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About me. Educational background – Applied Econometrics 4 years statistical modelling experience R experience – 2 years Currently Senior Analyst at Deloitte Hobby – rock climbing , data mining competitions Why? - Early retirement Current interest – Text analytics .

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About me
About me

  • Educational background – Applied Econometrics

  • 4 years statistical modelling experience

  • R experience – 2 years

  • Currently Senior Analyst at Deloitte

  • Hobby – rock climbing, data mining competitions

  • Why? - Early retirement

  • Current interest – Text analytics


Topic: The benefits of R from a data mining competitor’s point of view and from the point of view of an employee at Deloitte

  • Work

  • Professional and pragmatic

Home

The playful scientist


Agenda
Agenda point of view and from the point of view of an employee at Deloitte

  • Quick introduction to R

  • What I use R for

  • R at work

    • Introduction to Deloitte

    • Frequently used tools

    • Some of the work we do using R

    • Examples

    • Challenges: Data Storage

    • Challenges: Standardisation

    • How Deloitte is addressing this issue

  • R at home:

    • Some of the work I do using R, at home

    • Flexibility and convenience

    • Examples

    • Prototyping and experimenting

    • Examples

  • Questions

  • Essential R packages for everyday use


  • Quick introduction to r
    Quick introduction to R point of view and from the point of view of an employee at Deloitte

    • “A statistical software created by statisticians, for statisticians”

    • Personally, I use R for data analysis and statistical modelling

    • Unique features worth noting:

    • Open source – free, easy to find help in the active community

    • Understands mathematical computations and matrix operations naturally

    • Thousands of packages, implementations of almost any algorithm


    Introduction to r thousands of packages implementations of almost any algorithm
    Introduction to R point of view and from the point of view of an employee at DeloitteThousands of packages, implementations of almost any algorithm

    Packages

    ggplot2

    EBImage

    randomForest

    etc

    N = 500+


    • R at work point of view and from the point of view of an employee at Deloitte


    Introduction to deloitte
    Introduction to Deloitte point of view and from the point of view of an employee at Deloitte

    • We help clients capture, manage and analyse data to help solve important business problemsto make informed decisions

    • A holistic process of data mining


    Introduction to deloitte typical activity involved in a project at deloitte
    Introduction to point of view and from the point of view of an employee at DeloitteDeloitte: Typical activity involved in a project at Deloitte

    But not everything is R

    Data preparation

    Level of Activity

    Modeling

    Planning

    processes

    Data loading

    Closing

    processes

    20% - 40% time spent on modelling

    Initiating

    processes

    Time line


    Frequently used tools
    Frequently used tools point of view and from the point of view of an employee at Deloitte

    • Geospatial analytics - Tactician

    • Segmentation - Self Organising maps

    • SQL server

    • Modelling

    • Visualisation


    Some of the work we do using r
    Some of the work we do using point of view and from the point of view of an employee at DeloitteR

    • In Deloitte

    • Statistical Analysis and Predictive modelling

    • Time series analysis

    • Social Network Analysis

    • Data visualisation

    • Text analytics (NEW!)


    Examples time series
    Examples: Time Series point of view and from the point of view of an employee at Deloitte

    Actual

    --- Estimate

    y – retail activity?

    Fitted

    Time (days)

    R package:

    forecast


    Challenges data storage
    Challenges: Data point of view and from the point of view of an employee at DeloitteStorage

    • We have a dedicated tool to store and clean data – SQL

    • R cannot handle large data sets

    Error: cannot allocate vector of size 2097151 Kb


    Challenges standardisation
    Challenges: Standardisation point of view and from the point of view of an employee at Deloitte

    • ‘You’re not the only one using it”

      One of the reason’s why other commercial tools are preferred over R

    • Transferable skills across the team

    • Reliability of packages

    • Standardised functions and procedures


    How deloitte is addressing this issue
    How Deloitte is addressing this issue point of view and from the point of view of an employee at Deloitte

    • Creating standardised process:

    R package:

    RODBC


    How deloitte is addressing this issue1
    How Deloitte is addressing this issue point of view and from the point of view of an employee at Deloitte

    • Creating standardised functions:

    • # Density Plot for subject variable

    • DensityPlot <- function(dataset, col) {

    • ds <- data.frame(dataset);ds$c<- ds[,c(col)];a <- ggplot(data=ds, aes(x=c) )

    • a <- a + geom_density(kernel="biweight");a

    • }

    • DensityPlot (dataset, column number)

    • Retrieving data from the database (RODBC):

    • conn <- odbcDriverConnect("driver=SQL Server; database=DataBaseName; server=servername;")

    • query <- “Select * from TableName”

    • df<- sqlQuery(conn,query)

    R package:

    RODBC


    • R at home point of view and from the point of view of an employee at Deloitte


    Some of the work i do using r at home
    Some of the work point of view and from the point of view of an employee at DeloitteI do using R, at home

    At home (data mining competitions)

    • Statistical analysis and Predictive modelling

    • Time series analysis

    • Social Network Analysis

    • Data visualisation

    • Text analytics

    • Image analysis

    • (I mainly use R)

    • In Deloitte

    • Statistical Analysis and Predictive modelling

    • Time series analysis

    • Social Network Analysis

    • Data visualisation

    • Text analytics (NEW!)

    • (we don’t just use R)


    Flexibility and convenience
    Flexibility and convenience point of view and from the point of view of an employee at Deloitte

    • Is one of the easier programming languages to pick up

    • Dive into the analysis quickly


    Examples
    Examples point of view and from the point of view of an employee at Deloitte

    • Image analysis

    R package:

    EBImage


    Examples1
    Examples point of view and from the point of view of an employee at Deloitte

    • Image Analysis

    R package:

    EBImage


    Prototyping and experimenting
    Prototyping and experimenting point of view and from the point of view of an employee at Deloitte

    • Access to the latest most innovative techniques

    • Great for prototyping new algorithms


    Examples text analytics
    Examples: point of view and from the point of view of an employee at DeloitteText analytics

    R package:

    twitteR

    +


    Examples word cloud of twitter feeds
    Examples: Word cloud of twitter feeds point of view and from the point of view of an employee at Deloitte

    R package:

    wordcloud


    Examples text analytics1
    Examples: point of view and from the point of view of an employee at DeloitteText analytics

    What are the common themes that are being tweeted by Time magazine?

    +

    =

    ?


    A point of view and from the point of view of an employee at Deloitte

    Top words associated to the classification

    Tweet

    B

    C

    D

    A

    B

    C

    D

    R package:

    ggplot2


    Classification results
    Classification results point of view and from the point of view of an employee at Deloitte


    Questions
    Questions? point of view and from the point of view of an employee at Deloitte


    Essential r packages for everyday use
    Essential R packages for everyday use point of view and from the point of view of an employee at Deloitte

    • Essential

    • ggplot2

    • reshape

    • RODBC

    • randomForest

    • rpart

    • Nice to have

    • caret

    • forecast

    • tm


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