Role of R In Business Intelligence

To put it simply Business Intelligence is the action of extracting and to derive information that may be of use from the available data. As might be evident the process is a broad one where the quality and the source of the data structure is variable. Transformations like this might in technical terms be described as ETL or extract, transform and load in addition to the presentation of information that is of use.

 

role of r in business intelligence

R Programming in Business Intelligence

Some R Programming Experts hold that R is fully able to take on the role of the engine for processes related to BI. Here we will focus only on the BI function of R i.e. to extract, transform load and present information and data. The following packages correspond to indicated processes in Business Intelligence.

 

Extract

 

Extraction

 

  •  RODBC
  • DBI
  • data.table’s fread
  • RJDBC

 


 

In addition to these, there are several other packages that support data in a variety of formats.

 

Transform

 

  • data.table
  • dplyr

 

Load

 

  • DBI
  • RODBC
  • RJDBC

 

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Prsentation

 

Presenting data is a wholly different ball game than the previously mentioned process of ETL. Never fear, it may be outsourced with ease to tools of BI dashboard with ease by populating the structure of data according to the expectations of the particular data tool. R is able to create a dashboard of a web app directly from within itself through packages like:

 

  •  shiny
  • httpuv
  • opencpu
  • rook

 

These packages let you play host to interactive web apps. They have the ability to query the data in an interactive manner and generate interactive plots. The basis for all of these is an R session engine and is able to execute all functions of R and may leverage the capabilities of statistics of all packages in R.

 

2

 

Extras

 

The above mentioned packages serve as the core whose functionality may be simplified through the use of the packages mentioned below:

 

  • db.r
  • ETLUtils
  • Sqldf
  • Dplyr
  •  shinyBI
  • dwtools

 


 

The following factors are critical while R is adopted by businesses:

 

  • Extraction / Loading
  • Performance and scalability
  • Presentation
  • Support and licensing

 

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February 8, 2016 6:34 am Published by , , , , , , , , ,

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