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How R Programming is Transforming Business for Good

Today, every business is putting efforts to understand their customers and themselves, better. But, how? What methods are they applying? Do mere Excel pivot tables help analyze vast pool of data? The answer to the latter question is in the negative – Excel pivot tables are not that great at analyzing data – so a wide number of companies look forward to SAS and R Programming to cull Business Intelligence.

 
How R Programming is Transforming Business for Good
 

Besides SAS, R-Programming is another open-source language that is used by most of the budding data scientists in the world of analytics. The R Programming language is more oriented towards the correct implication of data science, while ensuring business the cutting edge data analysis tools. Continue reading “How R Programming is Transforming Business for Good”

We Feel Honored To Conduct Training for Mercer in R Programming

We are back again with some awesome news! DexLab Analytics is organizing a comprehensive one-week training program for super-efficient data analytics and big data team of Mercer – a top notch multinational corporation that provides top-of-the-line solutions in Talent, Retirement and Investments worldwide.

 
We Feel Honored To Conduct Training for Mercer in R Programming
 

The training module has started from Thursday, 21st September 2017 and our in-house senior consultants are imparting cutting edge technological knowledge about R Programming to the data-hungry Mercer professionals. The training is taking place at Mercer’s corporate in DLF Phase 3, Gurgaon Office: with the rising demand of data analytics and R skills to imbibe, the advancement in the field of health, wealth and careers is witnessing a steady growth. To target a larger audience and loyal clientele base, R Programming skills need to be harnessed properly so as to flourish the future of business on a larger scale.

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How to create Chart Templates with R Functions

R functions are used to produce chart templates to keep the look and feel of the reports intact.

 
How to create Chart Templates with R Functions
 

In this post you will come across how to create chart templates with R functions – all the R users should be accustomed to the calling functions so as to perform calculations and outline plots accurately. Remember what colors and fonts to use each time: R functions are used as a short-cut for producing customary-looking charts.

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Debugging Magrittr Pipelines in R with Bizarro Pipe and Eager Assignment

Debugging Magrittr Pipelines in R with Bizarro Pipe and Eager Assignment

 

Pipes in R

Pipe, written as “%>%“ is basically an efficient operator, supplied by magrittr R package. The pipe operator is notably famous due to its wide range of use in dplyr and by the proficient dplyr users. The usage of pipe operator allows one to write “sin(5)” as “5 %>% sin“,  which is inspired by F#‘s pipe-forward operator “|>” and is further characterised by: Continue reading “Debugging Magrittr Pipelines in R with Bizarro Pipe and Eager Assignment”

How To Visualize Multivariate Relationships in Large Datasets in R Programming:

How To Visualize Multivariate Relationships in Large Datasets in R Programming:
 

In this post, we will discuss how to use the package nmle in R programming, which includes the dataset MathArchieve. To install the package and load it into your R programming environment, use the code mentioned below:

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Is Data an Asset or Liability

While many firms are stating that they leverage their data to gain valuable insights and translate them into profit. But the basic question remains whether data is an asset or a liability. This is the mind-numbing question that haunts all IT managers and must be given ample concentration on what is collected in terms of data and how can it be managed efficiently.

 

Is data an asset or liability

 

There can be two approaches to answer this question, the first being that data could be an asset if used ethically and correctly. But when no actionable insight can be gathered from data, it is a liability in the same lines as an old non-performing loan. Optimum use of data is elemental to the operations of any data driven initiative. The main reason behind this data-drive remains to be to obtain faster and better decision making abilities with more accuracy. Nowadays organizations across the board leverage their data to achieve their goals. Currently sales organizations are the frontrunners who mine their data to get the best results and maximize their revenue from already customers. Also crediting companies use their data to evaluate the risks associated with different individual debtors and then act accordingly when setting rates and fees for their loans that seem to be fair based on this information. In these scenarios the companies use real information to make decisions.

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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

 

Let’s Take Your Data Dreams to the Next Level

 

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

 

For more details on R Programming, get yourself enrolled in superior R programming courses in Pune. R programming certification in Pune by DexLab Analytics is extremely popular.

 

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Twelve Great Free R Programming E-books

To Big Data enthusiasts R is word or rather a letter that needs no introduction. R programming is a programming language that brings the complex world of statistics and datasets at your fingertips. It is mainly used for computing statistics and relevant graphics. The following twelve e-books are not only useful to bring you up to the task for R programming but best of all they are free.

 

Twelve Great Free R Programming E-books

 

  • Learning Statistics with R
    Author: Daniel Navarro

If you are looking for a guide that will take you through the intricacies of developing software with R be it the basic types and structures of data to more complex topics like recursion, closures as well as anonymous functions. Knowledge of statistics, although helpful, is not an essential pre-requisite .

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