1.
Los datos hablan.
El impacto de Big Data en la Sociedad y la Economía
Dr Pedro A. de Alarcón
Senior Data Scientist. External Positioning
and Big Data for Social Good

2.
@LUCA_D3
1. Let Data Speak
2. ¿Qué está haciendo Telefónica?
3. Algunas ideas para durante y después del Máster
4. … y un buen ejemplo.

3.
@LUCA_D3
@LUCA_D3
@pdealarcon

4.
¿Qué está pasando?... Adapt or Die
@LUCA_D3

5.
@LUCA_D3
Let Data
Speak01

6.
Are you listening?
@LUCA_D3
Using CDR traffic to understand the impact of an earthquake in Mexico

7.
Are you listening?
@LUCA_D3
Using sports analytics software to understand footballer behaviour
Xavi: movements
faster than 5
m/sec
Messi:
movements
faster
than 5 m/sec
Time at each position sec.

8.
Big Data for Football Analytics
@LUCA_D3
Time at each position sec.

9.
Open Data for Customer Benefit
@LUCA_D3
Using open data to provide automated Oyster refunds in London

10.
Open Data for Marketing and Brand Awareness
@LUCA_D3
Using open data as an input for a real-time advertising campaign in London

11.
Big Data is no longer an emerging technology…
@LUCA_D3
“We’ve retired the Big Data hype cycle. I know some clients may be really surprised by
that because Big Data was a really important one for many years.” Betsy Burton, Gartner

12.
Tools and Infrastructure
@LUCA_D3
Difficulty
Value
Descriptive
Analytics
Diagnostic
Analytics
Predictive
Analytics
Prescriptive
Analytics
What
happened?
Why did it
happen?
What will
happen?
How can we
make it happen?
Source, Gartner 2012
Volume Velocity
Variety
3 Vs of
Big
DataTerabytes
Records
Transactions
Tables / Files
Batch
Real-time
Streams
Near-time
Structured
Unstructured
Semi-structured
All of the above

13.
Data Science
@LUCA_D3
“Data Scientist is the sexiest job in the 21st century.”
“Big Data expertise demand has increased by 85% in the last year.”
“21.000 Data Engineer jobs posted online.”
“90.000 Data Engineer jobs posted online.”

14.
@LUCA_D3
¿Qué está haciendo
Telefónica?02

15.
We have launched LUCA Data-Driven Decisions
@LUCA_D3
Our goal: to empower other organizations to become more data-driven

16.
The Big Data journey has different maturity stages
@LUCA_D3
• Interested in understanding
potential of Big Data
• Keen to run POCs
• Lack of internal know-how
and capabilities
• Data sources unknown /
uncontrolled
• Strategy and uses cases not
defined
Exploration
Data-Driven
• Big Data already
implemented in a “data-
centric” organization
• Data is intrinsic in decision-
making
• Data brings organization
closer to its customers
• In-house expertise in data
science and data
engineering
• External data sources used
regularly to generate richer
insights
• New data-driven business
models and processes in
creation
Transformation
• Decision made to leverage
Big Data
• Require methodology and
expert resources
• Need technology and
infrastructure
• Analytics capabilities to be
deployed / outsourced
• End-to-end transformation
programme planned,
including cultural and org.
changes

17.
And this is Telefonica’s Big Data journey – so far
@LUCA_D3
2011 20132012
Exploration
proving Big Data’s
potential
Smart Steps launched
SNA pilots marketing and churn
Global BI organization created
Data to become an asset
20152014
Transformation
accelerating adoption
Smart Digits launched
China Unicom Joint Venture
Smart Steps International roll out
Key use cases executed
Strategic data sourcing installed
20172016
Data-Driven
democratizing Big Data
Big Data B2B unit launch
Niche Big Data consultancy acquired
Cultural transformation
CDO (Chema Alonso) appointed
Breaking all kinds of silos
Big Data roadmap for each
Operating Business
New data-driven P&S

18.
These are the components to work on during the journey
@LUCA_D3
Data
Engineering
Tools &
Infrastructure
Data
Science
Business
Insights
Strategy and Transformation
(Strategic Assessments, Corporate Transformation Programmes, Culture and Talent programmes)
End 2 End Security Wrap

19.
Data Engineering – more data sources
@LUCA_D3
Big DataData Warehouse
+ External DataGeolocation
Call Centre Content
Channels (online & offline)
TV Audiences
Q of E
Sociodemographic
Products and Services
Consumption
Customer
Web Logs
Descriptive
WHO ?
Behavioral
WHAT, WHERE ?
Interaction
HOW ?
Attitudinal
WHY ?

20.
All of which is applied to the Business
@LUCA_D3
Product and
Innovation
Operational
and Finance
Channels
Sales and
Marketing
Network and
Infrastructure

21.
Business
optimisation
which have allowed us to create value internally:
@LUCA_D3
Smart
Marketing
Churn
Reduction &
Optimisation
Network
Planning
Optimization
Real Time
contextual campaigns
Video analytics
A
Data-Driven
Online channel
E2E churn
approach
Multi-channel analytics
Fibre/LTE deployment
Supply/demand
analysis
Value based analysis
Procurement
analytics
Fleet management
optimisation

22.
Business Insights for Sustainable transport
@LUCA_D3
Using mobile data to measure the sustainability of commuting in Barcelona

23.
Business Insights for Tourism Insights
@LUCA_D3
Using mobile data to understand the catchment and profile of tourists to the Fallas Festival

24.
Business Insights for Tourism Insights
@LUCA_D3
Using mobile data to understand the catchment and profile of tourists to Spain

25.
Business Insights for Smarter Communication
@LUCA_D3
Using analytics to optimize global communications in multinationals

26.
Big Data for Social Good
@LUCA_D3
Using CDR traffic to understand the impact of floods in Mexico

27.
@LUCA_D3
Algunas ideas
03

28.
Aprovechad las clases presenciales
@LUCA_D3
Vs.

29.
Leed blogs de Ciencia de Datos
@LUCA_D3
… os ayudarán a averiguar cuales son vuestros
verdaderos intereses

30.
Expresad vuestros intereses y mostrad vuestro valor
diferencial ANTES del primer trabajo… o como escribir
un CV aplastante sin usar Word.
@LUCA_D3
• Kaggle
• Github
• Ipython Notebooks
• Hackatons
• Open data Apps (Code4Good)
• StackOverflow
• Blog
• Twitter & Linkedin

31.
Los datos deben contar una historia: contadla bien.
@LUCA_D3
http://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-
essential-data-science-skill-everyone-needs/#1098ffadf0c8

32.
No olvideis las herramientas comerciales
@LUCA_D3

33.
Cambio de enfoque
@LUCA_D3
Teoría Práctica
ValidaciónCaso de uso
/ Problema
Preparación
de datos Teoría
Programación
Modelos /
Visualización
Industrialización
Máster
Empresa

34.
Si Mahoma no va a la montaña…
@LUCA_D3
• Lenguajes & Machine Learning:
Python, R, Scala
• Big Data (básico):
Spark, Hive.
• Demandas no bien cubiertas:
Modelos Predicitivos en Real Time.
Visualizaciones impresionantes (D3)
Mapas (PostGis)
• Vienen fuerte:
Deep Learning
Tensor Flow
AI+NLP (Chatbots)

35.
@LUCA_D3
Un buen ejemplo ;-)04

36.
@LUCA_D3
QUE ESPERABA…
• Conocer estructura de una gran empresa

37.
@LUCA_D3
QUE ESPERABA…
• Tratar con datos reales y muy diferentes

38.
@LUCA_D3
QUE ESPERABA…
• Grandes proyectos

39.
@LUCA_D3
QUE ME HE ENCONTRADO…
• Una gran empresa

40.
@LUCA_D3
QUE ME HE ENCONTRADO…
• Aprendizaje teórico continuo
SERIES TEMPORALES
ANÁLISIS DE REDES
ESTADÍSTICA
PREPROCESAMIENTO

41.
@LUCA_D3
QUE ME HE ENCONTRADO…
• Aprendizaje tecnológico continuo

42.
@LUCA_D3
EJEMPLOS …
• GLOBAL RIDER
https://www.youtube.com/watch?v=XeCTZcHqqyc
• ELECCIONES ESTADOS UNIDOS
http://data-speaks.luca-d3.com/2016/11/big-data-and-
elections-we-shine-light.html

43.
Global Rider
@LUCA_D3
https://www.youtube.com/watch?v=XeCTZcHqqyc

44.
@LUCA_D3
Elecciones USA 2016 & Twitter
http://data-speaks.luca-d3.com/2016/11/big-data-and-elections-we-shine-light.html
Twitter
Sinfonier
(11Paths) MongoDB
Philips
Hue + Spotfire
RealTime Filter Python
Elastic + Kibana
vs

45.
@LUCA_D3
Elecciones USA 2016 & Twitter
http://data-speaks.luca-d3.com/2016/11/big-data-and-elections-we-shine-light.html

46.
@LUCA_D3
Let your data speak

47.
Thanks for listening!
@vrbenjamins / @LUCA_D3
www.luca-d3.com