Data debugging and exploration with vizier

Mike Brachmann, Carlos Bautista, Sonia Castelo, Su Feng, Juliana Freire, Boris Glavic, Oliver Kennedy, Heiko Müller, Rémi Rampin, William Spoth, Ying Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We present Vizier, a multi-modal data exploration and debugging tool. The system supports a wide range of operations by seamlessly integrating Python, SQL, and automated data curation and debugging methods. Using Spark as an execution backend, Vizier handles large datasets in multiple formats. Ease-of-use is attained through integration of a notebook with a spreadsheet-style interface and with visualizations that guide and support the user in the loop. In addition, native support for provenance and versioning enable collaboration and uncertainty management. In this demonstration we will illustrate the diverse features of the system using several realistic data science tasks based on real data.

Original languageEnglish (US)
Title of host publicationSIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Electronic)9781450356435
StatePublished - Jun 25 2019
Event2019 International Conference on Management of Data, SIGMOD 2019 - Amsterdam, Netherlands
Duration: Jun 30 2019Jul 5 2019

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078


Conference2019 International Conference on Management of Data, SIGMOD 2019

ASJC Scopus subject areas

  • Software
  • Information Systems


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