Palestra sobre conceitos Big data no evento IDETI em SP. Aborda o que é Big data, debate alguns beneficios e desafios. Debate também o papel do CDO- Chief Data Officer.

1. Afinal, o que é Big Data?
Como vai afetar as empresas e nossas vidas?
Cezar Taurion
Consultor senior
ctaurion@gmail.com

2. A SOCIEDADE
HIPERCONECTADA
TECNOLOGIA
PERVASIVA E
COMPUTAÇÃO
SOCIAL
UM NOVO
AMBIENTE DE
TRABALHO
TUDO EM
TEMPO REAL
UMA NOVA
GERAÇÃO

7. Midias sociais fazem parte do dia a dia do
brasileiro

8. Celulares/ smartphones/tablets já se igualam em numero à
população do planeta…

10. As coisas acontecem muito rapido no mundo cada vez
mais hiperconectado

14. Quem é esta geração digital?
 Usam tecnologias digitais no seu dia a dia e esperam usá-las no trabalho.
São early adopters por natureza.
 Entram no mundo online cada vez mais cedo... usam a Internet como
laboratório social, para testar limites do relacionamento.
Vivem em ritmo cada vez mais acelerado e são multitarefas (usam celular,
MP3, tablet, smart TV...tudo ao mesmo tempo!)

17. Computing is not about computers anymore. It
is about living!

20. 2007 7% 93%
2000 75% 25%
2013 2% 98%
Digitalização dos dados e informações cresce em ritmo
acelerado!

22. Big Data refers to how to collect, store, and manage
information that comes into an enterprise so that it can be
harvested for decision making
22

23. Big Data and analytics unlock new insights and opportunities that just
weren’t possible before
Analytics
Applied
to Big Data
1. Better, smarter insights
highlighting business
opportunities—internal
and external
2. Internal process and
performance
improvement
3. Creating novel,
incremental revenue
possibilities
Traditional Approach
Structured, analytical, logical
Multimedia
Data
Warehouse
Web Logs
Social Data
Sensor data:
images
RFID
Internal App
Data
Transaction
Data
Mainframe
Data
OLTP System
Data
Traditional
Sources
ERP
Data
Structured
Repeatable
Linear
Unstructured
Exploratory
Dynamic
Text Data:
emails
Hadoop and
Streams
New
Sources
New Approach
Creative, holistic, intuitive
23
Volume, Variety, Velocity, Veracity = Value
Decem Big Data & Analytics North America | IBM Confidential

25. E você ainda pensava que lia sozinho(a)?

26. Você não é mais um anônimo...
On Internet, they know you’re a four-year-old male dog that has
fleas, prefers canned dog food and was neutered six months
after birth, and this data is for sale for a fraction of a cent in mass
quantities...

27. 27

28. 28

29. Novas técnicas de visualização

30. Biases in social media data
Digital access
Age
Class
Gender
Literacy
Geography
Optimism
Position on issues
Fans/opponents
...

31. Biases in social media data
Digital access
Age
Class
Gender
Literacy
Geography
Optimism
Position on issues
Fans/opponents
...

32. Sentiment Analysis

33. Big Data impacta todos setores de negócio…
Insurance
 Solvency II
 Antifraud, Waste, Abuse
 Next Best Action
 Operational Risk
 Policy Analytics
 Claims Analytics
 Single View of Customer
Banking
 Single View of Customer
 Customer Centric
 Asset Optimization
 Security
 Enterprise Ops Risk Mgmt
 Credit Lifecycle Mgmt
 Next Best Action
 Fraud – AML
 Digital Adoption
Telco
 Centralized BI Delivery Center
 EDW and BI Transformation
 Call Detail Record Analytics
 Advanced Analytics Lab
 Next Best Action
 Predictive Asset Optimization
 Network Analytics
Energy
& Utilities
 Power Delivery Dashboard
 CFO Performance Insight
 Smart Meter
 Customer Insight
 Grid Analytics
 Risk Analytics
 Condition Based Maintenance
Media and
Entertainment
• Audience Insight
• Business process transformation
Retail
 Customer Driven Loyalty Marketing
 Collaborative Analytics Platform
 Intelligent Ops Center
 Customer MDM
 Social Media Segmentation
Travel and
Transport
Consumer
Products
 Post Event Analysis and Tracking
(DSR)
• Shelf Availability (SW)
• Promotional Spend Optimization (SW)
• Merchandising Compliance (SW)
Government
 Social Program Integrity
 Citizen Access and Insight
 Border Control Management
 Customs Risk Management
 Road User Charging
Healthcare
Automotive
 Actionable Consumer Intelligence
 Predictive Asset Optimization (Equip
Health & Mfg Quality and SCO)
Life Sciences
 Strategic Insight Portfolio (SIIP)
 Clinical Research Library
 Patient Adherence
Chemical and
Petroleum
 Turnaround Management
 Performance Mgmt System
 Drilling Analytics
 Master Data Management
Industrial
Products
Electronics
 Predictive Asset Optimization
 Customer Analytics
 Quality Early Warning System
 Supply Chain Analytics
 Customer Loyalty & Insights
 Dynamic Social Media
Recommendations
 Production Design and Optimization
Scheduling
 Customer Segmentation and
Member Analytics
• Measure & Act on Population Health
Outcomes (SW)
• Engage Consumers in their
Healthcare (SW)

34. 34
'Big Data' está ainda no canto da tela do radar dos CIOs/CEOs/Gestores…
Adoção de Big data
Some are just
starting to explore
'Big Data'
Most are already debating/
evaluating/ considering
'Big Data'
Adoção
A few are already/
still implementing
'Big Data'
Several plan to
implement w/in the
near futureOnly a minority has
not looked/ won't
look into it
Ignorants Early
Explorers
Heavy
Explorers
Planners Implementors

35. The hype of big data continues, but in 2014/2015 the focus will be on
implementing solutions and finding value
Big Data: A 2014 HorizonWatch Trend Report
“The hype around big data continues to drive increased investment and attention,
but there is real substance behind the hype. Our survey underlines the fact that
organizations across industries and geographies see 'opportunity' and real business
value rather than the 'smoke and mirrors' with which hypes usually come.” – Gartner
“The hype around big data is coming to an end, signifying the beginning of a long-term
adoption trend that will expose myriad opportunities and challenges.” – IDC
“The reality will set in as more organizations attempt Big Data and analytics initiatives.
The opportunities are real, but still involves quite a bit of trial and error, and
experimentation.” – IDC

36. Big Data: A 2014 HorizonWatch Trend Report
Industry Analysts are forecasting significant growth in IT
spending associated with the Big Data

37. Organizations still face basic pain points, ranging from confusion about
Big Data to lack of skills
3 Big Data & Analytics North America | IBM Confidential
Big Data and Analytics Challenges:
1. Adoption is still early as users are confused by what big data is
2. Organizations don’t have the skills to fully exploit it:
a) Not having enough or the right IT skills to manage Big Data Projects
b) Not having enough or the right analytics staff to analyze the data
3. Organizations lack the tools & integration to existing proprietary offering
a) Unstructured or semi-structured text is difficult to query
4. There are underlying “information management” challenges that limit organizations ability to capitalize on big data
Traditional relational databases / data warehouses not designed for new types of data
5. Trouble deciding what data is relevant (What data to keep store/discard)
6. Cost of technology infrastructure
7. Different sources of data (enterprise apps, web, search, video, mobile, social conversations and sensors)
Source: IBM CEO,CIO, CFO, CMO Studies; Gartner Best Actions in a Decade of CIO Resolutions as CIOs Move From Technical Manager to Digital Leader, May 2013
, IDC Directions 2013: Building a Big Data and Analytics Road Map for Business Value
Decem

38. World without secrets...

39. The rise of the Data Scientist in 2013
39
“A data scientist is someone who can
understand the desired business
outcome, examine the data, and create
hypotheses about how to establish
predictive rules that can enable
business outcomes such as increasing
eCommerce upsell, keeping a
production line running, or eliminating
stock-outs” – Forrester
Data Scientist: The Sexiest Job of the 21st
Century – Harvard Business Review

40. CDO- Chief Data Officer role, one that reinforces the partnership among other C-
suite executives and promotes establishing an Analytics Center of Excellence
40
Overall guidance
and vision
Chief
Data
Officer
Managing the
Enterprise program
Working across the
executive set
Refining
processes
and introducing
analytic
innovation
Guiding the Analytics
Centers of Excellence
Defining
capabilities &
technology
investment
* CDO backgrounds require experience in statistical analysis, marketing, finance, and/or operations
 CDO role is two-fold:
1. Top executive responsible for business
analytics strategy, guiding strategy team
managing analytic priorities across all
business units
2. In partnership with the CIO, guide IT
infrastructure team with a centralized
analytics platform
 Must work closely with all C-Suite execs to
ensure priorities are met and to facilitate
cross-team collaboration and analytic skill
 CDO is different from the CIO, functioning
as key linkage between IT and Business
 Includes relationships with CEO, CIO,
CMO, CFO, and Lines of Business

41. CDO Responsibilities
Working across the
executive set to set strategy
and define roadmap
• Interfacing with CFO, CMO, COO and others to determine key business needs
to tie analytics strategy to corporate strategy and how to execute and measure
• Aligning teams, metrics framework and creation and maintenance of overall BA
strategy
• Defining value, prioritizing and creating the strategic and tactical roadmap of
projects
Overall guidance and vision
to all analytic teams
• Communications and evangelism of vision and roadmap
• Coaching metric definition, model development targets, business case
development and measurement of business outcomes
• Managing pool of analytic skill that can assist, coach and enable teams
Managing the enterprise
vision
• Program Management of all aspects of strategy, value, people, process and
technology
• Driving training, education and managing analytic skill advancement
• Development of the advise and consult framework
Guiding the Analytics
Centers of Excellence
• Creating the communication platform across teams (regular meetings,
newsletters, collaboration, onboarding, knowledge share)
• Defining organizational structures, dotted line structures, roles, responsibilities
• Identifying stakeholders, gaps and assisting teams in increasing use of analytics
Defining capabilities and
technology solutions
• Mapping capabilities to business needs
• Assessing technology state and understanding gaps
• Guiding technology investment and measuring TCO with IT team
Refining processes and
introducing innovative
technology solutions
• Assessing processes and understanding where analytics can refine process
• Evaluating where continual improvements can be made to re-define process
• Introduce analytic process that can enable and onboard satellite teams

42. 42
Customer
service
Marketing
IT
Operations
Product
development
Human
resources
Finance
Sales
The CDO’s office—
the Analytics Center
of Excellence—will
be the guiding,
impartial team to
work across various
lines of business
throughout an
organization
CDO & Analytics Center of Excellence

43. Como agir?
43
Funding
Source of Value
Sponsorship
Data
Platform Trust
Culture
Measurement
Strategy Technology Organization
Expertise
Establish a common vision
to guide actions and deliver value
Create trustworthy
relationships
Create confidence
with governance and security
Ensure alignment between analytic
focus and value creation
Create value with rigor
and collaboration
Measure impact
and model the future
Make decision
based on facts
Increase knowledge-sharing
opportunities
Integrate hardware and software
to manage big data
Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value © 2013 IBM

44. Multiple Data
Sources
Prediction &
Optimisation
Models
Organizational
Transformation
 Creatively source internal
& external data
 Upgrade IT architecture
and infrastructure for easy
merging of data
 Focus on the biggest
drivers of
performance
 Build models that
balance complexity
with ease of use
 Create simple,
understandable tools for
people on the frontline.
 Update processes and
develop capabilities to
enable tool use
Source : Making Advanced Analytics Work for You : A practical guide to capitalize on Big Data; Harvard Business Review, Oct. 2012
1 2 3
Como agir?

45. Agir rapido, pois o futuro se torna passado rapidamente!

48. Cezar Taurion
ctaurion@gmail.com
@ctaurion
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