Data Validation and Organization of Metadata for Local and Remote Tables

Validate data in data frames, 'tibble' objects, 'Spark' 'DataFrames', and database tables. Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions. Many other workflows are available including an information management workflow, where the aim is to record, collect, and generate useful information on data tables.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("pointblank")

0.12.4 by Richard Iannone, 2 months ago


https://rstudio.github.io/pointblank/, https://github.com/rstudio/pointblank


Report a bug at https://github.com/rstudio/pointblank/issues


Browse source code at https://github.com/cran/pointblank


Authors: Richard Iannone [aut, cre] (ORCID: , Mauricio Vargas [aut] , June Choe [aut] , Olivier Roy [ctb]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports base64enc, blastula, cli, DBI, digest, dplyr, dbplyr, fs, glue, gt, htmltools, knitr, rlang, magrittr, scales, testthat, tibble, tidyr, tidyselect, yaml

Suggests arrow, bigrquery, data.table, duckdb, ggforce, ggplot2, jsonlite, lubridate, RSQLite, RMySQL, RPostgres, readr, rmarkdown, sparklyr, dittodb, odbc


Imported by data.checker, datadiff.

Suggested by aggreCAT, intendo, manystates, whep.


See at CRAN