business unintelligence - a whistle stop tour

Copyright © 2013 9sight Consulting, All Rights Reserved

Dr Barry Devlin

Founder & Principal9sight Consulting

Business Intelligence:Beyond Analytics and Big Data

A whistle-stop tour

BrightTALK Webinar

11 September 2013

Dr. Barry Devlin

2 Copyright © 2013, 9sight ConsultingCopyright © 2013, 9sight Consulting

Founder and Principal9sight Consulting, www.9sight.com

Dr. Barry Devlin is a founder of the data warehousing industry andamong the foremost authorities worldwide on business intelligence(BI) and beyond. He is a widely respected consultant, lecturer andauthor of the seminal “Data Warehouse—from Architecture toImplementation”. His new book, “Business unIntelligence—Insightand Innovation Beyond Analytics and Big Data” (http://bit.ly/BunI-Technics) is published in October 2013.

Barry has 30 years of experience in the IT industry, previously withIBM, as an architect, consultant, manager and software evangelist.

As founder and principal of 9sight Consulting (www.9sight.com),Barry provides strategic consulting and thought-leadership tobuyers and vendors of BI solutions. He is currently developing newarchitectural models for fully consistent business support—frominformational to operational and collaborative work.

Based in Cape Town, South Africa, Barry’s knowledge andexpertise are in demand both locally and internationally.

Email: [email protected]: @BarryDevlin

A fair(l)y Big Data Tale

Wal-Mart Data Warehouse– 1991 … 340GB; 2004 … 460TB– 2008 … 2.5PB; 2013 … 10+PB

– Big data is not new

From the beginning, more thanbusiness intelligence– Operational BI– Supply chain management– Predictive analytics

12% of US productivity gains in thesecond half of the 1990s due toWal-Mart

– McKinsey Report


Introducing the biz-tech ecosystem

1. Reintegration:– Of the technology and the

organizations across entire business

2. Interdependence:– A classic positive feedback loop

between IT and business

3. Cross-over:– Of IT and business skills

4. Cooperation:– Free flow of information; joint

processes between businesses

5. Trust:– Hyper-competition or ???


http://ideasmanv2.wordpress.com/2007/04/15/a-mystical-yin-yang/

Business and IT – Beauty and the BeastA new beginning

Traditional out-sourcing isno longer an option

Simpler / cheaperdeployment (e.g. AmazonRedShift) for basicfunctionality allows IT tofocus on business valueand innovation


Designing the biz-tech ecosystem:The IDEAL conceptual architecture

Foundation forBusiness – IT cooperation

Characteristics– Integrated– Distributed– Emergent– Adaptive– Latent

Also…– Complete, Elegantly simple,

Enterprise-wide, Open system


Information

Process

People

m3: The modern meaning model

Ackoff’s DIKW pyramidis no longer viable

Information precedes data– Data is simply information

optimized for computers– The Web has fully devalued

“facts”

– People process information


Locu

s

Structure

Ph

ysic

al

Loose

Men

tal

Strict

Inte

rper

son

al

HardInformation

SoftInformation

ExplicitKnowledge

TacitKnowledge

MeaningThe stories we tell ourselves

Ob

ject

ive

/u

niv

ersa

lSu

bje

ctiv

e /

un

iqu

e

Sen

se-

mak

ing

Men

tori

ng

Understanding Insight

Data Content

Articulation

Practice

Vid

eoin

g

Ob

serving

Modeling

Interpreting

The tri-domain information model

Process-mediated data– “Traditional” operational

& informational data– Via data entry and

cleansing processes

Machine-generated data– Output of machines

and sensors– The Internet of Things

Human-sourced information– Subjectively interpreted

record of personalexperiences

– From Tweets to Videos


Human-sourced information

Machine-generated

data

Process-mediated data

Structure/Context

Timeliness/Consistency

HistoricalReconciledStableLiveIn-flight

[In the context of these domains, “data” signifies well-structured and/ormodeled and “information” is more loosely structured and human-centric.]

Decision making is a process, too

Extreme timeliness / high uncertainty– Sense and respond as the basis

for an adaptive enterprise– Stephan Haeckel

MEDA model– Closing the loop between

action and monitoring– Adaptive workflow

Adaptive decision cycle– Center-out model (traditional BI)– Edge-on model (spreadsheets)– Promote individual insights to

team and enterprise levels


Act Decide

EvaluateMonitor

Garner

Condition

Utilize

Iterate Innovate

The REAL logical architecture Realistic, Extensible,

Actionable, Labile

Build the biz-tech ecosystem

Three interconnected pillarsof information– Messages, events, measures and

transactions from real world– Metadata is context-setting

information

Adaptive process– Business and IT– Information processing

– Instantiation, assimilation andreification – ETL, ELT, Virtualization

– Workflows and activities– Choreography


EventsMeasures Messages

Transactions

Reification

Utilization

Ch

ore

ogr

aph

y

Org

aniz

atio

n

Instantiation

Human-sourced

(information)

Machine-generated

(data)

Process-mediated

(data)

Context-setting (information)

Assimilation

Transactional(data)

The human and social dimension:Gut-feel, intent and interaction

Meaning is a personal/ social interpretationbased (loosely) on information and knowledge– Rationality is only one part– Emotional state plays an important role– Gut-feel can be more effective than rationality

in decision making

Intention drives understandingand action

We are social animals– Business is a social enterprise

Innovation is often team-based


Innovative and insightful decision making:The iSight model

Formalizing the person/team environment– True Enterprise 2.0 and Collaboration– Adaptive process

Informal information is key– Capturing and storing personal interactions


• Strategy• Plan• Process Change• Specific Action• Etc.

Investigate

InteractInteract

Person

Intuit

Intend

Integrate

Interpret

InnovateInnovate

Team

Improvise

Imagine

ImplementInformation

(External,Formal)

Overt Hidden

Team Information(Formal & Informal)

From BI to Business unIntelligence

Rationality of thought and far beyond it

Logic of process, predefined and emergent

Information, knowledge and meaning

The confluence of– Reason and inspiration– Emotion and intention– Collaboration and competition– All that comprises the human and

social milieu that is business

Not business intelligence

Business unIntelligence

http://bit.ly/BunI-Technics : 25% discount with code “BIInsights25”


Conclusions Big data, speed, uncertainty, etc. demand

adaptive approaches to decision making– The biz-tech ecosystem

Information rather than data is key– Understanding structure and meaning

Decisions are human and social processes– Beyond rational and highly interactive

New architectures for all IT emerge fromreinventing business intelligence– Consider ethical and social implications, too


Additional resources

All my articles and white papers are available at:http://bit.ly/9sight_papers

See my blogs at: http://bit.ly/BD_Blog

Follow me on Twitter: @BarryDevlin


business unintelligence - a whistle stop tour

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