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 Data Vault Modeling

 DW2.0 & Unstructured Data

 Big Data

 Ensemble Modeling

 Agile DW

Agile BI with the Data Vault DW
Knowledge is Power.
© 2013 Genesee Academy, LLC
USA +1 303 526 0340
Sweden 072 736 8700
Hans@GeneseeAcademy.com
www.GeneseeAcademy.com

gohansgo

Hans Hultgren
Agile BI with the Data Vault DW
How is it that Data Vault supports Agile BI so well?
What about the other new approaches?
In this session we break down the characteristics of the data modeling approaches that support
data warehouse agility.
Using a Modeling Pattern Characteristics analysis, Hans will in this session compare leading
Ensemble modeling methods and their unique capabilities for supporting features of your EDW
program.
These include Data Vault, Anchor Modeling, Focal Point, and Hyper Agility modeling. What are
the strengths and what are the weaknesses for each approach?
How are they deployed and what do each mean for our overall DWBI architecture?

Topics covered in this session also include Unified Decomposition, the definition and
purpose of Raw versus BDW layers, the role of the Information Model related to our EDW,
and a discussion on where and how to apply automation tooling and techniques.

© 2013 Genesee Academy, LLC

2
Agile BI with the Data Vault DW
Knowledge is Power. | Premise #1
• You won’t achieve agility with a modeling pattern alone.
• You won’t achieve agility without a modeling pattern that
supports it.

© 2013 Genesee Academy, LLC

3
Agile BI with the Data Vault DW
• A Saga of Data Warehousing:
Once upon a time data warehousing was becoming more popular and
everyone was eager to build their own. But whenever they tried they failed.
They called upon their best to fix this but they just couldn’t solve the
problem.
They discovered that meeting the needs of the data warehouse meant that
the tables got too big and too hard to work with. They just could not handle
changes over time. If the smallest thing changed it always meant they had
to change the entire table. When just a single attribute was updated they
had to insert a record for all of the attributes. All seemed lost.
But around the world there were rebels who questioned the conventional
wisdom. And their voices were finally heard: Why not separate the things
that change from the things that don’t change?
© 2013 Genesee Academy, LLC

4
Modeling Pattern Awareness
• Separating the things that change from the things that don’t change.
• break things out into component parts for flexibility and to capture
things that
– are interpreted in different ways or
– changing independently of each other

– Unified Decomposition™
© 2013 Genesee Academy, LLC

5
Ensemble Modeling™
• The constellation of component parts acts as a whole – an Ensemble.
All the parts of a thing taken together, so that
each part is considered only in relation to the whole.

• With Ensemble Modeling the Core Business Concepts that we define
and model are represented as a whole – an ensemble – including all of
the component parts.
© 2013 Genesee Academy, LLC

6
What Forms are there?
Data
Mart

ERP
EDW

Acctg

Data
Mart

Sales

3NF

Anchor

Ensemble

Focal Point

Data Vault

2G

Data
Mart

Dimensional

Temporal, 6NF,
Hyper Agillity

+

Matter, DV2.0

+

© 2013 Genesee Academy, LLC

7
The Data Vault Ensemble
• The Data Vault Ensemble conforms to a single key – embodied in the Hub
construct.

• The component parts for the Data Vault Ensemble include:
– Hub
The Natural Business Key
– Link
The Natural Business Relationships
– Satellite
All Context, Descriptive Data and History
© 2013 Genesee Academy, LLC

8
Comparing the Big 3 Modeling Forms

•
•
•
•

Both 3NF and Dimensional use highly encapsulated concepts.
All forms are Attributed and stay rather close to the Business Concept.
3NF can sometimes move towards Abstracted Concepts.
None of these forms are focused on Fully Abstracted or Generic Context methods.

© 2013 Genesee Academy, LLC
Data Vault means thinking differently
Customer

Customer

© 2013 Genesee Academy, LLC

10
Agile BI with the Data Vault DW
Knowledge is Power. | Premise #2
• Modeling Awareness (understanding the pattern you are applying) is the
key to successful modeling.
• Not knowing when you are applying a modeling exception is
dangerous.

© 2013 Genesee Academy, LLC

11
Applying the Data Vault Ensemble
• Mixing “color types of data” is not Data Vaulting but rather unvaulting
• A blended pattern has different dynamics…

?
Thinking Differently

!

© 2013 Genesee Academy, LLC

12
Applying the Data Vault Ensemble
• Stay with the Ensemble Modeling Pattern. Continue practicing Unified
Decomposition. Continue Vaulting. Be aware when you change patterns.
Option 1

Option 2

or

© 2013 Genesee Academy, LLC

13
Agile BI with the Data Vault DW
Knowledge is Power. | Premise #3
• Identify your own specific Modeling Pattern (including hybrid or
blended patterns) to meet the needs of your EDW.
• Document your pattern and apply it consistently to gain the full
benefits (including agility, repeatability and automation).

© 2013 Genesee Academy, LLC

14
Sample: Sales Data Vault Model

© 2013 Genesee Academy, LLC

15
Agile BI with the Data Vault DW
Knowledge is Power. | Premise #4
• There is no Integration without Semantic Integration.
• Integrating Data without understanding the meaning of that data
is meaningless.

© 2013 Genesee Academy, LLC

16
Agile BI with the Data Vault DW
Information Modeling
• Logical Models, Conceptual Models, Industry Models, Semantic Models,
Taxonomies and Ontologies are all forms of Information Modeling.
• These seek to target the central meaning of the core business concepts
we work with and also how they relate to each other.
• These should be consistent with the concepts coming from your BICC,
SOA, MDM, MDD, GCI, and other organizational information modeling,
data governance or business glossary initiatives.

Information Model

© 2013 Genesee Academy, LLC

17
Staging

© 2013 Genesee Academy, LLC
Load

Transform

Calculate
Convert

Cleanse

Profile
Validate

Extract

Raw

Transform

Calculate
Convert

Cleanse

Profile
Validate

Integrate

Load

D/T Stamp

Integrate

Extract

Architecture: Raw and BDV

Information Model

BDW
Data
Mart

Data
Mart
Data
Mart

EDW
18
Agile BI with the Data Vault DW
Knowledge is Power. | Premise #5
• Automation must address the Central Meaning of our data in
order for it to be useful.
• Automating the modeling and loading of a source system can
never result in multi-source data integration.

© 2013 Genesee Academy, LLC

19
Automation Matrix
Consider and
compare the full
set of capabilities
for your
automation
solutions.
Process for modeling/deploying DV EDW
• Business Driven Modeling. Since an EDW integrates data from several sources,
departments, divisions, functions, and countries over time, the integration
target needs to be based on the organizations central view and not on a
handful of source systems that happen to be in scope at the time.

t + 10 yrs

Now / Today

t - 10 yrs

© 2013 Genesee Academy, LLC

Information
Model

EDW
The Enterprise Data Warehouse

Information Model

Data

© 2013 Genesee Academy, LLC

Stage

Data
Warehouse

Marts

Info
Recap
• Agile modeling for the DW comes from Unified Decomposition
• Data Vault modeling leads the Ensemble Modeling family
• Knowledge is Power:
•
•
•
•
•

Agility is more than modeling | Modeling must support it
Know your modeling pattern | Know your architecture
Customize your pattern, but | Apply it consistently
Integration requires meaning | Create an Information Model
Understand what you automate | Automate beyond sources

© 2013 Genesee Academy, LLC

23
About Data Vault Ensemble

Estimated 800 Data Vault based
Data Warehouses around the world

© 2013 Genesee Academy, LLC

24
Links and Information
CDVDM Training & Certification
www.GeneseeAcademy.com
Hans@GeneseeAcademy.com

gohansgo

Book DataVaultBook.blogspot.com
HansHultgren.WordPress.com
HansHultgren
DataVaultAcademy

Online video-lesson training

DataVaultAcademy.com
© 2013 Genesee Academy, LLC

25

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Data Vault Agility Bi Podium November 2013

  • 1.  Data Vault Modeling  DW2.0 & Unstructured Data  Big Data  Ensemble Modeling  Agile DW Agile BI with the Data Vault DW Knowledge is Power. © 2013 Genesee Academy, LLC USA +1 303 526 0340 Sweden 072 736 8700 Hans@GeneseeAcademy.com www.GeneseeAcademy.com gohansgo Hans Hultgren
  • 2. Agile BI with the Data Vault DW How is it that Data Vault supports Agile BI so well? What about the other new approaches? In this session we break down the characteristics of the data modeling approaches that support data warehouse agility. Using a Modeling Pattern Characteristics analysis, Hans will in this session compare leading Ensemble modeling methods and their unique capabilities for supporting features of your EDW program. These include Data Vault, Anchor Modeling, Focal Point, and Hyper Agility modeling. What are the strengths and what are the weaknesses for each approach? How are they deployed and what do each mean for our overall DWBI architecture? Topics covered in this session also include Unified Decomposition, the definition and purpose of Raw versus BDW layers, the role of the Information Model related to our EDW, and a discussion on where and how to apply automation tooling and techniques. © 2013 Genesee Academy, LLC 2
  • 3. Agile BI with the Data Vault DW Knowledge is Power. | Premise #1 • You won’t achieve agility with a modeling pattern alone. • You won’t achieve agility without a modeling pattern that supports it. © 2013 Genesee Academy, LLC 3
  • 4. Agile BI with the Data Vault DW • A Saga of Data Warehousing: Once upon a time data warehousing was becoming more popular and everyone was eager to build their own. But whenever they tried they failed. They called upon their best to fix this but they just couldn’t solve the problem. They discovered that meeting the needs of the data warehouse meant that the tables got too big and too hard to work with. They just could not handle changes over time. If the smallest thing changed it always meant they had to change the entire table. When just a single attribute was updated they had to insert a record for all of the attributes. All seemed lost. But around the world there were rebels who questioned the conventional wisdom. And their voices were finally heard: Why not separate the things that change from the things that don’t change? © 2013 Genesee Academy, LLC 4
  • 5. Modeling Pattern Awareness • Separating the things that change from the things that don’t change. • break things out into component parts for flexibility and to capture things that – are interpreted in different ways or – changing independently of each other – Unified Decomposition™ © 2013 Genesee Academy, LLC 5
  • 6. Ensemble Modeling™ • The constellation of component parts acts as a whole – an Ensemble. All the parts of a thing taken together, so that each part is considered only in relation to the whole. • With Ensemble Modeling the Core Business Concepts that we define and model are represented as a whole – an ensemble – including all of the component parts. © 2013 Genesee Academy, LLC 6
  • 7. What Forms are there? Data Mart ERP EDW Acctg Data Mart Sales 3NF Anchor Ensemble Focal Point Data Vault 2G Data Mart Dimensional Temporal, 6NF, Hyper Agillity + Matter, DV2.0 + © 2013 Genesee Academy, LLC 7
  • 8. The Data Vault Ensemble • The Data Vault Ensemble conforms to a single key – embodied in the Hub construct. • The component parts for the Data Vault Ensemble include: – Hub The Natural Business Key – Link The Natural Business Relationships – Satellite All Context, Descriptive Data and History © 2013 Genesee Academy, LLC 8
  • 9. Comparing the Big 3 Modeling Forms • • • • Both 3NF and Dimensional use highly encapsulated concepts. All forms are Attributed and stay rather close to the Business Concept. 3NF can sometimes move towards Abstracted Concepts. None of these forms are focused on Fully Abstracted or Generic Context methods. © 2013 Genesee Academy, LLC
  • 10. Data Vault means thinking differently Customer Customer © 2013 Genesee Academy, LLC 10
  • 11. Agile BI with the Data Vault DW Knowledge is Power. | Premise #2 • Modeling Awareness (understanding the pattern you are applying) is the key to successful modeling. • Not knowing when you are applying a modeling exception is dangerous. © 2013 Genesee Academy, LLC 11
  • 12. Applying the Data Vault Ensemble • Mixing “color types of data” is not Data Vaulting but rather unvaulting • A blended pattern has different dynamics… ? Thinking Differently ! © 2013 Genesee Academy, LLC 12
  • 13. Applying the Data Vault Ensemble • Stay with the Ensemble Modeling Pattern. Continue practicing Unified Decomposition. Continue Vaulting. Be aware when you change patterns. Option 1 Option 2 or © 2013 Genesee Academy, LLC 13
  • 14. Agile BI with the Data Vault DW Knowledge is Power. | Premise #3 • Identify your own specific Modeling Pattern (including hybrid or blended patterns) to meet the needs of your EDW. • Document your pattern and apply it consistently to gain the full benefits (including agility, repeatability and automation). © 2013 Genesee Academy, LLC 14
  • 15. Sample: Sales Data Vault Model © 2013 Genesee Academy, LLC 15
  • 16. Agile BI with the Data Vault DW Knowledge is Power. | Premise #4 • There is no Integration without Semantic Integration. • Integrating Data without understanding the meaning of that data is meaningless. © 2013 Genesee Academy, LLC 16
  • 17. Agile BI with the Data Vault DW Information Modeling • Logical Models, Conceptual Models, Industry Models, Semantic Models, Taxonomies and Ontologies are all forms of Information Modeling. • These seek to target the central meaning of the core business concepts we work with and also how they relate to each other. • These should be consistent with the concepts coming from your BICC, SOA, MDM, MDD, GCI, and other organizational information modeling, data governance or business glossary initiatives. Information Model © 2013 Genesee Academy, LLC 17
  • 18. Staging © 2013 Genesee Academy, LLC Load Transform Calculate Convert Cleanse Profile Validate Extract Raw Transform Calculate Convert Cleanse Profile Validate Integrate Load D/T Stamp Integrate Extract Architecture: Raw and BDV Information Model BDW Data Mart Data Mart Data Mart EDW 18
  • 19. Agile BI with the Data Vault DW Knowledge is Power. | Premise #5 • Automation must address the Central Meaning of our data in order for it to be useful. • Automating the modeling and loading of a source system can never result in multi-source data integration. © 2013 Genesee Academy, LLC 19
  • 20. Automation Matrix Consider and compare the full set of capabilities for your automation solutions.
  • 21. Process for modeling/deploying DV EDW • Business Driven Modeling. Since an EDW integrates data from several sources, departments, divisions, functions, and countries over time, the integration target needs to be based on the organizations central view and not on a handful of source systems that happen to be in scope at the time. t + 10 yrs Now / Today t - 10 yrs © 2013 Genesee Academy, LLC Information Model EDW
  • 22. The Enterprise Data Warehouse Information Model Data © 2013 Genesee Academy, LLC Stage Data Warehouse Marts Info
  • 23. Recap • Agile modeling for the DW comes from Unified Decomposition • Data Vault modeling leads the Ensemble Modeling family • Knowledge is Power: • • • • • Agility is more than modeling | Modeling must support it Know your modeling pattern | Know your architecture Customize your pattern, but | Apply it consistently Integration requires meaning | Create an Information Model Understand what you automate | Automate beyond sources © 2013 Genesee Academy, LLC 23
  • 24. About Data Vault Ensemble Estimated 800 Data Vault based Data Warehouses around the world © 2013 Genesee Academy, LLC 24
  • 25. Links and Information CDVDM Training & Certification www.GeneseeAcademy.com Hans@GeneseeAcademy.com gohansgo Book DataVaultBook.blogspot.com HansHultgren.WordPress.com HansHultgren DataVaultAcademy Online video-lesson training DataVaultAcademy.com © 2013 Genesee Academy, LLC 25