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I quite like Google’s monthly email on account activity. It is the Google way to offer free services, as well as treat users as special, that continues to command loyalty despite occasional exasperation with corporate thingies.
See this dashboard-
The medium range font shows persons sent/from statistics, and the color shades are done to empahsize or de-emphasize the metric
Colors used are black/grey, green and blue coincident with the Corporate Logo.
However some of the JS for visualizations need to be tweaked. Clearly the hover script ( an integral part of Dashboard design ) needs better elucidiation or formatting)
I would also venture my neck and suggest that rather than just monthly snapshots, atleast some way of comparing snapshots across periods or even the total time period be enabled- rather than be in seperate views. This may give the user a bit more analytical value.
Overall, a nice and simple dashboard which may be of some use to the business user who makes or views a lot of reports on online properties. Minimal and effective- and in keeping with Open Data- Data Liberation Principles. I guess Google is secure in the knowledge that users do not view time spent on Google services as a total waste , unlike some of the other more social websites they spend time on.
UPDATED- Here are three great examples of a visualization making a process easy to understand. Please click on the images to read them clearly.
1) It visualizes CRISP-DM and is made by Nicole Leaper (http://exde.wordpress.com/2009/03/13/a-visual-guide-to-crisp-dm-methodology/)
2) KDD -Knowledge Discovery in Databases -visualization by Fayyad whom I have interviewed here at http://www.decisionstats.com/interview-dr-usama-fayyad-founder-open-insights-llc/
and work By Gregory Piatetsky Shapiro interviewed by this website here
3) I am also attaching a visual representation of SEMMA from http://www.dataprix.net/en/blogs/respinosamilla/theory-data-mining
- Copy an idea from existing product. Make worse interface, but give more freebies. Do not charge money ( or charge vastly reduced ). Launch without warning.
- Write a blog post every three month on the launched product
- Watch product lose money as they did not charge any/some money to begin with.
- Close the product down without warning.
Only the Linux version of the updated package is here , but for Windows users (like say 80% of the USERs) you can just source the 2 R files within the package sub structure after unzipping the downloaded tar.z file TWICE. The package takes care of taking you to the correct link for authentication after the line access_token <- query$authorize(), you need to
1) sign in to your Google account
2) click grant access (blue button)
3) click exchange tokens (blue button)
4) paste the access token at the prompt specified within the R console
access tokens stay active for 3600 seconds !
library(rjson) library(RCurl) source('C:\\Users\\KUs\\Desktop\\RGoogleAnalytics_1.2.tar\\RGoogleAnalytics\\R\\QueryBuilder.R') source('C:\\Users\\KUs\\Desktop\\RGoogleAnalytics_1.2.tar\\RGoogleAnalytics\\R\\RGoogleAnalytics.R') query <- QueryBuilder() access_token <- query$authorize()
ga <- RGoogleAnalytics() ga.profiles <- ga$GetProfileData(access_token) ga.profiles query$Init(start.date = "2012-06-18", end.date = "2012-12-18", dimensions = "ga:date,ga:pagePath", metrics = "ga:visits,ga:pageviews,ga:timeOnPage", sort = "ga:visits", #filters="", #segment="", max.results = 99, table.id = paste("ga:",ga.profiles$id,sep="",collapse=","), access_token=access_token) # 4. Make a request to get the data from the API ga.data <- ga$GetReportData(query)# 5. Look at the returned data head(ga.data)
Interested in using R for Web Analytics? Use it from here http://code.google.com/p/r-google-analytics/
Great work by the Google team (Michael Pearmain et al) and Tatvic team working together!
It all started because of the Google Guy, Hal Varian
|Feb 25, 2009 – I keep saying the sexy job in the next ten years will be statisticians. … Hal Varian, The McKinsey Quarterly, January 2009. …|
Then these guys ( Thomas H. Davenport and D.J. Patil) made us sexy -that too in the Harvard Business Review.
She says here-
If the importance of data scientists is growing with the advent of big data, the sooner we understand what exactly it is they do, the better.
That is fair enough. But to add grievous injury to data scientists, She adds
(For fun I wrote a blog post on being a data scientist’s girlfriend.)
Actually the blog post was-Why I Wouldn’t Have Sex with a Data Scientist
But there’s no use. The data scientist is preoccupied. Preoccupied with finding, accessing, analyzing, validating, cleansing, integrating, provisioning, modeling, verifying, and explaining data to his management, colleagues, end-users, and friends.
And this is the year of the statistician ??
This is bare knuckles tactics. The art of Vaseline Insulting? Perish the thought. Geeks and Data Scientists rule.
Dont we? and we are perfect? right.
We statisticians (and data scientists and big dataists and data miners and business analysts and …)
are bringing sexy back!