the future of big data
TRANSCRIPT
A lot of people liked it! đ
75,000 Slideshare views.
40,000 Facebook shares and likes.
20,000 Tweets and re-tweets.
12,000 LinkedIn shares.
At an international data conference. .
Thanks for the tip of the hat (HT), but whatâs are lorries?
http://mybroadband.co.za/news/broadband/147239-this-simple-infographic-explains-how-broadband-speeds-compare.html,
In a marketing infographics. /
PBS even put it in a kids show! 0
It's Okay To Be Smart -- Is Big Data Getting Too Big? https://www.youtube.com/watch?v=NTMkc0bLRlI
Please tweet all complaints to @dwellman. - Management
Unfortunately, they all missed this, the most important part. đ
People missed it because I didnât define âvalueâ.
âš
Yep, it was my fault.
Please tweet all complaints to @dwellman. - Management
I did really bad job of defining value... đ
Please tweet all complaints to @dwellman. - Management
Dear NSA, please donât get mad at me... đł
Please tweet all complaints to @dwellman. - Management
Q: What is the value of BIG DATA?
This is a simple question,
but itâs a hard question to answer.
Hereâs an example of why...
A: âThe three defining properties or dimensions of BIG DATA are volume, variety and velocity.
Volume refers to the amount of data, variety refers to the number of types of data and velocity refers
to the speed of data processing.â
-⯠The Internet .
Q: What is the value of Big Data?
Argument For: The Internet đ´ Argument Against: David Wellman đ
Volume
The quantity of generated and stored data. The size of the data determines the value and potential insight - and whether it can actually be considered big data or not.
The volume of a dataset when viewed by one company may seem big while a different company would consider it comparatively small.
Variety
The type and nature of the data. This helps people who analyze it to effectively use the resulting insight.
Data variety in one industry may be structured while another company finds unstructured data useful.
Velocity
In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
Data velocity, whether it is fast or slow, is describing the rate of data collection, and it can be as different as collecting thousands of tweets per second compared to a single video feed.
Q: What is the value of Big Data?
Argument For: The Internet đ´ Argument Against: David Wellman đ
Volume
The quantity of generated and stored data. The size of the data determines the value and potential insight - and whether it can actually be considered big data or not.
The volume of a dataset when viewed by one company may seem big while a different company would consider it comparatively small.
Variety
The type and nature of the data. This helps people who analyze it to effectively use the resulting insight.
Data variety in one industry may be structured while another company finds unstructured data useful.
Velocity
In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
Data velocity, whether it is fast or slow, is describing the rate of data collection, and it can be as different as collecting thousands of tweets per second compared to a single video feed.
Q: What is the value of Big Data?
Argument For: The Internet đ´ Argument Against: David Wellman đ
Volume
The quantity of generated and stored data. The size of the data determines the value and potential insight - and whether it can actually be considered big data or not.
The volume of a dataset when viewed by one company may seem big while a different company would consider it comparatively small.
Variety
The type and nature of the data. This helps people who analyze it to effectively use the resulting insight.
Data variety in one industry may be structured while another company finds unstructured data useful.
Velocity
In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
Data velocity, whether it is fast or slow, is describing the rate of data collection, and it can be as different as collecting thousands of tweets per second compared to a single video feed.
Q: What is the value of Big Data?
Argument For: The Internet đ´ Argument Against: David Wellman đ
Volume
The quantity of generated and stored data. The size of the data determines the value and potential insight - and whether it can actually be considered big data or not.
The volume of a dataset when viewed by one company may seem big while a different company would consider it comparatively small.
Variety
The type and nature of the data. This helps people who analyze it to effectively use the resulting insight.
Data variety in one industry may be structured while another company finds unstructured data useful.
Velocity
In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
Data velocity, whether it is fast or slow, is describing the rate of data collection, and it can be as different as collecting thousands of tweets per second compared to a single video feed.
Q: What is the value of Big Data?
âThe metrics of volume, velocity, and variety are relative and that makes them poor measures of success.â
-⯠David Wellman
Itâs my presentation and I can quote myself if I want!
Please tweet all complaints to @dwellman. - Management
Q: What is the value of Big Data?
Our perspective shapes how we see Big Data And it shapes how we see the future of Big Data.
But, our perspective of Big Data is wrong.
Q: What is the value of Big Data?
Sinek Law
âPeople don't buy what you do; they buy why you do it. And what you do
simply proves what you believeâ -⯠â Simon Sinek
What vs. Why â The wrong questions
WHAT
HOW
WHY
âWHAT is big data?â
âHOWâ big, is BIG?
âWHYâ should I care?
What vs. Why â The wrong questions
WHAT
HOW
WHY
âWHAT is big data?â
âHOWâ big, is BIG?
âWHYâ should I care?
What vs. Why - The Right Questions
WHAT
HOW
WHY
3.⯠What does this mean to me?
2.⯠How does it change things?
1.⯠Why does Big Data matter?
Business Value Simulator Governance State
Market Mechanics (The Rules of the Game)
1.⯠Youâre selling Information. 2.⯠People buy what we believe is valuable. 3.⯠Why > What > How
Conwayâs law
âOrganizations which design systems are constrained to produce designs
which are copies of the communication structures of these organizations.â
- M. Conway
Business Value Simulator Governance State
Inn
ova
tion
Time
Point A The Starting Line
Point B The Finish Line
How we BELIEVE the world should work.
Business Value Simulator Governance State
Inn
ova
tion
Time
But, there are competing theories on the marketâs direction.
Business Value Simulator Governance State
Inn
ova
tion
Time
Some theories are more right than others.
Business Value Simulator Governance State
Inn
ova
tion
Time
Mooreâs Law sets the lower boundary for a markets performance.
Business Value Simulator Governance State
Innovators Early
Adopters
Basic Business Cycle â Adoption Curve
Early Majority
Late Majority Lagers
Business Value Simulator Governance State
Innovators
Early Adopters
Basic Business Cycle â Adoption S-Curve
Early Majority
Late Majority
Lagers
80%
100%
60%
20%
0%
% A
do
ptio
n -
Sta
te
10%
Business Value Simulator Governance State
Inn
ova
tion
Time
Normal business cycles create s-curves towards the target.
Business Value Simulator Governance State
Inn
ova
tion
Time
đŻ
Some believe this is the best the market offers.
Business Value Simulator Governance State
Inn
ova
tion
Time
over
Under
đŻ
đŻ
Amaraâs Law creates conflict between the two.
Amaraâs Law
âWe tend to overestimate the effect of technology in the short run
and underestimate the effect in the long run.â - Roy Charles Amara
Business Value Simulator Governance State
Inn
ova
tion
Time
over
Under
đŻ
đŻ
1. The Standard Way
Business Value Simulator Governance State
Inn
ova
tion
Time
over
Under
đŻ
đŻ
3. The Hard Struggle
Business Value Simulator Governance State
Inn
ova
tion
Time
over
Under
đŻ
đŻ
Achievement Earned â New Game, New Rules
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0
Training Level 1
How to win.
$0 Market Value
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0 $0
Market Value
Players
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0 $0
Market Value
Players
We want really BIG NUMBERS!
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0 $0
Market Value
Players
We want really BIG NUMBERS!
AND, reach the TOP of the MARKET!!!
đŻ đŻ
$0 Market Value
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0
Level 2
Supply Side Economics
Sarnoffâs Law
âThe value of a network is proportional to the number of viewers.â
- David Sarnoff
V(n)
A Potential Customer Sarnoffâs Law: V(n) Innovators
Producers:
Consumers:
Connections:
0 0 0
Consumer
$0 Market Value
Customer Demand Sarnoffâs Law: V(n) Innovators
Producers:
Consumers:
Connections:
0 0 0
Consumer
$0 Market Value
A Potential Producer Sarnoffâs Law: V(n) Innovators
Producers:
Consumers:
Connections:
0 0 0
Producer
$0 Market Value
Entrepreneur Sarnoffâs Law: V(n) Innovators
Producers:
Consumers:
Connections:
0 0 0
Producer
$0 Market Value
Product Market Gap Sarnoffâs Law: V(n) Innovators
Producers:
Consumers:
Connections:
0 0 0
THE SCARY âPRODUCT MARKET GAPâ!
$0 Market Value
Product Market Fit Sarnoffâs Law: V(n) Innovators
Producers:
Consumers:
Connections:
1 1 1 $1
Market Value
Excess Consumer Demand Sarnoffâs Law: V(n) Innovators
This is market potential!!!
Donât Stop!
$1 Market Value Producers:
Consumers:
Connections:
1 3 1
Market Reach Sarnoffâs Law: V(n) Early Adopters
Producers:
Consumers:
Connections:
1 3 3 $3
Market Value
Total Addressable Market Sarnoffâs Law: V(n) Early Adopters
$3 Market Value Producers:
Consumers:
Connections:
1 3 11
A small market means
small numbers...
Market Opportunity Sarnoffâs Law: V(n) Early Adopters
Producers:
Consumers:
Connections:
1 11 3 $3
Market Value
BIG NUMBERS! Opportunity: $11 Landed : $3
Missed: $8
Captured Market Sarnoffâs Law: V(n) Early Majority
$11 Market Value Producers:
Consumers:
Connections:
1 11 11
AWESOME! Now itâs time to get serious.
Monopoly Sarnoffâs Law: V(n) Late Majority
Producers:
Consumers:
Connections:
1 12 12 $12
Market Value
Demand Side Competition Sarnoffâs Law: V(n) Laggards
Producers:
Consumers:
Connections:
0 0 0 $12
Market Value Bargaining Power Of Suppliers
Bargaining Power Of Buyers
Thre
at
of
Ne
w E
ntra
nts Th
rea
t of
Ne
w Sub
stitutes
$0 Market Value
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0
Level 3
Demand Side Economics New game. New rules.
Metcalfeâs law
âThe value of a network is proportional to the square of the number of connected users of the
system.â - Robert Metcalfe
V(n2)
$0 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Connections:
1 1 1
$1 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Connections:
1 1 1
0 1
$2 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Connections:
1 1 2
0 1
2
$4 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Exchange:
1 1 2
1 0
3 2
$4 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Exchange:
1 1 2
1 0
3 2 4
$4 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Exchange:
1 1 2
V(n2)
V(22) = 4
$3 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Producers:
Consumers:
Connections:
1 3 3
0
1
2
3
$16 Market Value
Business Value Simulator Metcalfeâs law: V(n2) Innovators
Exchange: 4
V(n2)
V(42) = 16
$0 Market Value
Business Value Simulator Governance State
Producers:
Consumers:
Connections:
0 0 0
Level 4
Global Trade Economics New game. New rules.
Reedâs Law
âThe value of large networks scale exponentially with the size of the network.â
- David P. Reed
$?? Market Value
Business Value Simulator Reedâs law: V(2n) Innovators
Exchange:
Exchange: a(2) b(2)
$?? Market Value
Business Value Simulator Reedâs law: V(2n) Innovators
Exchange:
Exchange: a(2) b(2)
Business Value Simulator Governance State
Inn
ova
tion
Time
The S-Curve -> The smart Ones.
$12 Market Value
Business Value Simulator Governance State
Inn
ova
tion
Time
The S-Curve -> The SMARTER Ones.
$144 Market Value
Business Value Simulator Governance State
Inn
ova
tion
Time
The S-Curve -> The SMARTEST Ones. $4,096
Market Value
DataSize Type Network ValueLaw NetworkType
Hobbies Byte Proprietary V(n) Restricted Kilobyte SarnoffLaw
Desktop Megabyte Homogenous V(n2) SimpleSocial Gigabyte Metcalfe'sLaw
Internet Terabyte HeterogeneousV(2n) Market Petabyte Reed'sLaw &PlaDorms
BigData Exabyte Proprietary V(n) Restricted SarnoffLaw
Tomorrow Ze=abyte ??? Homogenous V(n2) Social Metcalfe'sLaw
TheFuture Yo=abyte ??? HeterogeneousV(2n) Market Reed'sLaw &PlaDorms
THE ONCE AND FUTURE PAST
Yesterday Tom
orrow
TODAY
The Future - Data
¤⯠Open Source Machine Learning
¤⯠Open Data Standards
¤⯠More Data Collected â Less Data Moving Location.
¤⯠Data Platforms â Data Brokers & Algorithm Exchange
¤⯠Network Effects around the USE OF DATA.
¤⯠More and more companies sharing RESULTS.
The Future - Management
¤⯠New management theories & styles are needed
¤⯠From command & control è community & interchange
¤⯠From internally è external,
¤⯠social and community needs come first.
The Future - Governance
¤⯠+ Crowdsourced Compliance & Open Governance
¤⯠+ âSignals of trustworthiness.â
¤⯠+ âDrain out the ego.â
¤⯠+ Trust & Safety
¤⯠- Unfettered access can destroy value
¤⯠- Un-vetted Memberships
The Future - Metrics
¤⯠Interaction Failures
¤⯠Engagement
¤⯠Match Quality
¤⯠Positive & Negative Network Effect
One Dataset, Many Analysts
A Social Research Experiment:
29 research teams from around the world where asked to answer the same question,
all using the same dataset.
The Question
Are football (soccer) referees more likely To give red cards (flags) to players with dark skin
Than to players with light skin?
CASE STUDY â THE RESULTS
âThe experiment convinced us that
bringing together many teams of skilled researchers can balance discussions, validate scientific findings
and better inform policymakers.â
http://www.nature.com/news/crowdsourced-research-many-hands-make-tight-work-1.18508
BE SMART
Inn
ova
tion
Time
HOW How do we use it?
What What is big data?
Why Why do we care?
WHAT HOW WHY
over
Under