Geek Sync | Data Modeling and Blockchain

Data Modeling and
Blockchain
Steve Hoberman
me@stevehoberman.com
www.SteveHoberman.com
www.TechnicsPub.com
www.DataModelingZone.com
June 21, 2017

Steve Hoberman

Game Changer Every Decade
Mainframe
1970s 1980s 1990s 2000s 2010s

PC
1970s 1980s 1990s 2000s 2010s

Web
1970s 1980s 1990s 2000s 2010s

Mobile
1970s 1980s 1990s 2000s 2010s

Blockchain
1970s 1980s 1990s 2000s 2010s

Blockchain
1.Definition
2.1.0, 2.0, 3.0
3.Challenges
4.Data Modeling Impact

A free
distributed
NoSQL
database that is
fault tolerant and
(almost) 100%
secure.
Blockchain (Developer Perspective)

Blockchain
(Modeler perspective)
Transaction
Transaction Public Key
Transaction Private Key (AK1:1)
Offering
Offering Public Key
Offering Private Key (AK1:1)
Party
Party Public Key
Party Private Key (AK1:1)
Purchase
Transaction Public Key (FK)
Offering Public Key (FK)
Be initiated by
Obtained through
Make

Blockchain
(Architect perspective)
Before

Blockchain
After
D C D C
D C
D C

Blockchain
F
F
F
F
F
F
F
F
F
F
F
F
DTC
Before (T+3)

Blockchain
F
F
F
F
F
F
F
F
F
F
F
F
After (T + 10 minutes)
D C D C
D C
D C

Blockchain
S
A
S
S
S
A
S
A
A
A
S
S
TP
Before (T+ up to 6 months)

Blockchain
S
A
S
S
S
A
S
A
A
A
S
S
After (T+ 10 minutes)
D C D C
D C
D C

By having multiple
“record keepers”,
we can trust that
the game is
played fairly,
without a central
authority.

Blockchain Levels (3 c’s)
1.0 (currency) 2.0
(contracts)
3.0 (claims)

Blockchain 1.0: Currency
• “Satoshi Nakamoto”
• Push not pull
• Micropayments
• Bitcoin has 90% of market
• What is Bitcoin, anyway?

Blockchain 2.0: Contracts
If-then statement

Blockchain 3.0: Claim
“I own this…”
“I did this…”

Top 5 Challenges
1. Performance
2. Evil
3. Government
4. Permanence
5. Usage

Blockchain on data modeling
• Stronger ties
– Data governance
– Data standards
– Data architecture
• Weaker ties
– RDBMS
• Questionable ties
– Agile
Blockchain
PDMLDMCDM
Data Model
Impact

Impact to CDM
• Industry scope
• Use cases
• Business glossary
• Architecture roadmap
Blockchain
PDMLDM
Data Model
CDM
Impact

Monopoly Conceptual
Structure
PropertyPlayer
Contain
Purchase

Impact to LDM
• Integration point (lineage)
• Greater importance to developers
• Some RDBMS artifacts disappear
• Naming standards critical
Blockchain
PDM
Data Model
CDM LDM
Impact

Player
Player Shape
Player First Name
Player Last Name
Property
Property Name
Player Shape (FK)
Property Cost
Property Color Name
Hotel
Property Name (FK)
Structure Sequence Number (FK)
House
Property Name (FK)
Structure Sequence Number (FK)
Structure
Structure Sequence Number
Property Name (FK)
Purchase
Contain
Monopoly Logical

Blockchain Data Model
CDM LDM PDM
Impact
Impact to Physical Data Modeling
• Additional metadata
– Private and public keys
– Number of recordkeepers
– % to make decisions
• Performance the main driver
– Performance vs. Availability
– Performance vs. Security
– Performance vs. Accuracy
• Same challenges as with any NoSQL DB

Monopoly Physical
Z Z
Player
Player Public ID (PK)
Player Shape (AK1:1)
Player First Name
Player Last Name
Property
Property ID (PK)
Player Public ID (FK)
Property Name (AK1:1)
Property Cost
Property Color Name
Structure
Structure Public ID (PK)
Property ID (FK) (AK1:1)
Structure Sequence Number (AK1:2)
Hotel
Structure Public ID (PK)(FK)
House
Structure Public ID (PK)(FK)
Purchase
Contain

Data Modeling and Blockchain
Steve Hoberman
www.SteveHoberman.com
www.TechnicsPub.com
www.DataModelingZone.com

Geek Sync | Data Modeling and Blockchain

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