VACUUM

VACUUM{{Google books|XPBbEAAAQBAJ|MLOps Engineering at Scale

|page=|keywords=VACUUM|text=|plainurl=https://www.google.com/books/edition/MLOps_Engineering_at_Scale/XPBbEAAAQBAJ}}

{{Cite web|title=The VACUUM Model: Valid, Accurate, Consistent, Uniform, and Unified

|url=https://archive.today/20241021170633/https://medium.com/aimonks/the-vacuum-model-valid-accurate-consistent-uniform-and-unified-da885bf9c622|website=archive.is}}{{Citation|last=Jim Nasby|title=All the Dirt on VACUUM|date=2015|url=https://av.tib.eu/media/19118|publisher=PGCon - PostgreSQL Conference for Users and Developers, Andrea Ross|access-date=2021-04-27}}{{Cite web|date=2019-11-22|title=An Overview of VACUUM Processing in PostgreSQL|url=https://severalnines.com/database-blog/overview-vacuum-processing-postgresql|access-date=2021-04-27|website=Severalnines|language=en}} is a set of normative guidance principles for achieving training and test dataset quality for structured datasets in data science and machine learning. The garbage-in, garbage out principle motivates a solution to the problem of data quality but does not offer a specific solution. Unlike the majority of the ad-hoc data quality assessment metrics often used by practitioners{{Cite journal|last1=Pipino|first1=Leo L.|last2=Lee|first2=Yang W.|last3=Wang|first3=Richard Y.|date=2002-04-01|title=Data quality assessment|url=https://doi.org/10.1145/505248.506010|journal=Communications of the ACM|volume=45|issue=4|pages=211–218|doi=10.1145/505248.506010|s2cid=426050 |issn=0001-0782}} VACUUM specifies qualitative principles for data quality management and serves as a basis for defining more detailed quantitative metrics of data quality.{{cite journal|last1=Wang|first1=R.Y.|last2=Storey|first2=V.C.|last3=Firth|first3=C.P.|date=August 1995|title=A framework for analysis of data quality research|url=https://ieeexplore.ieee.org/document/404034|journal=IEEE Transactions on Knowledge and Data Engineering|volume=7|issue=4|pages=623–640|doi=10.1109/69.404034}}

VACUUM is an acronym that stands for:

• valid
• accurate
• consistent
• uniform
• unified
• model