Big data is like teenage sex: everyone
talks about it, nobody really knows how to do it,
everyone thinks everyone else is doing it, so
everyone claims they are doing it.
“
” Dan Ariely
Professor at Duke University
Byte = 1 grain of rice
Kilobyte = 1 cup of rice
Megabyte = 8 bags of rice
Gigabyte = 3 trailers of rice
Terabyte = 2 container ships
Petabyte = blankets Manhattan
Exabyte = blankets west coast states
Zettabyte = fills the Pacific Ocean
Yottabyte = AN EARTH SIZED RICE BALL!
There were 5 Exabytes
of information created
between the dawn of
civilization through 2003,
but that much information
is now created every 2.
“
”Eric Schmidt
Executive Chairman at Alphabet Inc.
Former CEO of Google
VARIETY
Different types of
data we can use,
both structured and
unstructured.
Sensors Photos
Voice
Recordings
Social Media
Conversations
Messages
Video
Capital One - harnessing behavioral data to
shape customer offerings. For instance, their
deal optimization engine analyzes customer
demographics and spending patterns to
determine how, where and when to put offers
in front of people – leading to more revenue
for Capital One and a more positive experience
with the brand for customers.
T-Mobile managed to reduce "churn" by
50% just by staying on top of things like
usage patterns, geographical usage trends,
customer purchases by location and most
importantly, Customer Lifetime Value. T-
Mobile has banked on the fact that
customers with strong social networks can
influence others' telecomm decisions,
making a point of identifying its most
influential customers and giving them perks.
Free People uses millions of customer
records (reviewed by an in house
analytics team) to shape the next
season's offerings. Information like
what sold, what didn't, what was
returned and more fuels the brand's
product recommendations, the look of
its website and what kinds of
promotions customers see to improve
Free People's bottom line.
Starbucks' ability to
maintain a surprising
number of locations in
close proximity to one
another is a function of big
data. The fact that two
Starbucks can exist a
block away from one
another isn't luck; they
were placed in their
adjacent locations thanks
to location-based data,
street traffic analysis,
demographic info and data
culled from other
locations.
#1 Optimize Business Processes
The big objective - creating
predictable models. Retailers are
able to optimize their stock and
delivery routes optimize using
data from geographic positioning
and RFIDs.
#2 Improving Healthcare
We can find new cures and
better understand and predict
disease patterns or we can use
all the data from smart watches
and wearable devices to better
understand links between
lifestyles and diseases.
#3 Improving Cities and Countries
Big data can improve many
aspects of our cities, such as
optimizing traffic flows based on
real time traffic information as
well as social media and weather
data.
Uber - the reason Uber is so “frictionless” is
that when you are done with your ride, you just
get out of the car. No cash, no credit cards, no
signing receipts (or hassles over requesting
receipts).
Square - with this
small, square plastic
device that plugs into
any smartphone or
tablet, any business
can now set up an
account to process
credit and debit cards
and then sweep the
proceeds directly into
their bank account.
Amazon – its mobile app leverages
the best of all that Amazon has
done on desktops and laptops for
the last 15 years
#1 Optimize Mobile Check-out
Mobile commerce
conversion rates are still
low due to shoppers
giving up on the process
when it becomes too
hard to finalize an order.
#2 Create a holistic mobile approach
For retailers, the money is in the
mobile Web, not the app
The challenge is how to apply analytics for deeper
consumer insights, while maintaining the highest levels
of security and individual privacy.
“
”
Diarmuid Mallon
Direct of Global
Marketing Solutions at SAP
Example of EU Framework
Data controllers
transparency
Clear info on
Data processing
Data protection in 3rd
party transfers
24h for data disclosure
in case of breach