Intervento di Fabrizio Renzi all'Annual Meeting 2012 di Forum ICT

1. Evento CUOA sul LEAN IT
Altavilla Vicentina, 20 Novembre 2012
ed il LEAN IT
Fabrizio Renzi, Direttore Tecnico IBM Italia
Fabrizio_renzi@it.ibm.com
© 2012 IBM Corporation

2. Gli studi IBM confermano il bisogno del miglioramento continuo (lean)
1. Companies must become CMO’s top concerns: CIO’s top focus:
more client centric by 1. Data Explosion
1. Insight & Intelligence
leveraging sophisticated 2. Social Media
insights 3. Growth of channel 2. Client Intimacy
2. Extensive partnering is choices
3. Virtualization
enabling CEOs to make 4. Shifting demographics
radical innovation. Source: IBM’s 2012 4. Cloud Computing
CEO Survey, 1,700 CEO’s
2 © 2012 IBM Corporation
*Source: Top 200 global bank survey, IBM Institute for Business Value, The Economist Intelligence Unit.

3. Che cosa ci chiedono nostri clienti per l’IT: (lean)
Cost Savings + Innovation = Value Creation
Standardization
Lower IT Operating enabled by
Capex to Opex
and Capital Costs integrated service
management
Fast access to
Removing IT Fine grained IT
current technology
complexity from services with rapid
and powerful
end users provisioning
computing
3 © 2012 IBM Corporation

4. La visione IBM per l’ICT nel 2012.
IBM a supporto
dell’innovazione con
R&D e acquisizioni
Analytics
Oltre 3.200 ricercatori e
& Big data
scienziati
5 premi Nobel
Smarter New Da 18 anni prima società
Planet technologies
negli Stati Uniti per
numero di brevetti
(circa 53.000 in 18 anni,
5.896 nel 2010)
Spese annuali in:
Social & Cloud R&D 6 B$
Mobile Computing Acquisizioni sfw 6-10 B$
New technologies
investment. 5-8 B$
4 © 2012 IBM Corporation

5. Analytics sono definiti come l’uso dei dati e del calcolo per AIUTARE
a prendere decisioni smart. Sono sempre più usati per le aree della
gestione del rischio, payments, CRM, interactive marketing,
couponing, trading, finance, strategic planning….…..
Data Decision point Possible outcomes
Data instances
Historical
n1
Reports and queries on Optio
data aggregates
Predictive models Option 2
Answers and confidence Opt
Simulated ion
Feedback and learning
3
Text Video, Images Audio
5 © 2012 IBM Corporation
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6. La 4 dimensione dei Big Data l’affidabilità del dato.
Volume Velocity Variety Veracity*
Data in Many
Data at Rest Data in Motion Data in Doubt
Forms
Terabytes to Streaming data, Structured, Uncertainty due to
exabytes of existing milliseconds to unstructured, text, data inconsistency
data to process seconds to respond multimedia & incompleteness,
ambiguities, latency,
deception, model
approximations
* Truthfulness, accuracy or precision, correctness
6 © 2012 IBM Corporation
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7. Condensare i dati costruisce un contesto attorno agli stessi
Esempio di condensation sui dati da google. (carrots 2)
Risultato ricerca con online 13/11/2012:
Per IBM RENZI FABRIZIO TECHNICAL DIRECTOR
7 © 2012 IBM Corporation