Oracle & Big Data. Bram den Uijl InformaGon Architect Oracle ConsulGng, Business AnalyGcs May, 2015

Size: px
Start display at page:

Download "Oracle & Big Data. Bram den Uijl InformaGon Architect Oracle ConsulGng, Business AnalyGcs May, 2015"

Transcription

1

2 Oracle & Big Data Bram den Uijl InformaGon Architect Oracle ConsulGng, Business AnalyGcs May, 2015 Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted

3 Agenda Oracle history and background My daily job J - Oracle and Big Data Defini;ons of Big Data Characteris;cs Use cases Workshops /Food for thought Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 3

4 Oracle history and background Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 4

5 Oracle the begin Copyright 2014 Oracle and/or its affiliates. All rights reserved.

6 Oracle The Stack Copyright 2014 Oracle and/or its affiliates. All rights reserved.

7 ApplicaGons Programma s, SoWware Copyright 2014 Oracle and/or its affiliates. All rights reserved.

8 Middleware Cement en kit tussen de tegels/stenen Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 8

9 Database Gegevens, Kaartenbak Copyright 2014 Oracle and/or its affiliates. All rights reserved.

10 Database Data gestructureerd (Past netjes in 1 vakje van je kast) Data Niet gestructureerd = Big Data Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 10

11 OperaGng System Besturing van computers Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 11

12 Servers Computers zelf (soms klein, meestal groot) Copyright 2014 Oracle and/or its affiliates. All rights reserved.

13 Servers en applicagons On premise Cloud Op LocaGe: Je kan het Aanraken/ voelen... in de lucht Internet, via WiFi Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 13

14 Storage Opslag van gegevens en bestanden (filmpjes, muziek etc.) Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 14

15 My daily job J Oracle and Big Data Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 15

16 InformaGon Management Architecture Logical View InformaGon Provisioning Direct Flow from Source Systems Data Sources Data Engines & Poly- structured sources Structured Data Sources Master & Reference Data Sources OperaGonal Data COTS Data Streaming & BAM Data IngesGon Access & Performance Layer Access and Performance Layer Foundation Data Layer Past, current and future interpretagon of enterprise data. Structured to support agile access & navigagon Immutable modelled data. Business Process Neutral form. Abstracted from business process changes Virtualisation & Query Federation Enterprise Performance Management Pre- built & Ad- hoc BI Assets InformaGon Services Raw Data Reservoir Content Docs SMS Web & Social Media Immutable raw data reservoir Raw data at rest is not interpreted InformaGon InterpretaGon Data Science Copyright 2014 Oracle and/or its affiliates. All rights reserved.

17 Copyright 2014 Oracle and/or its affiliates. All rights reserved.

18 Big Data DefiniGons Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 18

19 DefiniGons Datasets whose size is beyond the ability of typical database sowware tools to capture, store, manage, and analyse Big Data Study of McKinsey in 2011 An all- encompassing term for any collec;on of data set so large and complex that it becomes difficult Higher to process using tradigonal data Different processing applicagons. New data volume Wikipedia structures The ability of society to harness informagon in novel ways to produce useful insights or goods and services of significant value and things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value. Viktro Mayer- Schönberger and Kenneth Cukier Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 19

20 More definigons The shiq (for enterprises) from processing internal data to mining external data. hap://whatsthebigdata.com/ The belief that the more data you have the more insights and answers will rise automa;cally from the pool of ones and zeros. External More Cameron insight Phillipp- Edmonds, techwell.com sources More feedback A new aotude by businesses, non- profits, government agencies, and individuals that combining data from mul;ple sources could lead to beper decisions. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 20

21 DefiniGon High- volume, - velocity and - variety informagon informa?on assets that demand cost- effecgve, innovagve forms of informagon processing for enhanced insight and decision making. Gartner WHAT High- volume, - velocity and - variety informagon assets Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 21

22 DefiniGon High- volume, - velocity and - variety informagon assets that demand cost- effec?ve, innova?ve forms of informa?on processing for enhanced insight and decision making. Gartner WHAT HOW High- volume, - velocity and - variety informagon assets Cost- effecgve, innovagve forms of informagon processing 22 Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted

23 DefiniGon High- volume, - velocity and - variety informagon assets that demand cost- effecgve, innovagve forms of informagon processing for enhanced insight and decision making. Gartner WHAT HOW GOAL High- volume, - velocity and - variety informagon assets Cost- effecgve, innovagve forms of informagon processing Enhanced insight and decision making 23 Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted

24 Self- branding Big Data insights Self-branding Better Matching Users all must brand themselves in a specific way in order to get whatever they are looking for, in this case a relagonship. It requires users to brand themselves as products that other users would poten;ally want to buy or more accurately get to know beper based on how they market themselves differently than every other individual looking for companionship on the site. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 24

25 CharacterisGcs Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 25

26 Produce Data 12 % ExecuGves who feel they understand the impact data will have on their organizagons Use Data Copyright 2014 Oracle and/or its affiliates. All rights reserved.

27 CharacterisGcs Structured transac;onal data Type (CX of and data ERP) #1 Procurement, sales, CX/CRM, Unstructured data (service, social, Type channel of data) #2 Facebook, Twiper, Google+, LinkedIn, Fraud detec;on etc. Data usage Opera;ons & supply chain Customer Experience fuel Non transac;onal data (partner data Type extern) of data #3 Market- scans, Gartner, Non transac;onal data (demographic data intern & Type extern) of data #4 CBS, SCP, Mul; strutured data (combina;on of web, Type video, of data images) #5 Instagram, Picasa, Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 27

28 Workshop 1 Welke data is er van jou bekend? Waar is de data van jou? Welke data van jou mag bekend zijn? Wie maakt er gebruik van je data? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 28

29 Use cases Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 29

30 Use Cases Sport Media Banking Industry Insurance Services Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 30

31 Workshop 2 Wat betekent Big Data voor bedrijven? Welke kansen zie je? Welke beperkingen/ gevaren zie je? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 31

32 Flemish company that we know from the following media: Radio & television: Q- music, AT5 Papers: Het Parool, Trouw, Algemeen Dagblad, de Volkskrant Magazines: VNU Media, Intermediair Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 32

33 Flemish company that we know from the following media: Radio & television: Q- music, AT5 Papers: Het Parool, Trouw, Algemeen Dagblad, de Volkskrant Magazines: VNU Media, Intermediair Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 33

34 Matching few examples: Media- content ~ interests of the customer MarkeGng focus ~ new customers (extend customer base) MarkeGng focus ~ current customers (maintain current customer base) Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 34

35 Available data: Sales data: what products are sold to what customers for what price at what Gme MarkeQng data: which markegng campaigns apracted what type of customers? Customer data: which customers ended their contract, website comments External data: reviews, twiper sengment Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 35

36 Improve matching markeqng focus ~ current customers Used data: locagon- data, sales- data per product, customer reviews, personal contact Purpose: determine what customers are likely to not renew their newspaper Improve matching: provide markegng with this list of customers Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 36

37 Actual use case: De Persgroep build a predicgve model based on big data which with an accuracy of 92% is able to predict that you wont renew your newspaper anymore. They changed their markegng strategy to retain customers that otherwise would have not renewed their newspaper. This predicgve model is build on Oracle s Big Data Appliance. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 37

38 Xerox is an American mulgnagonal document management corporagon that produces and sells a range of printers, photocopiers, presses, and related consulgng services and suppliers. Xerox had a matching problem: how to find good people for their call centres. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 38

39 Matching: Call centre applicants ~ job openings Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 39

40 Available data: Interview quesgons of applicants Behaviour of call centre personal that perform good A set of logs that describe call centre scenario s Feedback on call centre scenario s Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 40

41 Improve matching call centre applicants ~ job openings Collect personal traits from good personnel Create a test that screens for personality traits of the ideal call centre employee and puts them through scenarios they might encounter on the job Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 41

42 Goal: Improve hiring process of call centre employees Big Data challenge: At Xerox, applicants take a 30- minute test that screens for personality traits and puts them through scenarios they might encounter on the job. A big data model decides whether an applicant will get the job. This model is based on personal threats that ideal call- centre workers have. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 42

43 Insurance branch Matching: Driver behaviour ~ Prices for car insurances Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 43

44 Insurance branch Available data: Historical data (in case the driver has a record) Collect sensor data from the driver Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 44

45 Insurance branch Improve matching - Driver behaviour ~ Prices for car insurances Create risk model from sensor data Win/win? A driver can prove that he/she has a good driver behaviour and has a cheaper car insurance. Matching Available data How to improve matching? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 45

46 Use case Online dagng Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 46

47 Workshop 3 Welke vragen wil je stellen bij een dagng- site? Welke vragen zou je eventuele partner moeten stellen? Wat is nodig voor de ideale match? Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 47

48 Goal: DaGng matching performance Big Data challenge: Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 48

49 Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 49

50 Problem: You need common answers to be matched Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 50

51 answers of partners Mindful Diverse God Dog TaAoo Green Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 51

52 De afbeelding kan niet worden weergegeven. Mogelijk is er onvoldoende geheugen beschikbaar om de afbeelding te openen of is de afbeelding beschadigd. Start de computer opnieuw op en open het bestand opnieuw. Als de afbeelding nog steeds wordt voorgesteld door een rode X, kunt u de afbeelding verwijderen en opnieuw invoegen. De afbeelding kan niet worden weergegeven. Mogelijk is er onvoldoende geheugen beschikbaar om de afbeelding te openen of is de afbeelding beschadigd. Start de computer opnieuw op en open het bestand opnieuw. Als de afbeelding nog steeds wordt voorgesteld door een rode X, kunt u de afbeelding verwijderen en opnieuw invoegen. De afbeelding kan niet worden weergegeven. Mogelijk is er onvoldoende geheugen beschikbaar om de afbeelding te openen of is de afbeelding beschadigd. Start de computer opnieuw op en open het bestand opnieuw. Als de afbeelding nog steeds wordt voorgesteld door een rode X, kunt u de afbeelding verwijderen en opnieuw invoegen. De afbeelding kan niet worden weergegeven. Mogelijk is er onvoldoende geheugen beschikbaar om de afbeelding te openen of is de afbeelding beschadigd. Start de computer opnieuw op en open het bestand opnieuw. Als de afbeelding nog steeds wordt voorgesteld door een rode X, kunt u de afbeelding verwijderen en opnieuw invoegen. 1. What type of partners are in the cluster? 2. Set up a profile 3. Answer top 500 quesgons honestly 4. Let computer assign the importance of each quesgon 5. NoGfy partner by automagcally visigng their profiles Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 52

53 Self- branding Big Data insights Self-branding Better Matching Users all must brand themselves in a specific way in order to get whatever they are looking for, in this case a relagonship. It requires users to brand themselves as products that other users would poten;ally want to buy or more accurately get to know beper based on how they market themselves differently than every other individual looking for companionship on the site. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 53

54 Summary CreaGvity InnovaGon Big Data is everywhere! RelaGonships and dependencies Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle ConfidenGal Internal/Restricted/Highly Restricted 54

55

.Policy framework. .Themes and Actions.Civitas and EU funding instrumens.future vision. Overview. Plan on Urban Mobility

.Policy framework. .Themes and Actions.Civitas and EU funding instrumens.future vision. Overview. Plan on Urban Mobility Action Plan on Urban Mobility EUROPEAN COMMISSION 1 ADOPTED ON 30 SEPTEMBER 2009 Overview Policy framework Action Plan on Urban Mobility Themes and Actions Civitas and EU funding instrumens Future vision

More information

EMERGENCIES IVAO BE 28 OCT. 2006. by Bob van der Flier IVAO-TA12 & PATCO

EMERGENCIES IVAO BE 28 OCT. 2006. by Bob van der Flier IVAO-TA12 & PATCO De afbeelding kan niet worden weergegeven. Het is mogelijk dat er onvoldoende geheugen beschikbaar is op de computer om de afbeelding te openen of dat de afbeelding beschadigd is. Start de computer opnieuw

More information

Data and Application Migration The do s and don'ts. Iris Pinkster Professional Testing

Data and Application Migration The do s and don'ts. Iris Pinkster Professional Testing Data and Application Migration The do s and don'ts Iris Pinkster Professional Testing 1 Agenda - Introduction - Migration Statistics - Drivers for Migration - Migration Strategies - Test Strategies - Impact

More information

BIG DATA ANALYTICS REFERENCE ARCHITECTURES AND CASE STUDIES

BIG DATA ANALYTICS REFERENCE ARCHITECTURES AND CASE STUDIES BIG DATA ANALYTICS REFERENCE ARCHITECTURES AND CASE STUDIES Relational vs. Non-Relational Architecture Relational Non-Relational Rational Predictable Traditional Agile Flexible Modern 2 Agenda Big Data

More information

Welkom in de wereld van EDI en de zakelijke kansen op langer termijn

Welkom in de wereld van EDI en de zakelijke kansen op langer termijn Welkom in de wereld van EDI en de zakelijke kansen op langer termijn Sectorsessie mode 23 maart 2016 ISRID VAN GEUNS IS WORKS IS BOUTIQUES Let s get connected! Triumph Without EDI Triumph Let s get connected

More information

Cloud. Gebruik. Cases.

Cloud. Gebruik. Cases. Cloud. Gebruik. Cases. Dé cloud bestaat niet. maakt cloud concreet 2 Overview Cloud Gebruik. Christiaan Hoos Alliance Manager Microsoft 3 Why Cloud? Cloud? 4 Cloud Promises... increase QoS improve Agility

More information

Direct oral anticoagulants in daily care: what do we know today and what are the remaining issues?

Direct oral anticoagulants in daily care: what do we know today and what are the remaining issues? De afbeelding kan niet worden weergegeven. Mogelijk is er onvoldoende geheugen beschikbaar om de afbeelding te openen of is de afbeelding beschadigd. Start de computer opnieuw op en open het bestand opnieuw.

More information

Cloud. Transformatie. Cases.

Cloud. Transformatie. Cases. Cloud. Transformatie. Cases. Dé cloud bestaat niet. maakt cloud concreet 2 IT Transformatie. Cloud? De vraag is niet of we gaan, maar wanneer en hoe #sogetidoethet Matthias Radder Cloud Consultant 3 In

More information

Big Data. The Big Picture. Our flexible and efficient Big Data solu9ons open the door to new opportuni9es and new business areas

Big Data. The Big Picture. Our flexible and efficient Big Data solu9ons open the door to new opportuni9es and new business areas Big Data The Big Picture Our flexible and efficient Big Data solu9ons open the door to new opportuni9es and new business areas What is Big Data? Big Data gets its name because that s what it is data that

More information

Organisaties groot en klein, beginnen zich meer en meer te realiseren dat inzicht in (real-time) data helpt

Organisaties groot en klein, beginnen zich meer en meer te realiseren dat inzicht in (real-time) data helpt Data Virtualization, power to innovate with Agile data Drs. Patrick Berkhout, Enterprise en Software Architect, Trivento Organisaties groot en klein, beginnen zich meer en meer te realiseren dat inzicht

More information

Load Balancing Lync 2013. Jaap Wesselius

Load Balancing Lync 2013. Jaap Wesselius Load Balancing Lync 2013 Jaap Wesselius Agenda Introductie Interne Load Balancing Externe Load Balancing Reverse Proxy Samenvatting & Best Practices Introductie Load Balancing Lync 2013 Waarom Load Balancing?

More information

Memorandum. Zie bijlage. Behavioural and Societal Sciences Kampweg 5 3769 DE Soesterberg Postbus 23 3769 ZG Soesterberg. Van Dr. J.B.F.

Memorandum. Zie bijlage. Behavioural and Societal Sciences Kampweg 5 3769 DE Soesterberg Postbus 23 3769 ZG Soesterberg. Van Dr. J.B.F. Memorandum Van Dr. J.B.F. van Erp Onderwerp epartner architecture workshops 'The Results' Behavioural and Societal Sciences Kampweg 5 3769 DE Soesterberg Postbus 23 3769 ZG Soesterberg www.tno.nl T +31

More information

Internet of Things: What is going to change in our lives

Internet of Things: What is going to change in our lives Internet of Things: What is going to change in our lives Amrith NAWOOR Technology Manager, SADC & EA - Oracle World Telecommunication and Information Society Day May 18, 2015 Safe Harbor Statement The

More information

Operationalizing Customer Experience Initiatives

Operationalizing Customer Experience Initiatives Operationalizing Customer Experience Initiatives Applied Business Architecture Jason G. Fish Director, Business Strategy & Architecture Oracle Corp. Whynde Melaragno Business Architecture Practice Director

More information

The Perfect Storm in IT

The Perfect Storm in IT The Perfect Storm in IT Nice to meet you. I m William ( @wvisterin ) Smart Business Strategies Smart Business Strategies The only Belgian IT magazine that takes the business manager in perspective Business

More information

Welkom! Copyright 2014 Oracle and/or its affiliates. All rights reserved.

Welkom! Copyright 2014 Oracle and/or its affiliates. All rights reserved. Welkom! WIE? Bestuurslid OGh met BI / WA ervaring Bepalen activiteiten van de vereniging Deelname in organisatie commite van 1 of meerdere events Faciliteren van de SIG s Redactie van OGh-Visie Onderhouden

More information

Solving today's integra@on challenges with Oracle SOA Suite, and Oracle Coherence

Solving today's integra@on challenges with Oracle SOA Suite, and Oracle Coherence Solving today's integra@on challenges with Oracle SOA Suite, and Oracle Coherence Asaf Lev Sales Consul@ng asaf.lev@oracle.com Agenda Industry Trends Oracle SOA Suite Oracle Coherence Oracle Service Bus

More information

* With contributions of: Edwin de Jonge and Paul van den Hurk. Definition and the 3 V s. Can Big Data be used for official statistics?

* With contributions of: Edwin de Jonge and Paul van den Hurk. Definition and the 3 V s. Can Big Data be used for official statistics? Big Data (and official statistics) Piet Daas and Mark van der Loo* 3 Statistics Netherlands * With contributions of: Edwin de Jonge and Paul van den Hurk Overview What s Big Data? Definition and the 3

More information

GMP-Z Annex 15: Kwalificatie en validatie

GMP-Z Annex 15: Kwalificatie en validatie -Z Annex 15: Kwalificatie en validatie item Gewijzigd richtsnoer -Z Toelichting Principle 1. This Annex describes the principles of qualification and validation which are applicable to the manufacture

More information

Safe Harbor Statement

Safe Harbor Statement Safe Harbor Statement The following is intended to outline our general product direcgon. It is intended for informagon purposes only, and may not be incorporated into any contract. It is not a commitment

More information

Met wie moet je als erasmusstudent het eerst contact opnemen als je aankomt?

Met wie moet je als erasmusstudent het eerst contact opnemen als je aankomt? Erasmusbestemming: University of Edinburgh, Edinburgh, UK Academiejaar: 2011-2012 Één/twee semester(s) Universiteit Waar is de universiteit ergens gelegen (in het centrum/ ver uit het centrum)? For law

More information

IBM Predictive Analytics Solutions

IBM Predictive Analytics Solutions IBM Predictive Analytics Solutions Koenraad De Cock Wannes Rosius 2014 IBM Corporation 2014 IBM Corporation 1 Agenda Overzicht van de IBM oplossingen De Academische- vs de Business-wereld, een reflectie

More information

Maken we genoeg meters?

Maken we genoeg meters? Duurzaamheid in het HBO Maken we genoeg meters? 31 januari 2013 A.J.Gilbert Silvius Hogeschool Utrecht Van Aetsveld, project- en verandermanagement Duurzaamheid Hype of hoop? Green IT Computers generates

More information

Metadata Management as part of Data Governance and Data Stewardship at ebay, Inc. Mark Uksusman Sr. Manager, Enterprise Data Architecture, ebay, Inc.

Metadata Management as part of Data Governance and Data Stewardship at ebay, Inc. Mark Uksusman Sr. Manager, Enterprise Data Architecture, ebay, Inc. Metadata Management as part of Data Governance and Data Stewardship at ebay, Inc. Mark Uksusman Sr. Manager, Enterprise Data Architecture, ebay, Inc. 50,000 Categories of Products on ebay.com Scale at

More information

DAMA NY DAMA Day October 17, 2013 IBM 590 Madison Avenue 12th floor New York, NY

DAMA NY DAMA Day October 17, 2013 IBM 590 Madison Avenue 12th floor New York, NY Big Data Analytics DAMA NY DAMA Day October 17, 2013 IBM 590 Madison Avenue 12th floor New York, NY Tom Haughey InfoModel, LLC 868 Woodfield Road Franklin Lakes, NJ 07417 201 755 3350 tom.haughey@infomodelusa.com

More information

What can Office 365 do for your organization? Cor Kroon

What can Office 365 do for your organization? Cor Kroon What can Office 365 do for your organization? Cor Kroon Ciber Knowledge Carrousel 2013 What can Office 365 do for your Organization? Cor Kroon Business Analyst / Senior Microsoft Professional cor.kroon@ciber.nl

More information

QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM

QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM QlikView Technical Case Study Series Big Data June 2012 qlikview.com Introduction This QlikView technical case study focuses on the QlikView deployment

More information

Evolution of Information Management Architecture and Development

Evolution of Information Management Architecture and Development Evolution of Information Management Architecture and Development Stewart Bryson Chief Innovation Officer, Rittman Mead! Andrew Bond Head of Enterprise Architecture, Oracle EMEA Oracle Information Management

More information

Big data, the future of statistics

Big data, the future of statistics Big data, the future of statistics Experiences from Statistics Netherlands Dr. Piet J.H. Daas Senior-Methodologist, Big Data research coordinator and Marco Puts, Martijn Tennekes, Alex Priem, Edwin de

More information

What happens when Big Data and Master Data come together?

What happens when Big Data and Master Data come together? What happens when Big Data and Master Data come together? Jeremy Pritchard Master Data Management fgdd 1 What is Master Data? Master data is data that is shared by multiple computer systems. The Information

More information

Disrupt or be disrupted IT Driving Business Transformation

Disrupt or be disrupted IT Driving Business Transformation Disrupt or be disrupted IT Driving Business Transformation Gokula Mishra VP, Big Data & Advanced Analytics Business Analytics Product Group Copyright 2014 Oracle and/or its affiliates. All rights reserved.

More information

Data Refinery with Big Data Aspects

Data Refinery with Big Data Aspects International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 7 (2013), pp. 655-662 International Research Publications House http://www. irphouse.com /ijict.htm Data

More information

Aligning Your Strategic Initiatives with a Realistic Big Data Analytics Roadmap

Aligning Your Strategic Initiatives with a Realistic Big Data Analytics Roadmap Aligning Your Strategic Initiatives with a Realistic Big Data Analytics Roadmap 3 key strategic advantages, and a realistic roadmap for what you really need, and when 2012, Cognizant Topics to be discussed

More information

NL VMUG UserCon March 19 2015

NL VMUG UserCon March 19 2015 NL VMUG UserCon March 19 2015 VMware Microsoft Let's look beyond the war on checkbox compliancy. Introductie Insight24 Technologie is een middel, geen doel 3x M (Mensen, Methoden, Middelen) & Organisatie

More information

The state of DIY. Mix Express DIY event Maarssen 14 mei 2014

The state of DIY. Mix Express DIY event Maarssen 14 mei 2014 The state of DIY!! Mix Express DIY event Maarssen 14 mei 2014 Inleiding Mix press DIY sessie Maarssen 14 mei 2014 Deze presentatie is gemaakt voor het Mix DIY congres en gebaseerd op onze analyse van de

More information

ead management een digital wereld

ead management een digital wereld ead management een digital wereld april 2015 Andeta LauraNuhaan social Selling Today Marketing and Sales need to change Lead management and nurturing Content Marketing /Story telling Social Selling Yelpi

More information

Virtualisatie. voor desktop en beginners. Gert Schepens Slides & Notities op gertschepens.be

Virtualisatie. voor desktop en beginners. Gert Schepens Slides & Notities op gertschepens.be Virtualisatie voor desktop en beginners Gert Schepens Slides & Notities op gertschepens.be Op deze teksten is de Creative Commons Naamsvermelding- Niet-commercieel-Gelijk delen 2.0 van toepassing. Wat

More information

Improving customer service with data 19 may 2015 Maarten Jonker Leiden

Improving customer service with data 19 may 2015 Maarten Jonker Leiden Improving customer service with data 19 may 2015 Maarten Jonker Leiden Contents Introduction Our approach Our practice Increasing our understanding of data and using knowledge Achmea s digital-first principles

More information

IT-waardeketen management op basis van eeuwenoude supply chain kennis

IT-waardeketen management op basis van eeuwenoude supply chain kennis IT-waardeketen management op basis van eeuwenoude supply chain kennis Hans van Aken / November 28, 2012 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject

More information

10 best practices voor een groen IT systeem

10 best practices voor een groen IT systeem 10 best practices voor een groen IT systeem Symposium Groene ICT en Duurzaamheid, mei 2015 Niels van der Zwan, Michiel Cuijpers Software Improvement Group Kennis Netwerk Groene Software +31 20 314 0950

More information

Platform voor Informatiebeveiliging IB Governance en management dashboards

Platform voor Informatiebeveiliging IB Governance en management dashboards Platform voor Informatiebeveiliging IB Governance en management dashboards Johan Bakker MSc CISSP ISSAP Principal Policy Advisor KPN Corporate Center Information Security Governance Agenda Drivers voor

More information

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014 5 Keys to Unlocking the Big Data Analytics Puzzle Anurag Tandon Director, Product Marketing March 26, 2014 1 A Little About Us A global footprint. A proven innovator. A leader in enterprise analytics for

More information

OGH: : 11g in de praktijk

OGH: : 11g in de praktijk OGH: : 11g in de praktijk Real Application Testing SPREKER : E-MAIL : PATRICK MUNNE PMUNNE@TRANSFER-SOLUTIONS.COM DATUM : 14-09-2010 WWW.TRANSFER-SOLUTIONS.COM Real Application Testing Uitleg Real Application

More information

Hortonworks & SAS. Analytics everywhere. Page 1. Hortonworks Inc. 2011 2014. All Rights Reserved

Hortonworks & SAS. Analytics everywhere. Page 1. Hortonworks Inc. 2011 2014. All Rights Reserved Hortonworks & SAS Analytics everywhere. Page 1 A change in focus. A shift in Advertising From mass branding A shift in Financial Services From Educated Investing A shift in Healthcare From mass treatment

More information

Big Data & Analytics. The. Deal. About. Jacob Büchler jbuechler@dk.ibm.com Cand. Polit. IBM Denmark, Solution Exec. 2013 IBM Corporation

Big Data & Analytics. The. Deal. About. Jacob Büchler jbuechler@dk.ibm.com Cand. Polit. IBM Denmark, Solution Exec. 2013 IBM Corporation The Big Data & Analytics Deal About Jacob Büchler jbuechler@dk.ibm.com Cand. Polit. IBM Denmark, Solution Exec. 1 Big Data is All Data from Everywhere Big Data Is Becoming The Next Natural Resource We

More information

Getting Business Value from Customer Engagement. Chet Geschickter, Research Director Gartner Energy & Utilities Industries Research

Getting Business Value from Customer Engagement. Chet Geschickter, Research Director Gartner Energy & Utilities Industries Research Getting Business Value from Customer Engagement Chet Geschickter, Research Director Gartner Energy & Utilities Industries Research 1 How Gartner Delivers Value Gartner research helps clients review, develop,

More information

IBM G-Cloud - IBM Social Media Analytics Software as a Service

IBM G-Cloud - IBM Social Media Analytics Software as a Service IBM G-Cloud - IBM Social Media Analytics Software as a Service Service Definition 1 1. Summary 1.1 Service Description IBM Social Media Analytics Software as a Service is a powerful Cloud-based tool for

More information

Storage in Microsoft Azure Wat moet ik daarmee? Bert Wolters @bertwolters

Storage in Microsoft Azure Wat moet ik daarmee? Bert Wolters @bertwolters Storage in Microsoft Azure Wat moet ik daarmee? Bert Wolters @bertwolters Welk deel van het platform hebben we nu behandeld? Agenda Recap: Storage Account Nieuw! Premium Storage Nieuw! Native backup voor

More information

HP Vertica at MIT Sloan Sports Analytics Conference March 1, 2013 Will Cairns, Senior Data Scientist, HP Vertica

HP Vertica at MIT Sloan Sports Analytics Conference March 1, 2013 Will Cairns, Senior Data Scientist, HP Vertica HP Vertica at MIT Sloan Sports Analytics Conference March 1, 2013 Will Cairns, Senior Data Scientist, HP Vertica So What s the market s definition of Big Data? Datasets whose volume, velocity, variety

More information

Emerging Geospatial Trends The Convergence of Technologies. Jim Steiner Vice President, Product Management

Emerging Geospatial Trends The Convergence of Technologies. Jim Steiner Vice President, Product Management Emerging Geospatial Trends The Convergence of Technologies Jim Steiner Vice President, Product Management United Nation Analysis Initiative on Global GeoSpatial Information Management Future Trends Technology

More information

Hoe onze wereld aan het veranderen is

Hoe onze wereld aan het veranderen is Hoe onze wereld aan het veranderen is Michiel Schaalje CTO Cisco Nederland Sinds 1996 actief binnen Cisco Vanaf 2006 verantwoordelijk voor o.a. de gehele Nederlandse presales organisatie Richt zich vanuit

More information

The 3 questions to ask yourself about BIG DATA

The 3 questions to ask yourself about BIG DATA The 3 questions to ask yourself about BIG DATA Do you have a big data problem? Companies looking to tackle big data problems are embarking on a journey that is full of hype, buzz, confusion, and misinformation.

More information

Ins+tuto Superior Técnico Technical University of Lisbon. Big Data. Bruno Lopes Catarina Moreira João Pinho

Ins+tuto Superior Técnico Technical University of Lisbon. Big Data. Bruno Lopes Catarina Moreira João Pinho Ins+tuto Superior Técnico Technical University of Lisbon Big Data Bruno Lopes Catarina Moreira João Pinho Mo#va#on 2 220 PetaBytes Of data that people create every day! 2 Mo#va#on 90 % of Data UNSTRUCTURED

More information

Simplifying Big Data Analytics: Unifying Batch and Stream Processing. John Fanelli,! VP Product! In-Memory Compute Summit! June 30, 2015!!

Simplifying Big Data Analytics: Unifying Batch and Stream Processing. John Fanelli,! VP Product! In-Memory Compute Summit! June 30, 2015!! Simplifying Big Data Analytics: Unifying Batch and Stream Processing John Fanelli,! VP Product! In-Memory Compute Summit! June 30, 2015!! Streaming Analy.cs S S S Scale- up Database Data And Compute Grid

More information

Achieving Customer Intelligence with Splunk Enterprise

Achieving Customer Intelligence with Splunk Enterprise Copyright 2013 Splunk Inc. #splunkconf Achieving Customer Intelligence with Splunk Enterprise Leon Li IT Director, Far EasTone Telco Taiwan About Far EasTone! Among leading Taiwan telecom operators! Founded

More information

End to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ

End to End Solution to Accelerate Data Warehouse Optimization. Franco Flore Alliance Sales Director - APJ End to End Solution to Accelerate Data Warehouse Optimization Franco Flore Alliance Sales Director - APJ Big Data Is Driving Key Business Initiatives Increase profitability, innovation, customer satisfaction,

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics April 10, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

ANALYTICS IN BIG DATA ERA

ANALYTICS IN BIG DATA ERA ANALYTICS IN BIG DATA ERA ANALYTICS TECHNOLOGY AND ARCHITECTURE TO MANAGE VELOCITY AND VARIETY, DISCOVER RELATIONSHIPS AND CLASSIFY HUGE AMOUNT OF DATA MAURIZIO SALUSTI SAS Copyr i g ht 2012, SAS Ins titut

More information

MINISTRY OF DEFENCE LANGUAGES EXAMINATIONS BOARD

MINISTRY OF DEFENCE LANGUAGES EXAMINATIONS BOARD Name: Candidate Registration Number: Date of Exam: MINISTRY OF DEFENCE LANGUAGES EXAMINATIONS BOARD SURVIVAL SLP1 DUTCH PAPER A Reading Task 1 Task 2 Time allowed Translation Comprehension 15 minutes Candidates

More information

We are building the next generation of Big Data and Analytics solutions!

We are building the next generation of Big Data and Analytics solutions! We are building the next generation of Big Data and Analytics solutions! Background 26 years Experience IT Industry 12 Years Solutions Architect - International Profile Passionate about Technology Genuine

More information

IT Tools for SMEs and Business Innovation

IT Tools for SMEs and Business Innovation Purpose This Quick Guide is one of a series of information products targeted at small to medium sized enterprises (SMEs). It is designed to help SMEs better understand, and take advantage of, new information

More information

How Big Is Big Data Adoption? Survey Results. Survey Results... 4. Big Data Company Strategy... 6

How Big Is Big Data Adoption? Survey Results. Survey Results... 4. Big Data Company Strategy... 6 Survey Results Table of Contents Survey Results... 4 Big Data Company Strategy... 6 Big Data Business Drivers and Benefits Received... 8 Big Data Integration... 10 Big Data Implementation Challenges...

More information

Architecting your Business for Big Data Your Bridge to a Modern Information Architecture

Architecting your Business for Big Data Your Bridge to a Modern Information Architecture Architecting your Business for Big Data Your Bridge to a Modern Information Architecture Robert Stackowiak Vice President, Information Architecture & Big Data Oracle Safe Harbor Statement The following

More information

De la Business Intelligence aux Big Data. Marie- Aude AUFAURE Head of the Business Intelligence team Ecole Centrale Paris. 22/01/14 Séminaire Big Data

De la Business Intelligence aux Big Data. Marie- Aude AUFAURE Head of the Business Intelligence team Ecole Centrale Paris. 22/01/14 Séminaire Big Data De la Business Intelligence aux Big Data Marie- Aude AUFAURE Head of the Business Intelligence team Ecole Centrale Paris 22/01/14 Séminaire Big Data 1 Agenda EvoluHon of Business Intelligence SemanHc Technologies

More information

Making, Moving and Shaking a Community of Young Global Citizens Resultaten Nulmeting GET IT DONE

Making, Moving and Shaking a Community of Young Global Citizens Resultaten Nulmeting GET IT DONE Making, Moving and Shaking a Community of Young Global Citizens Resultaten Nulmeting GET IT DONE Rianne Verwijs Freek Hermens Inhoud Summary 5 1 Introductie en leeswijzer 7 2 Achtergrond en onderzoeksopzet

More information

Taking on Big Data in Li-le Steps September 24, 2015. Jason Milesko jmilesko@gmail.com

Taking on Big Data in Li-le Steps September 24, 2015. Jason Milesko jmilesko@gmail.com Taking on Big Data in Li-le Steps September 24, 2015 Jason Milesko jmilesko@gmail.com Today s Goals 1. Be-er understand what is Big Data 2. Discuss how credit unions stack up 3. Start thinking about ways

More information

Network Assessment Client Risk Report Demo

Network Assessment Client Risk Report Demo Network Assessment Client Risk Report Demo Prepared by: Henry Knoop Opmerking: Alle informatie in dit rapport is uitsluitend bestemd voor gebruik bij bovenvermelde client. Het kan vertrouwelijke en persoonlijke

More information

Oracle Cloud 25.09.14. Bjarte Drivenes Enterprise Architect. Copyright 2014 Oracle and/or its affiliates. All rights reserved.

Oracle Cloud 25.09.14. Bjarte Drivenes Enterprise Architect. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Oracle Cloud 25.09.14 Bjarte Drivenes Enterprise Architect Copyright 2014 Oracle and/or its affiliates. All rights reserved. Copyright 2014 Oracle and/or its affiliates. All rights reserved. Agenda Private

More information

The Role of Nutanix in the Public /Private / Hybrid Cloud Spectrum

The Role of Nutanix in the Public /Private / Hybrid Cloud Spectrum The Role of Nutanix in the Public /Private / Hybrid Cloud Spectrum Chris Howard Vice President, Nutanix Federal Phil Ditzel Senior SE Public Cloud Let s start with the definition NIST s Defini-on: A model

More information

and Analytic s i n Consu m e r P r oducts

and Analytic s i n Consu m e r P r oducts Global Headquarters: 5 Speen Street Framingham, MA 01701 USA P.508.988.7900 F.508.988.7881 www.idc-mi.com Creating Big O p portunities with Big Data and Analytic s i n Consu m e r P r oducts W H I T E

More information

Ganzheitliches Datenmanagement

Ganzheitliches Datenmanagement Ganzheitliches Datenmanagement für Hadoop Michael Kohs, Senior Sales Consultant @mikchaos The Problem with Big Data Projects in 2016 Relational, Mainframe Documents and Emails Data Modeler Data Scientist

More information

Building the Internet of Things Jim Green - CTO, Data & Analytics Business Group, Cisco Systems

Building the Internet of Things Jim Green - CTO, Data & Analytics Business Group, Cisco Systems Building the Internet of Things Jim Green - CTO, Data & Analytics Business Group, Cisco Systems Brian McCarson Sr. Principal Engineer & Sr. System Architect, Internet of Things Group, Intel Corp Mac Devine

More information

Using Mobile to Capture In- the- Moment Insights

Using Mobile to Capture In- the- Moment Insights With the global leader in sampling and data services Using Mobile to Capture In- the- Moment Insights Saran Ganesh Director, Mobile product marke8ng 2015 Survey Sampling Interna6onal 1 During this webcast

More information

www.pwc.com/oracle Next presentation starting soon Business Analytics using Big Data to gain competitive advantage

www.pwc.com/oracle Next presentation starting soon Business Analytics using Big Data to gain competitive advantage www.pwc.com/oracle Next presentation starting soon Business Analytics using Big Data to gain competitive advantage If every image made and every word written from the earliest stirring of civilization

More information

Management Accountants and IT Professionals providing Better Information = BI = Business Intelligence. Peter Simons peter.simons@cimaglobal.

Management Accountants and IT Professionals providing Better Information = BI = Business Intelligence. Peter Simons peter.simons@cimaglobal. Management Accountants and IT Professionals providing Better Information = BI = Business Intelligence Peter Simons peter.simons@cimaglobal.com Agenda Management Accountants? The need for Better Information

More information

AGENDA. What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story. Our BIG DATA Roadmap. Hadoop PDW

AGENDA. What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story. Our BIG DATA Roadmap. Hadoop PDW AGENDA What is BIG DATA? What is Hadoop? Why Microsoft? The Microsoft BIG DATA story Hadoop PDW Our BIG DATA Roadmap BIG DATA? Volume 59% growth in annual WW information 1.2M Zetabytes (10 21 bytes) this

More information

IP-NBM. Copyright Capgemini 2012. All Rights Reserved

IP-NBM. Copyright Capgemini 2012. All Rights Reserved IP-NBM 1 De bescheidenheid van een schaker 2 Maar wat betekent dat nu 3 De drie elementen richting onsterfelijkheid Genomics Artifical Intelligence (nano)robotics 4 De impact van automatisering en robotisering

More information

Big Data @ CBS. Experiences at Statistics Netherlands. Dr. Piet J.H. Daas Methodologist, Big Data research coördinator. Statistics Netherlands

Big Data @ CBS. Experiences at Statistics Netherlands. Dr. Piet J.H. Daas Methodologist, Big Data research coördinator. Statistics Netherlands Big Data @ CBS Experiences at Statistics Netherlands Dr. Piet J.H. Daas Methodologist, Big Data research coördinator Statistics Netherlands April 20, Enschede Overview Big Data Research theme at Statistics

More information

BIG DATA: PROMISE, POWER AND PITFALLS NISHANT MEHTA

BIG DATA: PROMISE, POWER AND PITFALLS NISHANT MEHTA BIG DATA: PROMISE, POWER AND PITFALLS NISHANT MEHTA Agenda Promise Definition Drivers of and for Big Data Increase revenue using Big Data Power Optimize operations and decrease costs Discover new revenue

More information

Business Intelligence Project Management 101

Business Intelligence Project Management 101 Business Intelligence Project Management 101 Managing BI Projects within the PMI Process Groups Too many times, Business Intelligence (BI) and Data Warehousing project managers are ill-equipped to handle

More information

Citrix Access Gateway: Implementing Enterprise Edition Feature 9.0

Citrix Access Gateway: Implementing Enterprise Edition Feature 9.0 coursemonstercom/uk Citrix Access Gateway: Implementing Enterprise Edition Feature 90 View training dates» Overview Nederlands Deze cursus behandelt informatie die beheerders en andere IT-professionals

More information

Raul F. Chong Senior program manager Big data, DB2, and Cloud IM Cloud Computing Center of Competence - IBM Toronto Lab, Canada

Raul F. Chong Senior program manager Big data, DB2, and Cloud IM Cloud Computing Center of Competence - IBM Toronto Lab, Canada What is big data? Raul F. Chong Senior program manager Big data, DB2, and Cloud IM Cloud Computing Center of Competence - IBM Toronto Lab, Canada 1 2011 IBM Corporation Agenda The world is changing What

More information

Telemetry: The Customer Experience

Telemetry: The Customer Experience Copyright 2014 Splunk Inc. Telemetry: The Customer Experience Simon Warrington Senior Program Manager, Microso@ Disclaimer During the course of this presentagon, we may make forward- looking statements

More information

Reduce and manage operating costs and improve efficiency. Support better business decisions based on availability of real-time information

Reduce and manage operating costs and improve efficiency. Support better business decisions based on availability of real-time information Data Management Solutions Horizon Software Solution s Data Management Solutions provide organisations with confidence in control of their data as they change systems and implement new solutions. Data is

More information

Taking Data Analytics to the Next Level

Taking Data Analytics to the Next Level Taking Data Analytics to the Next Level Implementing and Supporting Big Data Initiatives What Is Big Data and How Is It Applicable to Anti-Fraud Efforts? 2 of 20 Definition Gartner: Big data is high-volume,

More information

Fujitsu Big Data Software Use Cases

Fujitsu Big Data Software Use Cases Fujitsu Big Data Software Use s Using Big Data Opens the Door to New Business Areas The use of Big Data is needed in order to discover trends and predictions, hidden in data generated over the course of

More information

Third Platform Apps & EMC: Redefining IT & Helping Our Customers Lead The Way. Name

Third Platform Apps & EMC: Redefining IT & Helping Our Customers Lead The Way. Name 1 Third Platform Apps & EMC: Redefining IT & Helping Our Customers Lead The Way Name 2 3 Home, Driving & Work 3 rd Platform A Definition Four Interdependent Trends: Social Interaction, Mobility, Cloud,

More information

Quick Guide: Selecting ICT Tools for your Business

Quick Guide: Selecting ICT Tools for your Business Quick Guide: Selecting ICT Tools for your Business This Quick Guide is one of a series of information products targeted at small to medium sized businesses. It is designed to help businesses better understand,

More information

Uw partner in system management oplossingen

Uw partner in system management oplossingen Uw partner in system management oplossingen User Centric IT Bring your Own - Corporate Owned Onderzoek Forrester Welke applicatie gebruik je het meest op mobiele devices? Email 76% SMS 67% IM / Chat 48%

More information

what can we do with botnet data?

what can we do with botnet data? what can we do with botnet data? prof.dr. Ronald Leenes r.e.leenes@uvt.nl TILT - Tilburg Institute for Law, Technology, and Society background SURFnet (Dutch NREN) was offered 700 GB of data obtained from

More information

All You Wanted to Know About Big Data Projects Chida Sadayappan @schida. Jan 2014

All You Wanted to Know About Big Data Projects Chida Sadayappan @schida. Jan 2014 All You Wanted to Know About Big Data Projects Chida Sadayappan @schida Jan 2014 1 WHAT WE DISCUSS HERE AGENDA > > > > > > Need History Open Source - Hadoop BigData EcoSystem Use Cases Managing BigData

More information

Welcome to Services Discovery Channel. Host: Jean Wong, Head of Service Marketing, Asia Pacific, Japan and Greater China

Welcome to Services Discovery Channel. Host: Jean Wong, Head of Service Marketing, Asia Pacific, Japan and Greater China Welcome to Services Discovery Channel Host: Jean Wong, Head of Service Marketing, Asia Pacific, Japan and Greater China Connecting Analytics to Insight Are You Ready? Keynote Speakers: Mike Riegel, VP,

More information

New Broadband and Dynamic Infrastructures for the Internet of the Future

New Broadband and Dynamic Infrastructures for the Internet of the Future New Broadband and Dynamic Infrastructures for the Internet of the Future Margarete Donovang-Kuhlisch, Government Industry Technical Leader, Europe mdk@de.ibm.com Agenda Challenges for the Future Intelligent

More information

Lifting the Fog: The High Potential of Cloud Computing Paul Daugherty, Chief Technology Architect February 19, 2010

Lifting the Fog: The High Potential of Cloud Computing Paul Daugherty, Chief Technology Architect February 19, 2010 Lifting the Fog: The High Potential of Cloud Computing Paul Daugherty, Chief Technology Architect February 19, 2010 IT leaders are looking to the clouds Cloud 75% of IT decision makers knowledgeable or

More information

Big Data: Business Insight for Power and Utilities

Big Data: Business Insight for Power and Utilities Big Data: Business Insight for Power and Utilities A Look at Big Data By now, most enterprises have encountered the term Big Data. What they encounter less is an understanding of what Big Data means for

More information

Advanced Metering Infrastructure

Advanced Metering Infrastructure Advanced Metering Infrastructure Research Project 2 Vic Ding SNE, UvA February 8th 2012 Agenda Background Research motivation and questions Research methods Research findings Stakeholders Legislation Smart

More information

De veranderende samenleving. De smartphone revolutie

De veranderende samenleving. De smartphone revolutie De veranderende samenleving De smartphone revolutie GfK Retail and Technology Wie zijn wij? GfK Retail and Technology The Netherlands 21 November 2011 Consumenten Electronica, Telecom, IT, Klein- & Groot

More information

IC Rating NPSP Composieten BV. 9 juni 2010 Variopool

IC Rating NPSP Composieten BV. 9 juni 2010 Variopool IC Rating NPSP Composieten BV 9 juni 2010 Variopool AGENDA: The future of NPSP Future IC Rating TM NPSP Composieten BV 2 Bottom line 3 Bottom line 4 Definition of Intangibles The factors not shown in the

More information

Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012. Viswa Sharma Solutions Architect Tata Consultancy Services

Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012. Viswa Sharma Solutions Architect Tata Consultancy Services Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012 Viswa Sharma Solutions Architect Tata Consultancy Services 1 Agenda What is Hadoop Why Hadoop? The Net Generation is here Sizing the

More information

How to transform data into dollars this is always about Business Intelligence

How to transform data into dollars this is always about Business Intelligence Swiss BI Day - 03/04/2014! How to transform data into dollars this is always about Business Intelligence! Philippe Nieuwbourg philippe.nieuwbourg@decideo.com A lot of things in common between oil and

More information