DT Brown Bag 2.0: A Primer in Analytics

WELCOME! !

November 2013

Outline•EAT, Guten Appetit, Bon appetit, Buen apetito, Buon appetito!!!

•What’s new with DT Analytics?•What’s new?•About Shiny:•About us!

!!•Case Studies:•Discontinuities and Shiny (Shrayes R.) •Data Science in Afghanistan (Adam VE.)

!!

Whats new: Cyber IR&D21 days (October 1 - 21)!Primary Goal: Be unique! !Primary Dataset: 42 jihadi forums!Plus design specific passive collection efforts:

- Honeypots- TOR logs !

Methods: Discontinuities, Network Analysis, and Topic Models.!New IR&D launches in ~ three weeks.

https://portal.data-tactics-corp.com/sites/analytics/Shared%20Documents/cyber.pdf

Whats new: Open Source!R + Accumulo = RAccumulo!!Description: Functions to create and delete Accumulo tables and read/write/scan rows from Accumulo tables

License: Apache License (== 2.0)!library(raccumulo) !?raccumulo !https://github.com/DataTacticsCorp/raccumulo

18 Program Managers, 3 Data Scientist, 1 Marty, 3 hours DS4PM = Data Science for Program Managers !Goals: !1: Define the Analytics Team within Organization Structure2: Improve poorly developed notions of analytics3: Outline optimal interactions with Analytics Team4: Explain common steps for Data Science !5: Most importantly, develop a taxonomy to identify analytical questions one could ask of data to aid future business engagements.

https://portal.data-tactics-corp.com/sites/analytics/Shared%20Documents/DS4PM.pdf

Whats new: DS4PM

http://www.meetup.com/Data-Science-DC/events/146953142/

Whats new: LUBAP goes wild!359 attending!

ShinyOpen Sourced by RStudio in November 2012!Not the first to wrap R in the browser but perhaps the easiest for R developers !Dont need to know HTML, CSS and javascript to get started !Reactive Programming model !Web sockets for communication !!

server.R# Define server logic required to generate and plot a random # distribution!shinyServer(function(input, output) {! ! # Expression that generates a plot of the distribution.! # renderPlot:! #! # 1) Is "reactive" and therefore should be automatically ! # re-executed when inputs change! # 2) Its output type is a plot ! #! output$distPlot <- renderPlot({! ! # generate an rnorm distribution and plot it! dist <- rnorm(input$obs)! hist(dist)! })! !})

ui.Rlibrary(shiny)!!# Define UI for application that plots random distributions !shinyUI(pageWithSidebar(! ! # Application title! headerPanel("My Shiny App!"),! ! # Sidebar with a slider input for number of observations! sidebarPanel(! sliderInput("obs", ! "Number of observations:", ! min = 0, ! max = 1000, ! value = 500)! ),! ! # Show a plot of the generated distribution! mainPanel(! plotOutput("distPlot")! )!))

Hello World

headerPanel()

sidebarPanel()

mainPanel()

About us...

server.R,ui.R = microscope

adjustable parameters (knobs): 0 < knobs < small k knobs = lighting, varying objectives, focusing (fine and course) !

knobs fine and course filtering:

geographytimevariable of interest observations of interest

promotion of significant (objective) patternschange model parameters

https://dell.data-tactics-corp.com/cloudCore/apps/cyber

Whats new: BDE + Shiny

Analytical Resources:

https://portal.data-tactics-corp.com/sites/analytics/Shared%20Documents/kesnypaper-3.pdf

Thank you...

!15

Questions?

Homepage: http://www.data-tactics.comBlog: http://datatactics.blogspot.comTwitter: https://twitter.com/DataTactics

Or, me (Rich Heimann) at rheimann@data-tactics-corp.com