Big Data, Big True. IDC Big Data Conference II, Bologna 19 novembre Fabio Rizzotto IT Research&Consulting Director, IDC Italy

Transcription

1 Big Data, Big True IDC Big Data Conference II, Bologna 19 novembre 2013 Fabio Rizzotto IT Research&Consulting Director, IDC Italy

2 Il sorpasso dei Big Data sulla BI Business Intelligence Big Data Worldwide Business Intelligence Big Data Italia Fonte: Elaborazioni IDC da Google Trends, novembre 2013 Il grafico esprime il numero di ricerche web eseguite con un termine specifico rispetto al numero totale di ricerche effettuate su Google nel tempo. Non rappresentano valori assoluti di volume di ricerca, i dati sono normalizzati e presentati su una scala da 0 a

3 Big Data: Definizione IDC Volume Value Variety Velocity Big Data technologies describe a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data by enabling high velocity capture, discovery, and/or analysis. 3

4 Big Data: si fanno strada evidenze concrete Retailer is scoring customers based on their on- and off-line behavior Manufacturer of wind turbines uses weather data and big data technology to identify optimal locations Telecommunications company is improving predictability of customer churn Credit card company is improving fraud detection capabilities Data-driven companies 1 5% more productive 6% more profitable 45% of organizations achieve quantifiable benefits within six months 2 For 16% of organizations benefits exceeded expectations For 61% benefits met expectations 3 Sources: 1. Strength in Numbers: How Does Data-Driven Decision making Affect Firm Performance? MIT Center for Digital Business, IDC and Computerworld 2013 Business Analytics Survey, June 2013 IDC Visit us at IDC.com and follow us on 4 3. IDC Big Data and Analytics Maturity Survey, July 2013

5 Big Data: principali ambiti di applicazione Life sciences research Web app optimization Smart meter monitoring Weather forecasting Advertising analysis Activity Industry Oil and gas exploration Traffic flow optimization Customer behavior analysis Customer churn analysis Social media analysis Pricing optimization Process Fraud detection Healthcare outcomes analysis Use cases will fall into two primary categories: 1. Carrying out tasks more efficiently (including at lower costs) than for years 2. Doing completely new things that were previously impossible, driving up long-term strategic organizational value 5

6 Big Data & Analytics: Project Drivers Product or Service Improvement and Innovation Customer Service and Support Pricing Strategies and Programs Market and Competitive Intelligence Process and Operations Optimization and Control Customer Acquisition and/or Retention IT Optimization and/or Modernization Regulatory Compliance, Financial Controls Supply Chain Management and Logistics Human Capital Management Operational, Fraud, Malicious Risk Management Plant, Facilities, Equipm. Design, Maint&Use 0% 10% 20% 30% 40% 50% % of respondents Q. Which of the following areas have been identified as significant drivers of your organization's big data and analytics initiatives over the next 12 to 24 months? IDC Big Data and Analytics Maturity Survey, July

7 Big Data: le sfide tecnologiche Data Data Data Data integration Managing data quality Managing data security Lack of sufficiently skilled IT staff High initial cost of IT Evaluating appropriate IT Data Data governance Managing IT sprawl or need to consolidate IT High ongoing IT maintenance costs Insufficient system performance or scalability Managing external services providers 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% % of respondents Q. What are the top IT challenges your organization is facing with respect to its business analytics initiatives? IDC and Computerworld 2013 Business Analytics Survey 7

8 Big Data: le sfide di business Lack of sufficient number of staff with appropriate analytics skills Securing budget Agreeing on KPIs or metrics Defining business requirements Justifying business case for projects Measuring project outcomes Change management 0% 10% 20% 30% 40% 50% % of respondents Q. What are the top business challenges your organization is facing with respect to its business analytics initiatives? IDC and Computerworld 2013 Business Analytics Survey 8

9 Tipologie di Dati: da Big Data a All Data Data sources Internal External Data types Structured Unstructured Governance Quality Security Structured transactional data Non social media customer interaction text data Geographic or spatial data Text from content repositories Mobile device data Web clickstream data Sensor or machine generated Rich media Chatter or text from social media 0% 20% 40% 60% 80% 100% % of respondents Q. Are the following types of data analyzed in your organization? IDC and Computerworld 2013 Business Analytics Survey 9

10 Data Management rimane una grande sfida Data Quality Do we trust the data captured? Garbage IN, garbage OUT Good data, bad data Data Storage & Retrieval How long to store? Regulations Uncaptured Data What to capture? Machine data, social media feeds Data Integration Data Governance Data Ownership Data Architecture 10

11 Competenze e Analytical Skills How to Utilize the Analysis of Big Data to Make Effective Decisions Data analysts and scientists Managers/executives with analytical skills 11

12 Le aziende italiane e i Big Data (1) Settori Finanza/TCU maggiore propensione rispetto a Industria/Commercio/PA Finanza/TCU maggiore propensione verso Volume Industria => Velocità Commercio=> Varietà/Eterogeneità Aziende più propense a iniziative Big Data vedono opportunità per innovazione di business, cercano allineamento IT-Business e migliore qualità dei Servizi IT Fonte: Survey IDC Italia, 2013 (n=100) 12

13 Le aziende italiane e i Big Data (2) Requisiti di business, Data Integration e Competenze sono i fattori critici Sperimentazioni e prime iniziative consentono di vedere lo sviluppo delle Competenze anche come un opportunità Emerge correlazione positiva tra Big Data e iniziative Cloud Big Data contribuiscono a ridefinire ruoli e influencer a livello CxO Fonte: Survey IDC Italia, 2013 (n=100) 13

14 Conclusioni: Big Data per i nuovi scenari competitivi Product / Service Innovation Best-in-class technologies Process automation & reengineering 14