big data challenges

CHALLENGES AHEAD& THE ROLE I HOPE TO PLAY IN THE INDUSTRY

The Value Created

By Big Data

Observed trends in Big Data

3

Rapid change in technological capability & adoption is fueling the creation of new data

BIG DATA

$600 to buy a

disk drive than can

store all of the world’s

music

GROWING SOURCES OF VALUE

GROWING SOURCES OF DATA

Source : McKinsey, Big data : The next frontier for innovation, competition and productivity

5 billionmobile phones

used in 2010

30 billionpieces of content

shared on Facebook

every month

40% projected growth

in global data generation per

year vs. 5% increase in

IT spending

60%potential

increase in

retailer’s

operating

margins with

big data

€250 billionpotential annual value to

Europe’s public sector

administration

$300 billionpotential annual value to

US healthcare

$600 billionpotential annual consumer

surplus from using

personal location data

globally

Big data as a catalyst for value creation & innovation

4

Big data provides the building blocks for sustainable improvement across industries

HOW BIG DATA

CREATES VALUE

2. ENABELING EXPERIMENTATION

3. SEGMENTING POPULATIONS

4. REPLACING/SUPPORTING HUMAN DECISION MAKING

5. INNOVATIVE NEW BUSINESS MODELS

1. CREATING TRANSPERENCY

Data transparency is an almost immediate way of creating

value in businesses across industry sectors. Though there is

much to gain from this, failure to act is often driven by a

misalignment of incentives. An example of this can be found

in the public sector, where studies found that employees

spent up to 20% of their time searching for information via

non digital means (paper archives and phone calls). They

then often physically moved to the information source to

collect it via hardware (portable flash drives). Wasted efforts

such as these can be greatly reduced by using big data to

digitize information and create efficient resources to search

through stored data.


5

HOW BIG DATA

CREATES VALUE

1. CREATING TRANSPARENCY





Experimentation leads to the discovery of needs, an exposure

to variability and an increase in performance. Through the

ability to generate real time data, management now has the

possibility to integrate scientific methodology into their

practices. The formation of control groups allows for the

formulation and testing of specific hypothesis through the

rigorous analysis of specific data. Academic research has

demonstrated that the use of data to empirically test the

adequacy of management decisions is indeed beneficial for

organizations. For example, the healthcare sector uses data

analysis techniques to determine possible explanations for

variability in treatment decisions and outcomes.




6

HOW BIG DATA

CREATES VALUE






Targeting specific consumer needs on an individual basis, be

it on the product/service or marketing level, is a well accepted

and establish concept. Today, a vast majority of large

companies segment their customers through a combination of

many attributes, such as demographic characteristics,

purchasing habits and others. However, with increase in

technological proficiency, companies can now segment in real

time. We can think, for example, of airlines using dynamic

pricing models to maximize income by better determining

customer price elasticity. Advanced use of big data can now

also be used to tailor training and ad hoc support for

employees who will most benefit from a determined allocation

of resources.




7

HOW BIG DATA

CREATES VALUE





4. REPLACING/SUPPORTING HUMAN DECISION

MAKING

Advanced data analysis can prove key in minimizing risk,

assisting decision making and bringing valuable insight to

light. Quality data is however a prerequisite for developing

algorithms that make these advances possible, which is

where big data comes into play. Such progress can add value

to countless industries, be it in manufacturing by optimizing

inventory turnover, in tax services by automatically flagging

high risk profiles for further inquiry or in insurance by

statistically minimizing risk.




8

HOW BIG DATA

CREATES VALUE





5. INNOVATING NEW BUSINESS MODELS

The insight provided by big data can lead companies to

create entirely new products or services to meet a demand

that up to that point was misunderstood. Information gleaned

from data analysis can also be used to heighten existing

products and services. For example, retailers are presently

using data generated from sensors imbedded in products in

order to proceed to proactive maintenance, or the practice of

doing maintenance work before a failure happens or is

noticed. Data accessibility also profits directly to consumers in

areas such as price transparency, allowing prices to be

compared in real time, greatly adding to consumer surplus.




The Challenges

Ahead For Big Data

Challenge 1 : Dealing with increasing volume

A key hypothesis behind the value of big data is that it can processed efficiently

DATA VOLUME DATA SECURITYDATA VARIETY

Source : IDC storage reports, McKinsey Global Institute Analysis

>3500

North

America

>50

South

America

>200

Middle

East &

Africa

>2000

Europe>250

China

>400

Japan

>400

Rest of

APAC

>400

India

Amount of new data stored across geographies in 2010, in Petabytes

Given the extraordinary rate at which new data is be generated, governments and corporations

will be hard pressed to match the pace when it comes to spending in key IT areas needed to

analyse the raw material provided by big data. Only with the capacity to make sense of data is it

possible to gain useful insights.

THE

CHALLENGE

1 Petabyte is

equivalent to a thousand

terabytes

235 terabytes of data

collected by the US Library of

Congress by April 2011

15 out of 17 sectors

in the US have more data

stored by company than the

US Library of Congress

10

Challenge 2 : Interpreting a fast growing portfolio of data formats

With new technology comes new types of data, pressing for comprehensive analysis


Along with the development of new technological mean comes the emergence of new types of

data formats. A trend has emerged in the form of increasing data variety, leading to a greater

comprehensiveness in the analytical approach used to interpret the raw material itself. At the

most fundamental level, data is only as useful as the interpretation of the it’s meaning.

THE

CHALLENGE

Table

Data Base

Web140,000 – 190,000more deep analytical talent

positions needed

1.5 million more data-

savvy managers needed to take

full advantage of big data in the

United States

Data

Va

rie

ty

Source : IDC storage reports, McKinsey Global Institute Analysis, Data Science Central

11

Challenge 3 : Keeping sensitive data secure

Assessment of security risks and mitigation strategies must continually be reviewed


Data security is ultimately a continual iterative processes. New means for sharing and storing

data are created, and securitization protocols and methods must be development post hand. In

a very similar way, data theft is accomplished by adapting to change faster that security

measures. In a rapidly evolving environment, this issues continues to grow in importance.

THE

CHALLENGE

Assess Set Policies & Controls

Monitor & EnforceMeasure

Data Security Lifecycle

12

Where I See

Myself Fitting In

My post MSc career objectives

14

I perceive IE’s MSc program as a great lever to attain my professional ambitions

GOALS

Start my

own

business

Become

an IT

Consultant

Act as CIO

for a

start-up

As stated by the School itself,

IE promotes it’s MSc in

Business Analytics and Big

Data as being "A world of

exciting opportunities ". This is

perfectly aligned with how I see

my career evolving.

15

Annexe

Sources

https://www.mapr.com/blog/top-10-big-data-challenges-%E2%80%93-serious-look-10-big-data-

v%E2%80%99s#.VLqePCvF-hk

http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/

http://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data

http://www-01.ibm.com/software/data/security-privacy/

http://www.itbusinessedge.com/slideshows/top-data-protection-predictions-for-2014-02.html

http://www.dataguardstore.com/

Below are other sources used in the construction of this presentation

16

https://www.mapr.com/blog/top-10-big-data-challenges-%E2%80%93-serious-look-10-big-data-v%E2%80%99s#.VLqePCvF-hk

http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/

http://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data

http://www-01.ibm.com/software/data/security-privacy/

http://www.itbusinessedge.com/slideshows/top-data-protection-predictions-for-2014-02.html

http://www.dataguardstore.com/

big data challenges

Technology

productivity big data

stored data

use of data

data analysis techniques

real time data

global data generation

creation of new databig

potential annual value