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Presentation on Big Data
Transcript of Presentation on Big Data
Big Data paradigm
needs a full new IT architecture:
architecture (10 000 servers)
massive parallel processing
Text-analysis, Voice recognition capacities
(statistics, discovery, exploration)
Decision tools (Trees, Pro-Con analysis, Rule-based, Neural Network, Tradeoff-based )
Specific tools for
real time data
...still needs specific skills: 'data scientists' from fields like statistics, modeling, machine learning, linguistics, design experiments, and more.
by Corina Ciechanow, 2013 firstname.lastname@example.org
Introduction to Big Data
Data means Business
McKinsey and MIT 2012 survey: revenues of data-exploiting companies
increased more than 5%
It is a fundamental transformation in all sectors of the economy.
The New business of Data
Dorothee Belz, VP Legal and Corporate Affairs at Microsoft Europe said this month at IAMCP :
"The new business is Data"
Storing it (Cloud)
Extracting, Transforming, Analyzing it (Big Data)
Selling it (users behavior)
Creating new business with it
From Intuition to
We can make better predictions, that leads to smarter decisions than before.
Big Data means a mentality change on the decision-making culture, from '
What do you
' to '
What do you
It is a
Data is Everywhere
... to data-driven
Big Data Players
Big Data = BI + 3 'V's
Big Data Issues
Senior Executives and expensive Consultants (the
pinion) use their experience or 'hunch' where no data is available.
There are cognitive bias that have an impact on the Key Performance Indicators:
the Overconfidence bias
the Availability heuristic bias
the Status-quo bias
Decision-makers & Managers have to learn to formulate questions:
What do the data say?
Where do data come from?
How confident are we?
... and be ready to override their intuition.
That implies changing our perceptions and beliefs on
the value of experience
the nature of expertise
the practice of management
Big Data is
where the volume goes beyond the capacities of traditional data management software (Database/
Datawarehouse), when it is unstructured, in different formats or when it is disperse.
olume, subjective measure
ariety of sources and formats
elocity, the speed of data creation or data validity
Objective --> To find patterns, anomalies, models, to predict, to personalize
kilobyte (kB) = 10^3
megabyte (MB) = 10^6
gigabyte (GB) = 10^9
terabyte (TB) = 10^12
petabyte (PB) = 10^15
exabyte (EB) = 10^18
zettabyte (ZB) = 10^21
1 petabyte = 1 million gigabytes
1PB = 1 000 000 GB
1 exabyte = 1 thousand petabytes
1EB = 1 000 PB
Validation, Veracity, Quality
Correlation versus Causation
Data protection, Data privacy
Making it clear --> visualization
Predicting natural catastrophes
Dacom Agri Yield Mgt
Network analysis tools:
Cost of 5Gb
1975 --> 100 000 000 $
1990 --> 50 000 $
1995 --> 5 000 $
2000 --> 50 $
2005 --> 5 $
2012 --> < 0,5 $
Disclaimer: The data/logo/marks of organisations are used here merely for reference and used in good faith with no intention to infringe the intellectual property rights of the organizations.
Big Data is
a DO or DIE Business Case
THE new business
a MANAGEMENT REVOLUTION
a new PARADIGM
because as new system of knowledge it can change the very meaning of learning and experience
From Euro Beinat's presentation on Collective Sensing at NEXT Berlin 2011
Thanks, Wikipedia :-)
2.5 exabytes (10 000 US Library of Congress)
created each day,
more data each second than what was stored 20 years ago
and growing 40% per year from:
Internet of Things (sensors and
machines via RFID,Bluetooth,SIM..)
...and also keeping track of our behavior!
Source: HBR, October 2012, A.McAfee & E.Brynjolfsson
Source: HBR, October 2012, M.Maubassin
SME: use Crowdsourcing