Obtaining Stars from Flat Tables
Get conformed dimension
Get conformed dimension names
Get conformed dimension names
Get dimension
Get dimension attribute names
Get the dimension name
Get dimension names
Get the dimension type
Get fact name
Get measure names
Get the name of the role playing dimensions
Get name of uniquely implemented dimensions
Get role dimension names associated to a role-playing dimension
Get the associated role-playing dimension name
Get star schema
Get star schema names
Group facts
Group records
Group the records in the table
Homogenize a dimension
Purge dimensions in a constellation
Purge dimensions
record_update_set
S3 class
Transform a dimension into a role dimension
Set the type of a role-playing dimension
Set fact name
Set the associated role-playing dimension name
Apply dimension record update operations to a dimension
Apply update operations to dimensions
Update facts with a list of modified dimensions
Update facts with a general dimension
Update facts with a role dimension
Conform dimensions of given name
Replace in facts a star schema role dimension
Perform union of dimensions
Set the dimension type
Set the type of a conformed dimension
Transform a value according to its type
Unify facts by grain
fact_table
S3 class
constellation
S3 class
multistar
S3 class
record_update S3 class
dimensional_model
S3 class
dimensional_query
S3 class
Get all dimensions
Get attribute names
record_update_set S3 class
star_schema S3 class
Transform a tibble
to join
dimension_table
S3 class
dimensional_model S3 class
dimensional_query
S3 class
Conform all dimensions of a constellation
Transform a dimension numeric attributes to character
Transform dimension numeric attributes to character
Export a constellation as a multistar
Export a constellation as a tibble
list
Define dimensions in a dimensional_model
object
Define facts in a dimensional_model
object
Define selected dimensions
Define selected facts
Delete records
Delete unused foreign keys
Dereference a dimension
Export selected attributes of a dimension
Import tibble
to enrich a dimension
Import tibble
to test to enrich a dimension
Filter dimension
Filter fact rows
Filter selected instances
Find values in a dimension
Incrementally refresh a constellation with a star schema
Incrementally refresh a dimension with another
Incrementally refresh a fact table with another
Incrementally refresh a star schema with another
Is it conformed dimension?
Is dimension in set of updates?
Is it role dimension?
Is it role-playing dimension?
Make a dimension record equal to another
Apply dimension record update operations to conformed dimensions
Apply dimension record update operations
Export a multistar
as a flat table
constellation
S3 class
Reference a dimension
Remove duplicate dimension rows
Rename dimension
Rename dimension attributes
Rename fact
Rename measures
Replace a star schema dimension
Replace in facts a star schema dimension
Replace in facts a star schema general dimension
Replace records
Define a role playing dimension in a star_schema
object
Run query
Select dimension
Select fact
Generate a record selection bitmap
Set the dimension name
Transform names according to the snake case style
Transform names according to the snake case style in a dimension
Transform names according to the snake case style in a fact table
star_schema
S3 class
Export a star schema as a flat table
Star schema as multistar
export (common)
Export a star schema as a multistar
Export a star schema as a tibble
list
Export a star schema as a tibble
list (common)
Obtaining Star Schemas from Flat Tables
Update a dimension record with a set of values
Update dimension records with a set of values
Update dimension records with a set of values in given columns
Validate names
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 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 of this package is to define transformations that allow obtaining stars from flat tables easily. In addition, it includes basic data cleaning, dimension enrichment, incremental data refresh and query operations, adapted to this context.
Useful links