from data analytics to big data

25
from business analytics to an overview from telecom data scientists Ph.D. Ismail REBAI, Analytical CRM & BI Director Ines TEACĂ, BI Project Manager April 23 rd , 2013

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Page 1: From data analytics to Big Data

from business analytics to

an overview from telecom data scientists

Ph.D. Ismail REBAI, Analytical CRM & BI Director

Ines TEACĂ, BI Project ManagerApril 23rd, 2013

Page 2: From data analytics to Big Data

2

agenda

general overview of Big Data

telecom industry

big data at Orange France. Portal use case.

the data scientist

Page 3: From data analytics to Big Data

3

big data overview

Page 4: From data analytics to Big Data

4

big data is everywhere

Cell phone, texts, digital, music and movies

Financial markets and services

Real time traffic

Security and automation

Biomedical research and personal health

Weather and climate

Air traffic

Data Analytics

People

Cloud Devices

Network Ecosystems

CDRs

!

Page 5: From data analytics to Big Data

5

big data definition

big

data

3V’s

or

collaboration opportunity?

Page 6: From data analytics to Big Data

6

with Big Data, business is back in control of data

Mainframe Standalone

PC

Connected

PC

Connected

PC

Mobile

20102000199019801970

Data

Ownership

IT

Business

Page 7: From data analytics to Big Data

7

big data market. explore opportunities

The Hadoop-MapReduce market is

forecast to grow at a compound annual

growth rate (CAGR) 58% reaching $2.2

billion in 2018.

2012 Big Data Market had a clear actors

ranking with IBM, HP and Teradata.

Verizon is the only telecom pioneer in

the Big Data innovation context as listed

by the media. Source: http://wikibon.org/wiki/

Page 8: From data analytics to Big Data

8

telecom industry

Page 9: From data analytics to Big Data

9

in telecom. data increased a thousand-fold in the past 20

years

Orange presentation

Figure 1: Data volume on telecoms networks, worldwide, 1986–

2013 [Source: Analysys Mason, 2013]

Figure 2: Data on telecoms networks by type,

worldwide, 1990 and 2010 [Source: Analysys

Mason, 2013]

97%

3%

1990

2%

98%

2010

Analogue

Digital

Page 10: From data analytics to Big Data

10

telecom data monetization. exploration phase

Orange presentation

Telefonica Dynamic Insight (TDI) was launched on 9th October 2012

Focus to become analytical insight provider for companies and public sector organizations.

TDI Target: R&D, venture capital, digital service development and global partnership.

Processing: separate divisions and business units for Telefonica innovation activities

Precision Market insight division was launched on 1st October 2012

Focused to monetize collected customer data

In addition to basic data VERIZON used also geographic location, apps downloaded and web sites accessed.

Smart Steps

Outdoor Media Measurement

Venue Audience Measurement

Retail site analytics

PRIVACY

Page 11: From data analytics to Big Data

11 Orange presentation

telecom Orange France

use case

Page 12: From data analytics to Big Data

12

orange portal. a success story based on big data

platform

an innovation nominee for Orange Innovation Awards 2013

a «fast adopter» using as foundation open source technologies.

DMGP Orange France

Orange Labs Product and Services

http://www.orange.fr/portail

Page 13: From data analytics to Big Data

13

the project setup

Orange presentation

building a Big Data platform to extract value from 50 million customers usage data and offer better personalization applying mass predictive models

1st Orange Big Data service success story

Project foundation based on

open source

Direct impact on

digital contents business

Anticipation of Data Science

& Scientist need!

• industrialization and

experimentation (treatment of

100% anonymized usage

customer logs)

• Khiops, Orange Labs Data

Mining environment connected

to the open source

environment

a platform to distribute high

volume data computations on a

set of PC (Hadoop)

a high availability data

service to deliver customer

data to all Orange web services

• Improved customer

experience and click rates

using better targeting

• Reuse of highly available

data service of the Portal to

fill and answer anonymous

profiles for decision making

Page 14: From data analytics to Big Data

14

the data scientist

Page 15: From data analytics to Big Data

15

a data science team transformation phases

Orange presentation

description : several teams

with different data skills are

dealing with their own data

projects

storage location : each team is

storing and dealing with its

own data

Phase 1

description : one team is

ahead of the other teams and

has developed more data

skills

storage location : each team is

storing and dealing with its

own data

Phase 2

description : team 3 becomes

the data service providers of

the group and provide

dedicated services when

required to all BU teams (as a

service center)

storage location : all data are

centralized and stored in the

same data storage

infrastructure

Phase 3

Team 1

Team 3

Team 2

Team 4

decentralized data

Team 1

Team 3

Team 2

Team 4

decentralized data

Team 1

Team 3 – service

provider

Team 2

Team 4

centralized data

Business Units: Business Units:Business Units:

Page 16: From data analytics to Big Data

16

the data scientist or data science team?

Datamining and data transformation

Mathematics, statistics, econometrics and BI

General techniques: platform administrator, database administrator

Specific techniques: ETL, CEP, open source solutions (Hadoop…)

Legal

Business (marketing/sales)

Communication

Page 17: From data analytics to Big Data

17

from data to big data

Page 18: From data analytics to Big Data

18

(big) data analytics. are we there yet?

http://www.youtube.com/watch?v=LrNlZ7-SMPk

movie

Page 19: From data analytics to Big Data

19

big data in Romania. today

via Google Trends as seen on 18 April

Page 20: From data analytics to Big Data

20 Orange presentation

the data scientist

Page 21: From data analytics to Big Data

thanks

More questions?

Ismail.Rebai at orange.com

Ines.Teacă at orange.com

Page 22: From data analytics to Big Data

22 Orange presentation

appendix

Page 23: From data analytics to Big Data

23

big data routine for searching a data scientist

C l a s s D a t a S c i e n t i s t {

I s s k e p t i c a l , c u r i o u s . H a s i n q u i s i t i v e m i n d

K n o w s M a c h i n e L e a r n i n g , S t a t i s t i c s , P r o b a b i l i t y A p p l i

e s S c i e n t i fi c M e t h o d .

R u n s E x p e r i m e n t s

I s g o o d a t C o d i n g & H a c k i n g

A b l e t o d e a l w i t h I T D a t a E n g i n e e r i n g

K n o w s h o w t o b u i l d d a t a p r o d u c t s

A b l e t o fi n d a n s w e r s t o k n o w n u n k n o w n s

T e l l s r e l e v a n t b u s i n e s s s t o r i e s f r o m d a t a

H a s D o m a i n K n o w l e d g e

}

Page 24: From data analytics to Big Data

24

big data. ecosystem

Page 25: From data analytics to Big Data

25

Vincent Granville

DJ PatilJeff

HammerbacherMok Oh

Daniel Tunkelang

data scientists

Former LinkedIn

Scientist

Current Data

Scientist @

Greylock

Former Facebook

Current Chief

Scientist @ Cloudera

Former PayPal

Chief Scientist

Current

Entrepreneur

Analytic Bridge,

Data Science

Central

Data Science

Director @

LinkedIn