big data: status atual e tendências

Big Data: Perspectivas atuais e futuras.

Cezar Taurion

Executivo de Novas TecnologiasChief [email protected]

A SOCIEDADE HIPERCONECTADA

TECNOLOGIAPERVASIVA E COMPUTAÇÃO SOCIAL

UMA NOVO AMBIENTE DE TRABALHO

TUDO EM TEMPO REAL

UMA NOVA GERAÇÃO

Celulares/ smartphones/tablets já se igualam em numero àpopulação do planeta…

… and this isn’t just about connecting people

We are building systems of systems

Latest generation car:

�100 electronic controllers

�10 million lines of code

�Its own IP address

�Developed in 29 months (usually

a 60-120 month process)

General Motors - 2011 Chevy Volt

http://ibm.co/btsi5C

WiFi Zone

Cellular (WAN)

Vehicle-to-Vehicle

Vehicle to Roadside

Tolling

Satellite

Vehicle and Road Data

The Connected Vehicle – ‘A System of

systems’

DCAN

Ethernet

Most

Bytefligh

FlexRay

ICOM CAN

ECU 1 ECU n

GPSNETWORK

GSMGPRSPLMN

IPNETWORK

PARTNER SYSTEMS• Police/Emergency

• Weather

• Traffic

• Concierge

• Vehicle registration

• Bank

• Helpdesk

• Government

• Utilities

• Insurance

(pay as you go)

Vehicle

Control

Unit

Dealer

ANALYTICS SYSTEMS• Vehicle Condition Monitoring• Prognostics• Advanced Diagnostics• SW fault analytics• Vehicle Repair

EV/Hybrid Charging

BUSINESS SYSTEMS• Customer Support• Service Data• Warranty Data

PDA

Forecasts call for billions and billions of connected devices

9

50 Billion Connections in 2020 –Ericsson (from page 18 of 2010 annual report)

Ericsson CEO

Hans Vestberg

estimates 50 billion

devices will be

connected to the

Web by 2020

2012: 2800 Bilhões de GB!

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

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Web Logs, URLs

Social Data

Text data: emails, chats

Traditional Approach

Structured, analytical, logical

New Approach

Creative, holistic thought, intuition

HadoopStreaming

Data

New Sources

UnstructuredExploratory

Iterative

StructuredRepeatable

Linear

Data Warehouse

TraditionalSources

Enterprise Integration

Internal App Data

Transaction Data

ERP data

Mainframe Data

OLTP System Data RFID, sensor data

Network Data

“Clearly, the big data revolution is fostering a

powerful new type of data science. Having

more comprehensive data sets at our

disposal will enable more fine-grained long-

tail analysis, microsegmentation, next best

action, customer experience optimization,

and digital marketing applications” –Forrester

16

'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

Improve operational

efficiency from machine data

Improve operational

efficiency from machine data

Clients are in an exploratory phase analyzing traditional data types to address challenges around Operations &

Customer Experience

Top business imperatives for using Big Data technologies:

Grow, retain & satisfy

customers

Grow, retain & satisfy

customers

Source: Ventana Research – The Challenge of Big Data Benchmark ResearchQ: What type of data are organizations analysing most? n = 163

Organizations are analyzing traditional types of data – most often Customer & Transaction data

Key imperatives for clients implementing Big Data technologies

Intelligent Infrastructure Management

�Optimize building energy consumption with centralized monitoring

�Automate preventive and corrective maintenance

Real-time Call Data Record Analytics

�Real-time mediation and analysis of 6B CDRs per day

�Data processing time reduced from 12 hrs to 1 sec

�Hardware cost reduced to 1/8th

17

Sentiment Analysis

Novas técnicas de visualização

The rise of the Data Scientist in 2013

20

“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” – ForresterData Scientist: The Sexiest Job of the 21st Century – Harvard Business Review

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)

SW Business Use Cases

Como agir?

22

Funding

Source of Value

Sponsorship

Data

Platform Trust

Culture

Measurement

Strategy Technology Organization

Expertise

Establish a common visionto guide actions and deliver value

Create trustworthy relationships

Create confidencewith 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 softwareto manage big data

Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value © 2013 IBM

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

11 22 33

Como agir?

Obrigado pela Atenção

Cezar [email protected]

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