model drivers: datapoint modelling and its opportunity 2013-09-01
DESCRIPTION
The datapoint model offers a solution to the problem of giving data consumers flexibility while enforcing integrity. It breaks down data structures into datapoints, maximizing flexibility and re-use. It also enables end users perspectives of the data to be wire together, giving them structure and simplicity. These slides are from our YouTube presentation.TRANSCRIPT
The Datapoint modelling breakthrough and its opportunity
2013-09
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About Model Drivers
Business model industrialization.
Model driven products and services: •Reporting•Testing•Regulatory conformance•Business strategy and business cases•Business architecture•Systems delivery
2013-09 Datapoint modelling and its opportunity
Datapoint modelling and its opportunity
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Agenda
A. The problemB. What is Datapoint Modelling?C. Steps to exploiting the opportunity of Data Point ModellingD. Summary and further reading
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Datapoint modelling and its opportunity
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A: The problem
Everyone wants their cake, and to eat it too. There is only one cake.Each data management approach has weaknesses
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One piece of data, many voices
All this must be true: • There can
only be one source of truth
• It must be concrete and accurate
• Many players must view it in their own, very differently ways
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Client data
I need ….. We order that… I don’t care!
No way can we…
Look, it …
I have to …
Accounts data
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The model-less reporting architecture
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No one can afford gaps, inconsistency, errors in 100’s
of business reports.Not sure which is worse –
wrong / late internal reports for decision making
Or wrong reports to regulatorsBusiness
Unit ABusiness
Unit BBusiness
Unit CBusiness
Unit D
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Will Logical Data Modelling solve the problem?
LDM has • Hard coded concepts
and relationships• Single set of opinions
of how things are
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Hard coded attributes of
concepts
Hard coded relationships
New concepts are big deal
Great for transaction processing
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Will Ontology based technologies solve the problem?
Ontologies are•Generic and global•Flexible
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Fox Rabbit
eats
“Concepts “ have
relationships: “Is like”, “Is A”
Carnivore Herbivore
Is in the family of
Mammal
Is a species of
Is in the family of
Is a species of
Great for understanding
complex worlds
Datapoint modelling and its opportunity
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Will Data Warehouse technology solve the problem?
Star Schema models•Handle large volumes•Give access via many dimensions
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Client facts table
City
State
Country
Company
Department
Branch
Day
Month
Year
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B: What is Data Point Modelling?
Datapoint Modelling gives you both concrete data and flexibilityThe global business reporting language XBRL support DPMData point model meta model has one dozen main concepts The value of DPM shows in the user experience
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Data Point Modelling is getting global adoption
• Industry leaders are implementing Data Point Modelling for reporting and big data– XBRL International: Abstract Model– EBA : CRD IV
Reporting http://www.eba.europa.eu/News--Communications/Year/2013/Update-on-the-technical-standards-on-supervisory-r.aspx
– OMG (CWM includes data point modelling) http://en.wikipedia.org/wiki/Common_Warehouse_Metamodel
•Frsglobal– [Datapoint models] …will also give the regulatory authorities a tool to address
systemic industry-wide issues, something that has been called for time and time again in light of the financial crisis. Furthermore, the regulator will be able to combine information effectively in new and innovative ways.
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The Data Point Model
Data Point Models• Every piece of data
is unique, identifiable
• Every piece of data has a set of dimensions (Aspects)
• The aspects can be pulled together dynamically
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DP 1City
State
Country
Company
Department
Branch
Day
Month
Year
DP 1
DP 1
Daily Sales
Datapoint modelling and its opportunity
ABOUT XBRL
•eXstensible Business Reporting Language•Reports business data in XML•Taxonomies define valid forms e.g. SEC Quarterly filing•Allows extensions by individual submitters•Scope includes:
– Accounts– Social responsibility– Carbon and other emissions– Many others
•Mandated by– SEC– EU– Governments of Australian, Singapore etc– China stock exchange– Many more
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Example implantation: The SEC and regulatory reports
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Massive volumes of
business data
Every data point
annotated with definition and
other meta data
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Example implementation: Arelle, open source XBRL
• Taxonomy review
• Basic ability with instance docs
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http://www.sec.gov/Archives/edgar/data/19617/000001961713000221/jpm-20121231.xml
JPMorgan instance doc
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Data point model: the business report meta model has dozen main concepts
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Value
Value Set
Data point
Aspect
CubeBusiness class
Resource link
ResourceAxis
Axis coord.
Table
Datapoint modelling and its opportunity
Abstract / Meta model of a report
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We get graphical, automated, logical report design
And mapping to the business domain
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C: Steps to exploiting the opportunity of DPM
1) Adopt the mental model2) Architect your understanding of your data3) Given users both concrete and flexible data with PDM4) Industrialize your reporting process
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1) Adopt the mental model
• There are a number of data architecting approaches, each with strengths and weaknesses
• The Data Point model supports both concrete data definitions and multiple view points
• DMP therefor is ideal for supporting reporting and analytic type functions
we are gearing up for a shift to polyglot persistence [1] -
where any decent sized enterprise will have a variety
of different data storage technologies for different
kinds of data. http://www.martinfowler.com/bliki/PolyglotPersistence.html
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Datapoint modelling and its opportunity
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Manage
2) Architect your understanding of your data
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Business Domain
DataData
warehouse
Consumer(Regulator, manager,
analyst..)
Extract &
formatSubmission
modellDR
Data point
model
Taxonomy design
Business domain
LDM
View, Publish,Analyse
Arelle, EDGAR
Oracle, NoSQLBusiness Objects, Cognos
RDF, SparqlOntology
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3) Given users both concrete and flexible data with PDM
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Taxonomy
Environment & technologycan be different –
the taxonomy has to be the same
Automated
Still un-happy, but with someone else
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4) Industrialize your reporting process
Implement the big ideas of Reporting Industrialization• Big idea 1: Industrialise the understanding of your data• Big idea 2: Industrialise your reporting and analytics
ecosystem• Big idea 3: Map your business data understanding to your
reporting and analytics requirements• Big idea 4: Drive reporting and analytics through
automation and tooling
See the presentation “How to industrialize business reporting”
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D: Summary and further reading
Data point modelling has strengths in reporting and analyticsIt supports industrialization of the reporting process
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Datapoint modelling and its opportunity
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D: Next steps
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Contact me http://uk.linkedin.com/in/gregsoulsby/ www.modeldrivers.us
News on twitter https://twitter.com/model_dr
This slide deck http://www.slideshare.net/greg.soulsby/
Next presentation: Building data point models To be updated here. Follow me on twitterhttps://twitter.com/model_dr
EDGAR – SEC online view of submitted http://www.sec.gov/edgar.shtml
Arelle – Open source XBRL software report http://arelle.org/
XBRL Abstract model specification http://www.xbrl.org/Specification/abstractmodel-primary/PWD-2012-06-06/abstractmodel-primary-pwd-2012-06-06.html
DATA POINT MODEL presentation, Ignacio Santos, Bank of Spain
http://www.openfiling.info/wp-content/upLoads/data/DPMvsMDM_1.pdf
EBA’s Data Point Model: A reporting game changer for management information
http://www.frsglobal.com/news_and_events/ebas-data-point-model-a-reporting-game-changer-for-management-information.html
EBA: Implementing Technical Standard (ITS) on Supervisory Reporting (Data Point Model)
http://www.eba.europa.eu/regulation-and-policy/supervisory-reporting/implementing-technical-standard-on-supervisory-reporting-data-point-model-/-/regulatory-activity/consultation-paper
The Data Point Model methodology in the European Supervision: COREP/FINREP
http://www.eurofiling.info/documents/DataPointModelMethodologyIB.pdf