Information Builders. Transforming Data Into Business Value. Mauro Grassi. Information Builders. Milano, 8 Novembre 2012

Transcript

1 Information Builders Transforming Data Into Business Value Mauro Grassi Information Builders Milano, 8 Novembre

2 Information Builders About Us Software vendor indipendente con operazioni su scala globale Valori centrali e primari Servire il Cliente Focalizzarsi sull innovazione tecnologica Forte penetrazione in tutti i maggiori mercati verticali Partnership di lungo termine con tutti i Clienti 36 anni di esperienza 1,350 dipendenti 60 sedi worldwide installazioni Millioni di utenti Only Information Builders achieves above-average ease of use, below-average implementation costs per user, above-average support for complex deployments and above-average business benefits. 2

3 Information Builders Customers Banking Financial Services and Service Providers Manufacturing Consumer Packaged Goods Communications Insurance Retail Natural Resources Outsourced Services 3

4 Information Builders Customers Federal Government State and Local Government Education Healthcare Providers Healthcare Insurers Pharmaceutical and Medical Supply Transportation and Logistics Travel and Entertainment Not for Profit 4

5 Cosa ci chiede il mercato 6

6 BIG DATA per Information Builders Volume di dati Velocità (di generazione, raccolta, elaborazione e distribuzione) Variabilità (di fonti e formati) Tipologia di utenti Nuovi processi 7

7 ANALITYTICS per Information Builders BI Tools What s the best that can happen? BI Analytics Decision Optimization Competitive Advantage What will happen next? Predictive Analytics What if these trends continue? Forecasting Why is this happening? Statistical models Alerts What actions are needed? Query/drill down Where exactly is the problem? Ad hoc reports How many, how often, where? Standard reports What happened? Information Degree of Intelligence (adattamento da Davenport, 2007) Insight 8

8 Information Builders, BIG DATA + ANALITYTICS Information Builders the Only Large Independent With Above Average Ease of Use, Complexity but Low Implementation Cost per User

9 Information Builders The Information Stack Business Intelligence Advanced Analytics Performance Management Data Quality Management Master Data Management Data Governance Integration Infrastructure Data Integration Universal Adapter Suite 10

10 Information Builders Transforming Data Into Business Value Revenue Generation Quality of Care/Service Information Operations and Financial Mgmt. Fraud, Waste and Abuse Risk, Compliance and Governance 1 1

11 Information Builders BIG DATA + ANALYTICS Highest Return on Investment Information Solutions Revenue Generation Customer Acquisition and Retention Online customer experience Single view of customer Quality of Care/Service Customer intelligence Single view of patient, citizen, student, or criminal Public information portals Call center performance Operations & Financial Mgmt Cost control and budget management Performance management of employees, suppliers, contractors Product and logistics intelligence Reduction of redundant, error-prone, and manual processes Fraud, Waste and Abuse Real-time event analysis and predictive scoring Identity management Location intelligence Risk, Compliance and Governance Government, industry, and corporate 1 2

12 Prescriptive Analytics Price Optimization Solution: Fact-Based Pricing

13 BIG DATA + ANALYTICS per TESCO 14

14 Turning data into value

15 Turning data into value

16 Turning data into value

17 TESCO BIG DATA + ANALYTICS CUSTOMER RETANTION FROM 13% TO 30% PROFILO SOCIO-DEMO RECENCY, FREQUENCY, MONETARY PROFITABILITY BASKET E MIX DI ACQUISTO FIDELITY CARD, PUNTI PREMIO SOCIAL WEB DATA (RT e non RT) GARANZIE PRODOTTI consumer GEO-POSITIONING VIDEO-INTELLIGENCE (riconoscimento volti e Comportamento fisico) INFORMAZIONI E RECLAMI AL CONTACT CENTER FEEDBACK E-SURVEY Businesses change slowly, customers change in an instant, Sir Terry Leahy, CEO TESCO 18

18 Health Governance & Information Management Cineca Case Study (Business Intelligence) Ing Busca Paolo

19 Criteri di scelta degli strumenti Analisi processi di erogazione ed utilizzo dei servizi INTERNI ETL Report dinamico sviluppo Reporting e KPI standard predisposizione ambiente di analisi dati ESTERNI (utenti) utilizzo Reporting e KPI sviluppo Reporting e KPI personalizzati analisi dati from CONSUMER to PRODUCER of INFORMATION

20 As - Is 100+ Utenti Power User Reporting Guidato Report dinamico Analisi dei dati 32 Asl (~9000 medici di famiglia) Reporting statico (KPI) 200 TB di datastore

21 Simulazione variazione indicatori Impatto economico Anno 2010 ASL resid. Spesa per statine: Spesa altri farmaci: Spesa totale: , eventi CV acuti pari a

22 PIANETA CARCERE, COME DARE I NUMERI SENZA PERDERE LA TESTA. WebFOCUS a supporto dell Amministrazione Penitenziaria Dott.ssa ANNA FINO, Funzionario Informatico Ufficio per lo Sviluppo e la Gestione del S.I.A. e Supporto alle decisioni -Sezione Statistica Ministero della Giustizia

23 Consolidamento - Statistica T istit T icons T evol dati giudiziari (condanne, reati,...); Caratteristich e(sesso, nazionalità,..) dati sociali (professione, ). Diffusione dei dati Pagine statiche aggiornate periodicamente e intranet Pagine dinamiche Reportistica giornaliera con WebFOCUS Statistica Penitenziaria e altri adempimenti Sistan PIANETA CARCERE,: COME DARE I NUMERI SENZA PERDERE LA TESTA. WebFOCUS a supporto dell Amministrazione Penitenziaria Dott.ssa Anna Fino

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25 Passa ad active report Drilldown

26 NATION WIDE and SECURITIES AMERICA agent application 27

27 La piattaforma di Information Builders 28

28 La piattaforma di Information Builders Enterprise Search Visualization & Mapping Mobile Applications App/Dev, Portals & Mash-ups Predictive Analytics High Performance Data Store Performance Management Reporting Query & Analysis Dashboards Information Delivery MS Office & e-publishing Data Warehouse & ETL Business to Business Data Quality Master Data Management Business Activity Monitoring

29 MetroPulse Co pyr igh t 20 07, Inf or ma

30 US bank

31 Terada applicazioni RapidWH di Teradata

32 Conclusioni 33

33 Big Data Our goal is to enable WebFOCUS to access ALL types of data. Relational i.e. Oracle, Teradata, SqlSrv Application owned i.e. Peoplesoft, Siebel, SAP OLAP i.e. SAP/BW, ESSBASE, SQL SRV Legacy i.e. IMS, Remedy, C-ISAM Flat files i.e. Excel, Delimited, 300+ adapters New Data Sources.. NoSQL New WebFOCUS adapters FaceBook SalesForce.com MongoDB (JSON) Hadoop/Hive/HDFS GreenPlum, Vertica, Par Accel, 1010, Netezza 34

34 Big Data Search-based BI with Magnify: Automatic transfer of database records to search index database Look for records based on items in their text and instantly access and display it from the database. Create new entities during transfer Magnify Active Report of Hits for data analysis Perform analysis on Text fields e.g. Sentiment Analysis 36

35 Magnify s Search Results with Sentiment 37

36 Big Data WebFOCUS Hyperstage: A column-oriented database designed for speed of reporting Replaces Cubes Replaces Aggregate tables Replaces Indexes Doesn t need a Database Administrator It s managed entirely thru the WebFOCUS console Comes with a fast data load ETL like facility for a quick start WebFOCUS DataMigrator ETL for more complex situations Features include.. 90% compression of data.. E.g. 1 Terabyte of RDBMS data is only 10 gigabytes Fits into memory easily 38

37 Mobile Our Strategy is: Build Once, Deploy Anywhere We will rely on the HTML5 browser that all devices use, and not require any device coding. This will extend to the Adobe format of FLEX that is very popular and will be added in our Release so it will work on the ipad. To achieve running on all devices.. we recognize the device and adjust what we send to conform to the capabilities of the device. Fx 39

38 Summit Evaluation Form on ipad 40

39 Data Visualization: Our HTML5 Catalog

40 Data Visualization: New Chart Types

41 Data Visualization: Social Media Charts Lexical Diversity Re-Posting Paths Cloud Tags Lexical Frequencies Streaming Frequencies 43

42 Data Visualization: New Chart Types

43 Grazie! Mauro Grassi Milano, 7 Novembre