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© 2014 IBM Corporation 스마트한 분석, 제대로 알고 접근하는 비결 한국IBM 김연진 차장 IBM 빅데이터 분석 성공 사례 세미나

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Page 1: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation

스마트한 분석, 제대로 알고 접근하는 비결

한국IBM 김연진 차장

IBM 빅데이터 분석 성공 사례 세미나

Page 2: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation2

Business Intelligence를 넘어서 Business Analytics 환경으로…

Page 3: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation3

Business Analytics 발전 방향성

Degree of Complexity

Com

petitive A

dvanta

ge

Standard Reporting

Ad hoc reporting

Query/drill down

Alerts

Simulation

Forecasting

Predictive

modeling

Optimizati

on

What exactly is the problem?

What will happen next if ?

What if these trends continue?

What could happen.. ?

What actions are needed?

How many, how often, where?

What happened?

Stochastic

Optimization

Descriptive

Prescriptive

Predictive

How can we achieve the best outcome?

How can we achieve the best outcome

including the effects of variability?

CognitiveCognitive Computing Jarvis, Answer me.

Page 4: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation4

빅데이터 분석 시대에 요구 되는 주요 역량

타입으로 접근하던 기존차트 환경에서 빅데이터에적합한 확장가능한 시각화엔진을 기반으로 보다직관적인 빅데이터 간의상관관계 분석 환경 제공

시각화

사외에 존재하는 정보중에 대표적인 소셜미디어에 대한 분석영역확장을 통하여, 브랜드평판 관리, 가망고객발굴, 잠재적 리스크모니터링 수행

소셜 미디어 분석예측 분석

기존 과거 데이터로 부터조회되던 정보 뿐만 아니라사용자가 복잡한 데이터간의 상관관계를 손쉽게이해하고, 미래를 예측하는분석 역량

Page 5: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation5

1 : 시각화

Page 6: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation6

새로운 시각화 엔진A picture paints a thousand insights

The Business Problem:

− New requirements for visualizations are constantly emerging

− Each requirement is unique and is difficult to meet

The Solution:

− Provide a wider variety of visualizations with the

means to extend and customize

Page 7: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation7

�Flexible – NOT a library of charts

�Multiplatform

− Mobile native

− Web

− Desktop

− Server

IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight

IBM ManyEyesIBM ManyEyes

IBM Signature SolutionsIBM Signature Solutions

IBM Data ExplorerIBM Data ExplorerIBM InfoSphere BigInsightsIBM InfoSphere BigInsights

Highlights

IBM Cognos InsightIBM Cognos Insight

RAVE 차트 엔진으로 빠른 통찰력 증대

IBM Rapidly Adaptive Visualization Engine

향상된 시각화

Page 8: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation8

What’s Possible

Page 9: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation9

데모 1 :

시각화 기반의 빅데이터 상관관계 분석

Page 10: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation10

2 : 예측 분석

Page 11: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation11

When confidence

is measured, managed

and visualized

Page 12: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

It can be understood

and acted upon Win 16%

Bust 21%

Win 53%

Bust 8%

Probability of

a 10 card

51%

Page 13: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation13

예측 분석

?

?

이게 만약 분석을 통해서 나온정보라면, 그 다음 해의 결과는어떻게 될까요?

�현재 우리가 주로 사용하는분석은 다음을 사람이 직접추정하게 합니다.

Page 14: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation14

예측 분석

으아~ 이렇게복잡하면, 다음은어찌될 것인가?

Page 15: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation15

What is Predictive Analytics?How is it different than business intelligence?

Sheep A – BI Dashboard

Reports showing “What happened?”

Reports showing “Why did it happen?”

Conclusion: “You walked off a cliff.”

Conclusion: “You walked too far.”

Sheep B – Predictive Analytics

Reports showing “What will happen?”

Reports showing “What should I do?”

Conclusion: “You are about to walk off a cliff.”

Conclusion: “Option F – Stop Walking is likely to produce the best result.”

Comparison

Business Intelligence Predictive Analytics

What happened? What’s next?

ForesightInsight

Scenario ModelingRoot Cause Analysis

Page 16: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation16

데모 2 :

예측 분석

Page 17: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation17

시너지 3: 소셜 미디어 분석

Page 18: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation18

Mobile and social are reshaping business

34%of smartphone users have scanned a QR

Code, 27% have read online reviews

84%of US adults who have

conducted a

transaction online or

through a mobile

device report

experiencing a

problem

50%increase in

online sales via mobile devices

over 2011

55%of smartphone users compare prices in stores

63% of online adults are

less likely to buy via

other channels if they

experienced a

problem on their

mobile phones

92%of consumers say they trust earned media, such as

word-of-mouth and recommendations

Sources: IBM, Forrester, Tealeaf and Emphathica Reports

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© 2014 IBM Corporation19

Every interaction is important

Engagement

Interacting

Awareness

Transacting

Involvement

Usage

Advocacy

Page 20: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation20

IBM Social Media Analytics

� 소셜 관련 투자가 미치는 영향도를 평가

� 소셜 미디어 상의 행태를 인식

� 고객 중 충성 고객 파악

� 관계분석을 통한 인사이트 확보• 신규 기회 또는 위험을 알려주는 주제 발견

� 지역, 인구통계학적, 추천관계, 행동학적특성을 기반으로한 세분화 및 타겟 분석

� 소셜 미디어 상에 적극적으로 개입할 수있는 기준 정보 확보

소셜 미디어 상에서 발생하는일들을손쉽게 분석 가능

클라우드(SaaS) 또는자체 구축 (on premise)

선택 가능

Page 21: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation21

IBM Social Media Analytics

Demographics

Affinity

Evolving Topics

Influencer Scoring

and Sentiment

Behavioural

AnalyticsGeographics

IBM Social IBM Social Media AnalyticsMedia Analytics

소셜데이터로 부터 실행가능한 인사이트 제공

Page 22: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf

© 2014 IBM Corporation22

데모 3 :

소셜 미디어 분석

Page 23: 스마트한 분석, 제대로 알고 접근하는 비결IBM SPSS Modeler IBM SPSS Modeler IBM Cognos Consumer InsightIBM Cognos Consumer Insight IBM ManyEyesIBM ManyEyes ... Tealeaf
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© 2014 IBM Corporation24

Legal Disclaimer

• © IBM Corporation 2014. All Rights Reserved.

• The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained

in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are

subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing

contained in this publication is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and

conditions of the applicable license agreement governing the use of IBM software.

• References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or

capabilities referenced in this presentation may change at any time at IBM’s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to

future product or feature availability in any way. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by

you will result in any specific sales, revenue growth or other results.

• If the text contains performance statistics or references to benchmarks, insert the following language; otherwise delete:

Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will

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All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs

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