starschemar: Obtaining Star Schemas from Flat Tables
Data in multidimensional systems is obtained from
operational systems and is transformed to adapt it to the new
structure. Frequently, the operations to be performed aim to
transform a flat table into a star schema. Transformations can
be carried out using professional ETL (extract, transform and
load) tools or tools intended for data transformation for end
users. With the tools mentioned, this transformation can be
carried out, but it requires a lot of work. The main objective
this package is to define transformations that allow obtaining
star schemas from flat tables easily. In addition, it includes
basic data cleaning, dimension enrichment, incremental data
refresh and query operations, adapted to this context.
| Version: |
1.2.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
dplyr, readr, tibble, tidyr, tidyselect, snakecase, purrr, rlang, stats, pander, generics |
| Suggests: |
testthat, knitr, rmarkdown |
| Published: |
2020-09-25 |
| Author: |
Jose Samos  [aut,
cre, cph] |
| Maintainer: |
Jose Samos <jsamos at ugr.es> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Language: |
en-GB |
| Citation: |
starschemar citation info |
| Materials: |
README NEWS |
| CRAN checks: |
starschemar results |
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