2014 15 IT trend

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2014. 6.

오산대학교 교수 배재호

[email protected]

IT Trend 眺望

mailto:[email protected]

Who am I ?

l저서 - 공급망관리: 실무적용을 위한 계획에서 운영까지, 도서출판 두남, 2010. 6.

lTrading Area Analysis Using Modified Huff Model Based on Analytic Hierarchy Process, JKKITS, 9(1), pp.179-190, 2014.

lEfficiency Comparision and Performance Targets for Academic Departments in the Local Private College Using DEA, JKIIE, 39(4), pp.298-312, 2013.

lDerivation of Key Process Input Variables on Flim Production Line Using Analytic Hierarchy Process, JKIPE, 17(4), pp.35-44, 2012

lAn Empirical Approach to Evaluate Management Performance Using a Trading Area Analysis: Focused on Small and Medium-sized Retail Business, JDS, 10(12), pp.5-11, 2012.

lDerivation of Key Process Input Variables on Film Production Line Using Analytic Hierarchy Process, JKIPE, 17(4), pp.35-44, 2012.

lMeasurement of Overall Equipment Effectiveness Considering Processing Materials and Methods, JKIPE, 16(3), pp.25-33, 2011.

lMature Market Sub-segmentation and Its Evaluation by the Degree of Homogeneity, JDS, 8(3), pp.27-35, 2010.

lA Study on the Customer Experience Analysis for the Silver Generation in the Communication Service Market using CEM, JSKISE, 32(2), pp.66—75, 2009.

lPractical setup time implementation in the roll-based manufacturing practice having print operations, IE Interface, 22(1), pp. 85-94, 2009.

lQuality control system development corresponding to the floor status for improving process control level, JKIPE, 13(2), pp. 59-67, 2008.

Books/Papers

Major ConsultingPractices

배재호 (Jae-Ho Bae, Ph. D.)

공학박사 (인공신경망, SCM, 성과관리)

2014 최우수논문상 (한국지식정보기술학회) 2012 설비관리 학술상 (대한설비관리학회) 2012 우수논문상 (한국지식정보기술학회) 2008 우수논문상 (대한설비관리학회)

l현) 대전과학기술대학교 물류유통경영과 교수/학과장 l현) 대한설비관리학회 이사, 편집위원

l전) EIB Korea, 상무이사 l전) PWC Consulting, Principal Consultant

l전) 아주대학교 e-Business 학부, 겸임교수 l전) 삼육대학교, 외래교수

Who am I ?

Books/Papers

Major ConsultingPractices

Researches or Consultations l 2012.03~2012.12: 혜천대학교 학과/계열의 성과평가 및 목표수준 제시l 2012.12~2012.12: 대중소협력재단, Dr. R&R (과제 수행 자문)l 2010.06~2011.05: 중기청,고효율 에너지 기자재 규격에 적합한 LED 가로등 개발l 2009.07~2009.10: 지경부, Innovation Mentor (자동차 산업 ISP 수립)

PI 및 업무 혁신 부문 l 2010.07~2010.12: 율촌화학 필름공장의 CTQ 도출 및 개선 방안 수립l 2008.01~2008.12: 율촌화학 PI Master Plan 및 PI 1차 과제 수행l 2007.09~2007.11: KT 고객경험관리를 통한 신제품/서비스 개발l 2006.04~2006.06: 도레이새한 PI Master Plan 수립l 2004.04~2004.06: 율촌화학 생산 부문 PI Master Plan 수립l 2002.03~2002.06: SKT 내부 IT 고객 지원 프로세스 개선l 2001.07~2001.09: CCKBC (코카콜라) 생산 전략 수립

알고리즘 설계 및 구현 부문 l 2007.03~2007.08: KCC의 생산계획 알고리즘 설계l 2006.11~2007.03: 동진쎄미켐의 스케줄링 알고리즘 설계l 2004.08~2005.01: KAC의 스케줄링 알고리즘 설계l 1998.09~1999.10: 산업자원부, 한국형 ERP 개발을 위한 제조부문 설계l 1997.06~1998.06: 농심의 재고 자동 보충 시스템/수요예측 시스템의 설계 및 개발l 1996.11~1997.06: 정보통신부, 직렬통신 설비의 원격제어를 위한 converter 개발l 1995.11~1996.03: 과학기술처, MMI 구현

기타 시스템 구축 l동진쎄미켐의 품질관리 시스템 구축l율촌화학의 BI 시스템 구축l동진쎄미켐의 MES 시스템 구축l MCM의 ERP Roll-outl율촌화학의 생산계획 시스템 구축l율촌화학의 MES 구축l KAC의 MES 구축l KT의 ERP 구축l동부전자의 ERP 구축l팬택의 ERP 구축l풀무원의 ERP 구축

배재호 (Jae-Ho Bae, Ph. D.)

공학박사 (인공신경망, SCM, 성과관리)

2014 최우수논문상 (한국지식정보기술학회) 2012 설비관리 학술상 (대한설비관리학회) 2012 우수논문상 (한국지식정보기술학회) 2008 우수논문상 (대한설비관리학회)

l현) 대전과학기술대학교 물류유통경영과 교수/학과장 l현) 대한설비관리학회 이사, 편집위원

l전) EIB Korea, 상무이사 l전) PWC Consulting, Principal Consultant

l전) 아주대학교 e-Business 학부, 겸임교수 l전) 삼육대학교, 외래교수

It is not the strongest of the species that survives nor the most intelligent, it is those most adaptive to change.

"

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가장 강한 자가 살아 남는 것이 아니라, 변화에 잘 적응하는 자가 살아 남는다.

Charles Robert Darwin, 1809.2.12 ~ 1882.4.19영국의 생물학자, 철학자. 주요 저서: 종의 기원

haos and OrderC IT Trend prediction

art 1P 2012년부터 지속적으로 제기되고 있는 Keyword는?

Mobile Cloud Social IoT

eference 1RGartner 선정 10대 전략 기술 추이

Rank 2011년 2012년 2013년 2014년

1 클라우드 컴퓨팅 미디어 태블릿 그 이후 모바일 대전 다양한 모바일 기기 관리

2 모바일 앱과 미디어 태블릿 모바일 중심 애플리케이션과 인터페이스

모바일 앱 & HTML 5 모바일 앱과 애플리케이션

3 소셜 커뮤니케이션 및 협업 상황인식과 소셜이 결합된 사용자 경험

퍼스널 클라우드 만물 인터넷

4 비디오 사물인터넷 사물인터넷 하이브리드 클라우드와 서비스 브로커로서의 IT

5 차세대 분석 앱스토어와 마켓 플레이스 하이브리드 IT & 클라우드 컴퓨팅

클라우드/클라이언트 아키텍처

6 소셜 분석 차세대 분석 전략적 빅데이터 퍼스널 클라우드의 시대

7 상황인식 컴퓨팅 빅데이터 실용분석 소프트웨어 정의

8 스토리지급 메모리 인메모리 컴퓨팅 인메모리 컴퓨팅 웹 스케일 IT

9 유비쿼터스 컴퓨팅 저전력 서버 통합생태계 스마트 머신

10 패브릭 기반 컴퓨팅 및 인프라스트럭처

클라우드 컴퓨팅 엔터프라이즈 앱 스토어 3D 프린팅

http://www.alibabaoglan.com/blog/gartners-technology-predictions-2014-2015-2016/

2014년 이후의 IT Trend는?

Converging Forces Derivative Impact Future Disruption

集約派生混亂

art 2P

onverging Forces CMobile Device Diversity & Management

Diverse Devices, Computing Style, and User Environment

BYOD(Bring your own device) Balancing between Privacy vs. Security

onverging Forces CMobile Apps. and Applications

HTML5 Growing Mobile Apps. and declining Application Voice & Video related apps. based on HTML5

onverging Forces C The Internet of Everything

IoT to IoE Internet of People (1.11B people on Facebook, Mar. 2013)

Internet of Things (25B things by 2020) Internet of Information (30T web pages in Google index, 2013)

Internet of Places (3B Foursqure check ins, Jan 2013)

onverging Forces C Hybrid Cloud and IT as Service Broker

Private Cloud vs. Public Cloud

Hybrid Cloud

erivative ImpactDCloud/Client Architecture

Changing envirionment of Cloud & Client System Utilizing space and CPU performance of client

devices

erivative ImpactDThe Era of Personal Cloud

Independance from devices

Data repository on Personal cloud storage not your PC

not a device-centric, but a service-centric Change

erivative ImpactDSoftware Defined Anything

SDx (Software Defined Everything/Anything) Virtualization, Scalability & Elasticity

erivative ImpactDWeb-scale IT

Web-oriented Architectures like Amazone, Google, Facebook, salesforce.com

uture DisruptionF Smart Machine

Siri, Waston Era of smart machine will be come by 2020

uture DisruptionF 3D Printing

Increase 75% in 2014, 200% by 2015 Custome manufacturing era

eview - IT TrendsR

Enterprise Application Development Trends?

6

art 3P

rend 1T Enterprise Application Development Trends

Development moves to the client side

Mainframe C/S WebSmart Client

Business applications get “consumerized”


Business applications of the past focused on function over form. A well-designed, intuitive interface wasn’t so important as a powerful

applications, and users accepted this as normal. These days, that’s changing. Users now expect the types of applications they

can access on their smartphone and tablets-powerful, yet easily understandable applications.

Integration takes ceter stage


According to Gartner, “if application integration does not become a true area of expertise, companies will find themselves at a serious competitive

disadvantage within the next few years.”

Enterprise applicatios get extended to mobile devices


With the rise of mobile devices, the concept of a “typical user” has vanished. The web is no longer limited to a desktop PC.

These days, a user might access a web application using one of many devices.

Application development and delivery shifts to the cloud


Now, am I saying that most businesses will shift their application development to the cloud? Not at all.

However, I believe we’ll see a growing push towards this approach in the coming year.

HTML5 gets widespread business adoption


Browser Ver. Scores

Chrome 35 507

Firefox 29 467

Internet Explorer 11 376

Opera 21 496

Safari 7.0 397

Android 4.4 428

iOS 7.0 412

Windows Phone 8 332

source: http://html5test.com

http://html5test.com

Several keywords to predict future IT Trends

PaaS and BPM Mobile and HTML5

Big data and Real-time Analytics Elastic Application Platform (EAP)

BYOD vs. Security

art 4P

Money Ball

New York Yankees $114,457,768

vs $39,722,689

Oakland Athletics

타율, 타점, 홈런

출루율, 장타율, 사사구율

Big Data

What is Big Data?

How big is BIG?

Big Data“Big Data is the frontier of a firm’s ability to store, process, and access (SPA) all the data it needs to operate effectively, make decisions, reduce risks, and server customers.”Forrester

BORING!“Big Data is general id defined as high volume, velocity and variety information assets that

demand cost-effective, innovative formas of information processing for enhanced insight and decision making”

Gartner

“Big Data is data that exceeds the processing capacity of conventional database ststems. The data is too big, moves too fast, or doesn’t fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it.”

O’Reilly

“Big Data is the data characterized by 3 attributes: volume, variety and velocity.”IBM

“Big Data is the data characterized by 4 key attributes: volume, variety, velocity and value.”Oracle

Big Data

Big Data

Byte : one grain of rice

Big Data


Kilobyte : cup of rice

Big Data



Megabyte : 8 bags of rice

Big Data

ByteByte : one grain of rice



Gigabyte : 3 Semi trucks

Big Data

ByteByte : one grain of rice



Terabyte : 2 Container Ships


Big Data





Petabyte : Blankets Manhattan


Big Data






Exabyte : Blankets West Coast States


Big Data






Exabyte

Zettabyte : Fills the Pacific Ocean

: Blankets West Coast States


Big Data






Exabyte


Yottabyte : A Earth Size Rice Ball



Big Data






Exabyte





Big Data






Exabyte





Big Data






Exabyte





Big Data






Exabyte





Big Data






Exabyte





Big DataExabyte



Big Datais not about the size of the data.

is about the value within the data.

is good for correlation analysis

is not good for cause and effect analysis

Most people don’t know what to do with all the data that they already have.

Big Data is not big, if you know how to use it.

Questions,

Q & A

Answers

Your Desire,

Our Instinct!!

Thank you for your patient listeningJun. 2014, Jaeho BAE@Osan.

IT Trend 조망

End of Document

Created by JHBae.