Based on the results of the 20 lakh
students taking the Class XII exams at
Tamil Nadu over the last 3 years, it
appears that the month you were born
in can make a difference of as much as
120 marks out of 1,200.
… and peaks for
The marks shoot
up for Aug borns
120 marks out of
1200 explainable by
month of birth
June borns score
An identical pattern was observed in 2009 and 2010…
“It’s simply that in Canada the eligibility
cutoff for age-class hockey is January 1. A
boy who turns ten on January 2, then, could
be playing alongside someone who doesn’t
turn ten until the end of the year—and at that
age, in preadolescence, a twelve-month gap
in age represents an enormous difference in
-- Malcolm Gladwell, Outliers
… and across districts, gender, subjects, and class X & XII.
CARGO DELAY ADD-ON THAT PROVIDES INSIGHTS
This visualisation is part of a suite of analytical techniques we call “grouped
means” that allows us to measure the impact of every parameter (shifts,
weekdays, etc.) on any measure of interest – recovery time in this case, but this
could be extended to revenue, operational efficiency, or ability to cross-sell.
This visualisation measures the recovery time (time from
arrival of the flight until delivery), and identifies which
factors most influence the recovery time.
It allows automatically detection of
statistically significant flows and
highlights only relevant ones to users.
The system therefore analyses all
possible patterns, but users only see
the insights that matter.
Recovery times are neutral during the evening and morning shifts (mornings are slightly worse), night times are the best.
Specifically, Friday mornings are particularly bad.
So are Thursday mornings.
Recovery times are worst on Fridays, and best on Saturdays & Wednesdays.
However, RPP on Sundays is unusually slow.
The FAH product category has the best recovery time, while ZDH is much worse.
This is especially problematic for ZDH
Part shipped products tend to perform worse than full-shipments. Specifically the <20% and 40-60% part-shipments.
THE 4 EMERGING
Take one or more sources of public data, mash them up,
add analysis and visuals, and deliver the output as a
Identify a skill gap in the data science ecosystem, and
provide a platform to allow buyers to reach sellers. This
could be for data (e.g. surveys, scraping), transformation
(e.g. Hadoop processing), analysis, or visual. CROWDANALYTIX
TEMPLATISED ANALYSES Create a series of analyses that are applicable to a wide
range of domains and scenarios, and build a product that
rapidly throws out these analyses when given the data.
Enhance existing products’ big data processing ability by
integrating with a product / framework with designed with
large scale data in mind. BIZOSYS
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We handle terabyte-size data
via non-traditional analytics
and visualise it in real-time.
Gramener transforms your data into concise dashboards
that make your business problem & solution visually obvious.
We help you find insights quickly, based on cognitive research,
and our visualisations guide you towards actionable decisions.