SlideShare a Scribd company logo
1 of 19
Anchor Modeling
A Technique for Information under Evolution
      Lars Rönnbäck @ GSE Nordics June 7–9, 2011
INFORMATION   MONEY   LOVE




                                     Google ngram viewer

Graph showing relative occurrence of words
in literature over the last century

Information is rapidly becoming the most
important asset
c litus
Hera      C
  5 00.B
               “Panta rhei”
               Everything
                  flows
Evolving
        Information
Changing content

Changing structure

Changing constraints

Changing interpretation   There's a big difference
                           between saying: "This
Changing origins          information has a 95%
                            reliability" and "This
Changing reliability         information is 100%
                                  reliable".
What is a database?
The purpose of a database is to store a body
of information and allow searches over it.

The purpose of a temporal database is to
store a body of information under evolution
and allow historical searches over it.

                                                  t
                                           a re no
                                      , we
                                   But e yet!
                                      ther
What is a
  Data Warehouse?
Integrates information from many sources

Keeps a history of changes

Provides “one version of the truth”

Enables reporting, ad-hoc analysis, mining

Calculates and stores new information
The dilemma
Many sources and
many users naturally
                                                lack of
result in many




                               tim ion
                                               adherence




                           er at
changes




                                  e
                         ov rad
                             g
                       de
                                         25%


                                               55%

Dimensional Modeling                     20%
Normalized
Haphazard               lack of
                       adherence
Patch or Redo?
Patching works initially to cope with new
requirements

Maintenance costs usually rise proportionally
to the lifetime of the data warehouse

Redoing is unavoidable at some point
(and for dimensional modeling sometimes accounted for)


The average lifetime is five years

The return of investment should and could
be much better with a longer lifetime!
What is
 Anchor Modeling?
Anchor Modeling combines normalization and
emulation to provide an agile database
modeling technique for evolving information
that is implementable in current relational
databases.

Most, if not all, of what Anchor Modeling is
doing in its physical (relational)
representation could be "hidden" from the
end-user in a true temporal database.
Technologies

       Entity-Relationship
one-   Modeling
 to-
one

       Sixth Normal Form
       Tables


       Temporal Database
       Emulation
History
                                                                     Best Paper Award
                                                                         @ ER’09


                                            Maria     Petia
                 Lars        Olle
    Paul                                  Bergholtz   Wohed        research
               Rönnbäck    Regardt
Johannesson


                                                                         DW
              consulting
                                                        SU  DW      DKE GSE
     DW        MDM        EDW    DW          TDWI      WWW ER09    TOOL AMW



     03         04        05         06         07      08    09     10       11
Philosophy
Make modeling free from assumptions

Make modeling agile and iterative

Make evolution non-destructive

Do not duplicate information

Do not alter existing information

Decouple metadata from the model

Provide a simple interface for queries
Evolutio
Changing content                              Anchor M
                                                         n in
full support [6NF + time of change]                    odeling


Changing structure
full support (through extensions) [non-destructive schema evolution]


Changing constraints
minimal support [only primary and foreign keys]


Changing interpretation
achievable [explicitly modeled]


Changing origins
restricted support [using metadata]


Changing reliability
restricted support [using metadata]
ionin
              g
  Posit odeling
                                Domain
    chor
          M                      driven
 An                             modeling



Data Vault/ODS/3NF (Inmon)        mimics           Anchor Modeling
                                  reality




                      mimics                   mimics           Use-
 Data               structure                 searches           case
 driven                                                        driven
 modeling                                                    modeling
                        Dimensional Modeling (Kimball)
Basic Notions
 Attributes – properties
  Example: The surname of a Person
 <#42, ‘Rönnbäck’, 2004-06-19>                      Anchors – entities
                                                    Example: A Person
                               <#42> (holds only identities of entities)


                                                   
                    



              


                             



Knots – shared properties
    Example: The gender of a Person
                                                  Ties – relationships
        <#1, ‘Male’> + <#42, #1>                  Example: The children of a Person
                                                  <#42, #4711>
Historization
<#42, ‘Samuelsson’, 1972-08-20>         closed interval
                                      historical information
<#42, ‘Rönnbäck’,       2004-06-19>
                                        open interval
                                      current information



  Historization is done using
   the time of change as the
 start of an interval implicitly
 closed by another instance of        Note tha
                                               t UPDAT
 the same identity with a later       never al
                                               lowed in
                                                        E is
        time of change.                anchor
                                                databas
                                                        an
                                                        e
The Modeling Tool
                     www.anchormodeling.com/modeler
Open Source

Online (HTML5)

Free to use

In the Cloud
                                             EM O!
XML Interchange Format                     D

Automatic generation of SQL scripts

Interactive (force-directed) Layout Engine
Important Benefits
Handles evolving information       (keeping the integrity intact)

Increases longevity   (databases with long life expectancy)

Simplifies modeling concepts        (less prone to error)

Enables modular and iterative development
Needs no translation logic to the physical layer
Automates generation of scripts
No downtime when upgrading databases
Scans only relevant data during searches
Sparse data cause no gaps       (no null values)
More Information
                          :                   Twitter: anchormod
               Homepage                  m                      eling
                          ode  ling.co
             w. anchorm
ht tp://ww
                             od eling Tool
               Tutorials . M
 B log . Video

                                                   deling.com
                  E -mail: lars.r onnback@anchormo



                           LinkedIn Groups:
                          Anchor Modeling
                      Temporal Data Modeling
                           Temporal Data

More Related Content

Viewers also liked

D O M E S T I C V I O L E N C E A G A I N S T W O M E N [1]
D O M E S T I C  V I O L E N C E  A G A I N S T  W O M E N [1]D O M E S T I C  V I O L E N C E  A G A I N S T  W O M E N [1]
D O M E S T I C V I O L E N C E A G A I N S T W O M E N [1]DYUTI
 
中國最黑的風景名勝
中國最黑的風景名勝中國最黑的風景名勝
中國最黑的風景名勝ykyr7850
 
Рынок промышленных котлов ( производство/импорт/экспорт )
Рынок промышленных котлов (производство/импорт/экспорт)Рынок промышленных котлов (производство/импорт/экспорт)
Рынок промышленных котлов ( производство/импорт/экспорт )Agency of Industrial Marketing
 
Assignment 2 are you paying attention
Assignment 2   are you paying attentionAssignment 2   are you paying attention
Assignment 2 are you paying attentionAbhishek Shirali
 
Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...
Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...
Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...Verimatrix
 
Мониторинг рынка частотных преобразователей 2014, demo
Мониторинг рынка частотных преобразователей 2014, demoМониторинг рынка частотных преобразователей 2014, demo
Мониторинг рынка частотных преобразователей 2014, demoAgency of Industrial Marketing
 
Мониторинг украинского рынка гибкой черепицы
Мониторинг украинского рынка гибкой черепицыМониторинг украинского рынка гибкой черепицы
Мониторинг украинского рынка гибкой черепицыAgency of Industrial Marketing
 
Green Consultants- brief profile
Green Consultants- brief profileGreen Consultants- brief profile
Green Consultants- brief profileGunjan Bagaria
 
N.e.m.o. albert serrat
N.e.m.o. albert serratN.e.m.o. albert serrat
N.e.m.o. albert serratemallol1
 
Brandraising Jewishly
Brandraising JewishlyBrandraising Jewishly
Brandraising JewishlySarah Durham
 

Viewers also liked (19)

D O M E S T I C V I O L E N C E A G A I N S T W O M E N [1]
D O M E S T I C  V I O L E N C E  A G A I N S T  W O M E N [1]D O M E S T I C  V I O L E N C E  A G A I N S T  W O M E N [1]
D O M E S T I C V I O L E N C E A G A I N S T W O M E N [1]
 
led-holodnyh-kontaktov
led-holodnyh-kontaktovled-holodnyh-kontaktov
led-holodnyh-kontaktov
 
中國最黑的風景名勝
中國最黑的風景名勝中國最黑的風景名勝
中國最黑的風景名勝
 
Couchdb w Ruby'm
Couchdb w Ruby'mCouchdb w Ruby'm
Couchdb w Ruby'm
 
Рынок промышленных котлов ( производство/импорт/экспорт )
Рынок промышленных котлов (производство/импорт/экспорт)Рынок промышленных котлов (производство/импорт/экспорт)
Рынок промышленных котлов ( производство/импорт/экспорт )
 
Assignment 2 are you paying attention
Assignment 2   are you paying attentionAssignment 2   are you paying attention
Assignment 2 are you paying attention
 
ETE Award Ceremony 2009 (Chinese)
ETE Award Ceremony 2009 (Chinese)ETE Award Ceremony 2009 (Chinese)
ETE Award Ceremony 2009 (Chinese)
 
Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...
Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...
Multi-network Solutions in the Real World: NAB 2012, Bill Rosenblatt, GiantSt...
 
Verb To Be
Verb To BeVerb To Be
Verb To Be
 
Methode GoldenBox
Methode GoldenBoxMethode GoldenBox
Methode GoldenBox
 
Мониторинг рынка частотных преобразователей 2014, demo
Мониторинг рынка частотных преобразователей 2014, demoМониторинг рынка частотных преобразователей 2014, demo
Мониторинг рынка частотных преобразователей 2014, demo
 
Chapter1
Chapter1Chapter1
Chapter1
 
Little Bear Book
Little  Bear  BookLittle  Bear  Book
Little Bear Book
 
Мониторинг украинского рынка гибкой черепицы
Мониторинг украинского рынка гибкой черепицыМониторинг украинского рынка гибкой черепицы
Мониторинг украинского рынка гибкой черепицы
 
Green Consultants- brief profile
Green Consultants- brief profileGreen Consultants- brief profile
Green Consultants- brief profile
 
N.e.m.o. albert serrat
N.e.m.o. albert serratN.e.m.o. albert serrat
N.e.m.o. albert serrat
 
中文发现在澳科大实用性分析
中文发现在澳科大实用性分析中文发现在澳科大实用性分析
中文发现在澳科大实用性分析
 
Energia
EnergiaEnergia
Energia
 
Brandraising Jewishly
Brandraising JewishlyBrandraising Jewishly
Brandraising Jewishly
 

Similar to Anchor Modeling GSE11 Presentation

Scientific data management from the lab to the web
Scientific data management   from the lab to the webScientific data management   from the lab to the web
Scientific data management from the lab to the webJose Manuel Gómez-Pérez
 
The return of big iron?
The return of big iron?The return of big iron?
The return of big iron?Ben Stopford
 
Vital AI: Big Data Modeling
Vital AI: Big Data ModelingVital AI: Big Data Modeling
Vital AI: Big Data ModelingVital.AI
 
ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides DuraSpace
 
Domain oriented development
Domain oriented developmentDomain oriented development
Domain oriented developmentrajmundr
 
Research Objects: more than the sum of the parts
Research Objects: more than the sum of the partsResearch Objects: more than the sum of the parts
Research Objects: more than the sum of the partsCarole Goble
 
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and SparkVital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and SparkVital.AI
 
Cloud Programming Models: eScience, Big Data, etc.
Cloud Programming Models: eScience, Big Data, etc.Cloud Programming Models: eScience, Big Data, etc.
Cloud Programming Models: eScience, Big Data, etc.Alexandru Iosup
 
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera, Inc.
 
Reinventing Laboratory Data To Be Bigger, Smarter & Faster
Reinventing Laboratory Data To Be Bigger, Smarter & FasterReinventing Laboratory Data To Be Bigger, Smarter & Faster
Reinventing Laboratory Data To Be Bigger, Smarter & FasterOSTHUS
 
Silicon valley nosql meetup april 2012
Silicon valley nosql meetup  april 2012Silicon valley nosql meetup  april 2012
Silicon valley nosql meetup april 2012InfiniteGraph
 
The Research Object Initiative: Frameworks and Use Cases
The Research Object Initiative:Frameworks and Use CasesThe Research Object Initiative:Frameworks and Use Cases
The Research Object Initiative: Frameworks and Use CasesCarole Goble
 
Text and Data Visualization Introduction 2012
Text and Data Visualization Introduction 2012Text and Data Visualization Introduction 2012
Text and Data Visualization Introduction 2012Treparel
 
Spring Data Neo4j Intro SpringOne 2011
Spring Data Neo4j Intro SpringOne 2011Spring Data Neo4j Intro SpringOne 2011
Spring Data Neo4j Intro SpringOne 2011jexp
 
NO SQL: What, Why, How
NO SQL: What, Why, HowNO SQL: What, Why, How
NO SQL: What, Why, HowIgor Moochnick
 
The Symbiotic Nature of Provenance and Workflow
The Symbiotic Nature of Provenance and WorkflowThe Symbiotic Nature of Provenance and Workflow
The Symbiotic Nature of Provenance and WorkflowEric Stephan
 
AI Beyond Deep Learning
AI Beyond Deep LearningAI Beyond Deep Learning
AI Beyond Deep LearningAndre Freitas
 

Similar to Anchor Modeling GSE11 Presentation (20)

Scientific data management from the lab to the web
Scientific data management   from the lab to the webScientific data management   from the lab to the web
Scientific data management from the lab to the web
 
The return of big iron?
The return of big iron?The return of big iron?
The return of big iron?
 
Vital AI: Big Data Modeling
Vital AI: Big Data ModelingVital AI: Big Data Modeling
Vital AI: Big Data Modeling
 
Anchor modeling
Anchor modelingAnchor modeling
Anchor modeling
 
ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides
 
Domain oriented development
Domain oriented developmentDomain oriented development
Domain oriented development
 
Research Objects: more than the sum of the parts
Research Objects: more than the sum of the partsResearch Objects: more than the sum of the parts
Research Objects: more than the sum of the parts
 
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and SparkVital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
 
Cloud Programming Models: eScience, Big Data, etc.
Cloud Programming Models: eScience, Big Data, etc.Cloud Programming Models: eScience, Big Data, etc.
Cloud Programming Models: eScience, Big Data, etc.
 
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
 
Reinventing Laboratory Data To Be Bigger, Smarter & Faster
Reinventing Laboratory Data To Be Bigger, Smarter & FasterReinventing Laboratory Data To Be Bigger, Smarter & Faster
Reinventing Laboratory Data To Be Bigger, Smarter & Faster
 
Silicon valley nosql meetup april 2012
Silicon valley nosql meetup  april 2012Silicon valley nosql meetup  april 2012
Silicon valley nosql meetup april 2012
 
The Research Object Initiative: Frameworks and Use Cases
The Research Object Initiative:Frameworks and Use CasesThe Research Object Initiative:Frameworks and Use Cases
The Research Object Initiative: Frameworks and Use Cases
 
Text and Data Visualization Introduction 2012
Text and Data Visualization Introduction 2012Text and Data Visualization Introduction 2012
Text and Data Visualization Introduction 2012
 
Role of Semantic Web in Health Informatics
Role of Semantic Web in Health InformaticsRole of Semantic Web in Health Informatics
Role of Semantic Web in Health Informatics
 
Spring Data Neo4j Intro SpringOne 2011
Spring Data Neo4j Intro SpringOne 2011Spring Data Neo4j Intro SpringOne 2011
Spring Data Neo4j Intro SpringOne 2011
 
NO SQL: What, Why, How
NO SQL: What, Why, HowNO SQL: What, Why, How
NO SQL: What, Why, How
 
2014 aus-agta
2014 aus-agta2014 aus-agta
2014 aus-agta
 
The Symbiotic Nature of Provenance and Workflow
The Symbiotic Nature of Provenance and WorkflowThe Symbiotic Nature of Provenance and Workflow
The Symbiotic Nature of Provenance and Workflow
 
AI Beyond Deep Learning
AI Beyond Deep LearningAI Beyond Deep Learning
AI Beyond Deep Learning
 

Recently uploaded

(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...
(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...
(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...AliaaTarek5
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demoHarshalMandlekar2
 
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better StrongerModern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better Strongerpanagenda
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationKnoldus Inc.
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...Wes McKinney
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfpanagenda
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
Assure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyesAssure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyesThousandEyes
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesThousandEyes
 
Scale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterScale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterMydbops
 
Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...Rick Flair
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
Emixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native developmentEmixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native developmentPim van der Noll
 
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...Alkin Tezuysal
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...
Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...
Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...Scott Andery
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Farhan Tariq
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 

Recently uploaded (20)

(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...
(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...
(How to Program) Paul Deitel, Harvey Deitel-Java How to Program, Early Object...
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demo
 
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better StrongerModern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog Presentation
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
Assure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyesAssure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyes
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
 
Scale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL RouterScale your database traffic with Read & Write split using MySQL Router
Scale your database traffic with Read & Write split using MySQL Router
 
Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
Emixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native developmentEmixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native development
 
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...
Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...
Enhancing User Experience - Exploring the Latest Features of Tallyman Axis Lo...
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 

Anchor Modeling GSE11 Presentation

  • 1. Anchor Modeling A Technique for Information under Evolution Lars Rönnbäck @ GSE Nordics June 7–9, 2011
  • 2. INFORMATION MONEY LOVE Google ngram viewer Graph showing relative occurrence of words in literature over the last century Information is rapidly becoming the most important asset
  • 3. c litus Hera C 5 00.B “Panta rhei” Everything flows
  • 4. Evolving Information Changing content Changing structure Changing constraints Changing interpretation There's a big difference between saying: "This Changing origins information has a 95% reliability" and "This Changing reliability information is 100% reliable".
  • 5. What is a database? The purpose of a database is to store a body of information and allow searches over it. The purpose of a temporal database is to store a body of information under evolution and allow historical searches over it. t a re no , we But e yet! ther
  • 6. What is a Data Warehouse? Integrates information from many sources Keeps a history of changes Provides “one version of the truth” Enables reporting, ad-hoc analysis, mining Calculates and stores new information
  • 7. The dilemma Many sources and many users naturally lack of result in many tim ion adherence er at changes e ov rad g de 25% 55% Dimensional Modeling 20% Normalized Haphazard lack of adherence
  • 8. Patch or Redo? Patching works initially to cope with new requirements Maintenance costs usually rise proportionally to the lifetime of the data warehouse Redoing is unavoidable at some point (and for dimensional modeling sometimes accounted for) The average lifetime is five years The return of investment should and could be much better with a longer lifetime!
  • 9. What is Anchor Modeling? Anchor Modeling combines normalization and emulation to provide an agile database modeling technique for evolving information that is implementable in current relational databases. Most, if not all, of what Anchor Modeling is doing in its physical (relational) representation could be "hidden" from the end-user in a true temporal database.
  • 10. Technologies Entity-Relationship one- Modeling to- one Sixth Normal Form Tables Temporal Database Emulation
  • 11. History Best Paper Award @ ER’09 Maria Petia Lars Olle Paul Bergholtz Wohed research Rönnbäck Regardt Johannesson DW consulting SU DW DKE GSE DW MDM EDW DW TDWI WWW ER09 TOOL AMW 03 04 05 06 07 08 09 10 11
  • 12. Philosophy Make modeling free from assumptions Make modeling agile and iterative Make evolution non-destructive Do not duplicate information Do not alter existing information Decouple metadata from the model Provide a simple interface for queries
  • 13. Evolutio Changing content Anchor M n in full support [6NF + time of change] odeling Changing structure full support (through extensions) [non-destructive schema evolution] Changing constraints minimal support [only primary and foreign keys] Changing interpretation achievable [explicitly modeled] Changing origins restricted support [using metadata] Changing reliability restricted support [using metadata]
  • 14. ionin g Posit odeling Domain chor M driven An modeling Data Vault/ODS/3NF (Inmon) mimics Anchor Modeling reality mimics mimics Use- Data structure searches case driven driven modeling modeling Dimensional Modeling (Kimball)
  • 15. Basic Notions Attributes – properties Example: The surname of a Person <#42, ‘Rönnbäck’, 2004-06-19> Anchors – entities Example: A Person  <#42> (holds only identities of entities)     Knots – shared properties Example: The gender of a Person Ties – relationships <#1, ‘Male’> + <#42, #1> Example: The children of a Person <#42, #4711>
  • 16. Historization <#42, ‘Samuelsson’, 1972-08-20> closed interval historical information <#42, ‘Rönnbäck’, 2004-06-19> open interval current information Historization is done using the time of change as the start of an interval implicitly closed by another instance of Note tha t UPDAT the same identity with a later never al lowed in E is time of change. anchor databas an e
  • 17. The Modeling Tool www.anchormodeling.com/modeler Open Source Online (HTML5) Free to use In the Cloud EM O! XML Interchange Format D Automatic generation of SQL scripts Interactive (force-directed) Layout Engine
  • 18. Important Benefits Handles evolving information (keeping the integrity intact) Increases longevity (databases with long life expectancy) Simplifies modeling concepts (less prone to error) Enables modular and iterative development Needs no translation logic to the physical layer Automates generation of scripts No downtime when upgrading databases Scans only relevant data during searches Sparse data cause no gaps (no null values)
  • 19. More Information : Twitter: anchormod Homepage m eling ode ling.co w. anchorm ht tp://ww od eling Tool Tutorials . M B log . Video deling.com E -mail: lars.r onnback@anchormo LinkedIn Groups: Anchor Modeling Temporal Data Modeling Temporal Data

Editor's Notes

  1. \n
  2. \n
  3. \n
  4. \n
  5. \n
  6. \n
  7. \n
  8. \n
  9. \n
  10. \n
  11. \n
  12. \n
  13. \n
  14. \n
  15. \n
  16. \n
  17. \n
  18. \n
  19. \n