The data gurus. Jak szybko zarobić, A się nie zmęczyć. Paweł Płaszczak Business Intelligence Trends, Warszawa years, 150 projects

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1 Oracle BI Big Strategy Jak szybko zarobić, A się nie zmęczyć. Paweł Płaszczak Business Intelligence Trends, Warszawa The data gurus 10 years, 150 projects

2 Most people use <10% neurons

3 Most people use <10% neurons myth

4 Most people use <10% neurons Most firms use <1% data myth fact

5 The offer We help you discover information you already have.

6 1. warehousing and Business Intelligence: Information delivery

7 The data Replaced 1000s jobs key asset: data Most critical Most vulnerable security safety downtime response time Access / WWW Application Hardware + OS Services Oracle Care Audit Optimization Metrics Monitoring Migration Hardware + OS

8

9 HA

10 HA Disaster Recovery Center DR DR

11 HA Disaster Recovery Center DR DR Archive Backup

12 Dev Test HA Disaster Recovery Center DR DR Archive Backup

13 multi master Dev Test HA Disaster Recovery Center DR DR Archive Backup

14 multi master Dev Test HA ETL Warehouse Disaster Recovery Center DR DR Archive Backup

15 multi master Dev Test HA ETL Staging Warehouse Disaster Recovery Center DR DR Archive Backup data mart data mart data mart data mart

16 In memo ry multi master Dev Test HA ETL Staging Warehouse Disaster Recovery Center DR DR Archive Backup data mart data mart data mart data mart

17 In memo ry consolidation multi master Dev Test HA ETL Staging Warehouse Disaster Recovery Center DR DR Archive Backup data mart data mart data mart data mart

18 In memo ry consolidation multi master cloud Dev Test HA ETL Staging Warehouse Disaster Recovery Center DR DR Archive Backup data mart data mart data mart data mart

19 In memo ry multi master Dev Test HA ETL Staging Warehouse DR DR Archive Backup data mart data mart data mart data mart

20 management Business Intelligence IT In memo ry multi master Dev Test HA ETL Staging Warehouse DR DR Archive Backup data mart data mart data mart data mart

21 electronics manufacturer case study Customer Tier 1 electronics manufacturer, shipping 120,000 units per day, and annual revenue in $ billions. Challenge from production floor must be available immediately. However, delays of minutes and hours were observed. Impact Production increase by 30% planned, enabling 8 digit growth Picture By Robert Scoble [CC-BY-2.0 (http://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons

22 Customer World s 4th oil&gas corporation. Operations in over 130 countries, 95,000 employees. Challenge case study Efficient processing of large seismic data. Where are the undiscovered natural resources? Impact In oil&gas, seismic processing needed in all stages of exploration 10,000-node data centers not uncommon In exploration, efficient processing can save $100M per well Reservoir simulations support $1billion decisions

23 major insurance group case study

24 Klasyfikator Naive Bayes Predykcja klasyfikatora nr 1 Klasyfikator drzewo decyzyjne Prawdopodobieństwo predykcji klasyfikatora nr 1 Wniosek: klient z wysokim prawdopodobieństwem spowoduje szkodę ubezpieczeniową

25 retail & logistics case study: Jysk

26 Czas Capacity analysis Czas Czas operacji w funkcji metrów ładowych Liczba metrów ładownych Czas operacji w funkcji liczby sklepów Liczba sklepów

27 m m m m m m m m m m m m m m m m m m m m m m m m Cost per operation 2,5 2 1,5 1 0,5 0 Telco case study (1) User experience Availability 40 Incidents Capacity

28 Relative risk rank Telco case study (2) The aggregate risk timeline Legend Business Continuity Safety Security severe <120 high <90 medium <60 low <30 trivial <10 Business Continuity Security Safety Business Continuity Performance Risk by class severe high acceptable measured system RPO RTO current required Transparency Maturity Compliance Performance 100% 100% 100% 100% 80% 80% 80% 80% 60% 60% 60% 60% 40% 40% 40% 40% 20% 20% 20% 20% 0% 0% 0% 0%

29 Sales case study (1)

30 Sales case study (2)

31 Sales case study (3)

32 2. Big and Agile Business Intelligence: Information discovery

33 What is big data? that cannot be easily managed with commodity methods.

34 Inspirational projects Univ. Amsterdam Eur. Commission Leibniz Reichenzen trum WD Policja Warta non-structured data scientific structured data business structured data Philips Enea Żabka Grid Forum Total BAT BP CNN MIMOS USGS Ricoh BigMatters (2009)

35 A brief history of Big Yesterday: large volumes, VLDB Big Today: unstructured, non-relational CERN 1 PB/second (usable 25 PB/yr) Metagenomics: 1000s of PB expected 1,2 mln PB unstructured content worldwide non-structured data scientific structured data USGS: 2 PB Astrophysics: 100 PB needed 90% of corporate data is unstructured business structured data 2010: Walmart 2,5 PB 2008: AT&T: TB : Ebay 9 PB

36 Big challenge Non-structured, or semi-structured Inconsistent, nonrelational Various sources Large Dynamic Owned by many

37 The anatomy of Big & BI Text Text Morfologik Endeca Text Enrichment Text processing Cleansing Oracle Integrator Oracle Endeca Information Discovery Integrator Integration Oracle Warehouse Builder Reports & monitoring Warehousing Oracle Business Intelligence Oracle BI Publisher Oracle Oracle Endeca Server Oracle Mining Rapid Miner Mining Gephi Oracle Business Intelligence Oracle Endeca Studio Visualisation

38 Pic By Elopde (Own work) [CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons public security case study

39 Przykład 1 Dane z Allegro Krótki czas trwania? Czy cena zaniżona? Wiele kont? Grupa?

40 Przykład 2 Parametry pożyczki Parametry pożyczkobiorcy Parametry pożyczkobiorcy

41 Discovery value search Wybór Interfejsu wyszukiwania Podpowiedzi

42 Dane tekstowe Przed stemmingiem Po stemmingu

43 Wyszukiwanie wzorców, zachowań nietypowych: allegro, 31 mln rekordów aukcji mam do sprzedania zdjęcie psa oraz całkowicie za darmo dorzucam wirtualnej gotówki na Casino.pl zdjęcie i gratis wysyłam w ciągu 5min od zaksięgowania wpłaty. Przypominam ze kasa jest własnością netinus Casino.pl Oficerski tasaczek oficera RADu paleta sprzętu RTV o wartości rynkowej zł w cenie startowej 650 zł - cały towar pochodzi z Niemiec użytkownik oferujący kilkadziesiąt aukcji: motocykl, felgi i opony do samochodów i inne części samochodowe sprzedawane w obrębie wyprzedaży garażowych

44 Decision trees 85% 92% 93% 100%

45 Subgroup discovery

46 Gephi Visual analytics

47 Grafy

48 Odległość suma krawędzi Kolor krawędzi wartość Wielkość węzła pożyczki wzięte Kolor węzła pożyczki udzielone

49 Badanie powiązań społecznych

50 The anatomy of Big & BI Text Text Morfologik Endeca Text Enrichment Text processing Cleansing Oracle Integrator Oracle Endeca Information Discovery Integrator Integration Oracle Warehouse Builder Reports & monitoring Warehousing Oracle Business Intelligence Oracle BI Publisher Oracle Oracle Endeca Server Oracle Mining Rapid Miner Mining Gephi Oracle Business Intelligence Oracle Endeca Studio Visualisation

51 Big opportunity Information discovery Marketing: sentiment analysis Telco: cross-selling Finance: insurance pricing, fraud Web: paid content Public: security, crime Sales: lead generation General: client behavior monitoring agile Business Intelligence

52 Beat your competitors Use 100% neurons Use 100% information

53 Paweł Płaszczak Thank you We help you discover information you already have.