav, Peter Haas, Alexandra Meliou: https://t.co/GJh7C3Vuqw