XBRL and Complex Data mapping

Paul SnijdersCEO Semansys Technologies BVBoard member XBRL NederlandFounding member XBRL in EuropeFormer vice chair XBRL Solutions groupProject Manager Architecture NTP

XBRL: from a software point of view

XBRL process Data models in XBRL Data mapping Conclusions

Important forimplementation

Presentation is based on cases

90’ties 1999 2000 2001 2002 20042003 2005 2006

Scripting &Automation

XBRL 1.0Composer

XBRL 2.0Composer

XBRL 2.1Composer

Professional XBRL Development Kit

Conformance Suite Support

XBRL validator

XBRL receiving and processing application

XBRL DeploymentManager

Semansys is the first to offer a complete application suite for digital reporting based on XBRL, enabling organizations to optimize their internal and external financial reporting and business monitoring processes.

Semantic BusinessIntelligence

XBRL 1.0, XBRL 2.0, XBRL 2.1, XBRL GL ,Conformance Suite, Dimensions, LRR, FRTA, FRIS, Formulas,

Projects

• First European projects XBRL

• Dutch Treasury

• NTP, Netherlands Taxonomy Project

• Water Boards

• Local Government• (60.000 data elements, 150+ contexts)

• Large bank/Daily Close, • (50!!! Dimensions, 500 contexts dynamically generated every day)

• Banks in Europe• (dimensional mapping, conversions)

When is data mapping important

XBRL and basic financial data XBRL and reporting data XBRL and dimensional data Mapping with multiple taxonomies XBRL and data warehousing XBRL-GL and financial applications

Current software products

Accounting

ERP/GL

Logic

BusinessIntelligence

Data Warehouse

Logic

ConsolidationReporting

FinancialReporting

Logic

Taxreporting

TaxSoftware

Logic Each application has

proprietary data definitions

Applications have different

data models

The XBRL reporting process

Validation

Compliance checking

Analysis

Taxonomy creation

Accountingrules

Validation

Regulator

TaxonomyTaxonomy

Data entryManual Tagging

XBRLReport

XBRLReport

ERP/GL

Logic

Data Warehouse

Logic

FinancialReporting

Logic

TaxSoftware

Logic

Mapping

Validation

Companies

XBRLReport

XBRLReport

Reporting

Area of interest

XBRL is externalization of data

XBRL delivers standardization and externalization of data definition and data validation

Data exchange format Data definitions

also labels, references

Multiple data modelsHierarchical, dimensional and relational

Validation rules

Externalization of:

Exports, Queries Data Dictionary

Application data modelRDMB, Cubes

Impact on

Data in XBRL?

XBRL has a complex data structure XBRL holds many data models XBRL data is different per output XBRL has data validation and quality inside XBRL is NOT a standard chart of accounts

XBRL data mapping is needed

Example XBRL

Based on

Taxonomy

Goodwill 3.400.500Goodwill 3.400.500Goodwill 3.400.500Goodwill 3.400.500

Turnover 168920000Turnover 168920000Turnover 168920000Turnover 168920000

Common stock 12.500.000Common stock 12.500.000Common stock 12.500.000Common stock 12.500.000CEO Bill GatesCEO Bill GatesCEO Bill GatesCEO Bill GatesProfit 45.870.000Profit 45.870.000

Data element

XBRL: more than a data definition

LabelCash & Cash Equivalents

LabelCash & Cash Equivalents

LabelKas en Geldmiddelen

LabelKas en Geldmiddelen

FormulasCash Beginning Balance ≥ 0

FormulasCash Beginning Balance ≥ 0

ReferencesIAS 16, 2, a

ReferencesIAS 16, 2, a

PresentationAnnual report

PresentationAnnual report

PresentationBalance sheet Indirect

PresentationBalance sheet Indirect

PresentationIncome statement

PresentationIncome statementPresentationCash flow statement

PresentationCash flow statement

CalculationCash = Currency + Deposits

CalculationCash = Currency + Deposits

Currency Euro/US$ M2,

Currency Euro/US$ M2,

Segment2Prod TVHifi

Segment2Prod TVHifi

Segment2VideoAudio

Segment2VideoAudio

ScenarioBudgetActual

ScenarioBudgetActual

PeriodFY 2004 Q1,

PeriodFY 2004 Q1,

Segment1BeneluxEU

Segment1BeneluxEU

LabelComptant et Comptant Equivalents

LabelComptant et Comptant Equivalents

LabelGeld & Geld nahe Mittel

LabelGeld & Geld nahe Mittel

LabelГроші та їх еквіваленти

LabelГроші та їх еквіваленти

XBRL Taxonomy

XBRL Instance

ElementsElements

Profit : 45.870.000Profit : 45.870.000

Entity: XYZ Ltd Entity: XYZ Ltd

Instance document

Instance document

<ifrs:profit contextRef=“Contex1” unitRef=“Euros” Decimal=“0”>45870000</ifrs:profit>

Data

Taxonomy

<xbrli:unit xbrli:id="u0"> <xbrli:measure>iso4217:EUR </xbrli:measure> </xbrli:unit>

Unit

<xbrli:entity>Virtual Company</xbrli:entity > <segment>North</Segment><xbrli:period> <xbrli:startDate>2004-01-01</xbrli:startDate> <xbrli:endDate>2004-06-30</xbrli:endDate> </xbrli:period> <scenario> <Scenario>Actual</Scenario> </scenario>

Context Definition

Simplified

Instance data: is a simple star schema

C2

C1

Context

C3

Unit2

Unit1

Unit

Unit3

ifrs-gp_bank

ifrs-gp_Cash

Taxonomy element

ifrs-gp_loan

23.750

112.340

Value

454

ElementData

C2

C1

Value

Unit2

Unit1

Unit

C3 Unit3

UnitsReference

Entity A

Entity A

Entity

Entity B

C2

C1

Context

C3

31-12-2006

01-01-2006

Period

1-12-2006 31-12-2006

Budget

Actual

Scenario

Pro forma

TV

Hifi

Products

USA

Regions

Far East

Dealers

Internet

Channel

Direct sale

Contexts

Reference

Technical fundament of XBRL

• XBRL specification 2.1• Schema driven XML language• Heavy use of X-link

• Data structuring• Relational data models• Multidimensional structures• Hierarchical data• Flat structures• Multiple data representations

• Fully extensible • Taxonomies• Data structuring• XML and custom data types• Presentation & Calculation

Important

Different data models in XBRL

Element 1: 4000Element 2: 203Element 3: AmsterdamElement 4: 8000Element 5: KPMG

Simple list

+ Element 1: 12000 + Element 2: 8000 + Element 3: 4000Element 4: Address Element 5: Street Element 6: zip

Hierarchy

Relational

6000Street 4Address 4Employee 4

Street 3

Street 2

Street 1

Street

4000Address 3Employee 3

1700Address 2Employee 2

1300Address 1Employee 1

SalaryAddressName

6007507000Employee 4

560

420

230

4005000Employee 3

1702700Employee 2

1302300Employee 1

Insur.GrossName Soc.Sec

Multi dimensional

200300 Costs

1100012000 Sales

18002700 Profit

BudgetActualSales, 2006 April

200024002500Product D

1200

400

UK

10002000Product C

700Product B

300500Product A

FranceGermanySales, 2006 Actual, April

XX

Data mapping

Account Account - XBRL

Data preparation Data transformation Data cleansing

Dimensions Dimensional mapping Dimension data transformation

Accept Transform Import layer

Accept Transform Import

Discussion points

Account – taxonomy mapping Check on processing Account transformations Account value mapping Checks on processing

Dimensional mapping Dimensional data transformation Checks on processing

Account – XBRL mapping

1 Simple account mapping

Account Result

100.100.10 Cash 45.000

Data value mapping

IFRS-GP_CashEquivalents 45000

Mapping

Account – XBRL mapping Checks

GAP analysis Is there a match between COA and mapping

No new accounts Account have same meaning

Checks on processing Is the correct data set collected

Monthly process closed Complete dataset, correct query

Is the correct account map used

Account transformations

Cost centre = NOT used

Main account code = used

Xxx.yyy.zzz

Account transformation2

yyy needs to be converted to …..

Xxx.yyy.zzz

Account transformation3

Data value transformations

Account Debit Credit Result

100.100.10 Loan 23.750 12.250 11.500

IFRS-GP_Loan 11.500 IFRS-GP_LoanDecrease 12.250

IFRS-GP_LoanIncrease 23.750

Mapping account values to different Elements

Account Result

100.100.10 Cash 11.450,45

Value transformation

IFRS-GP_CashEquivalents 11.500

(+ - / * )Calculations

4

5

Data value transformations

6 Mapping based on signAccount value Positive Element A

Account value Negative Element B

7 Sign conversion Account value Signs need to be converted to Debit or Credit elements

Checks on processing

Correct account mapping Correct mapping file Correctness of account transformation Correct value to element mapping Correctness of value transformation (calculation)

What to do with calculation roundings

What is the unit of the values (currency)

What is the scenario of the values (budget/actual)

Dimensional mapping

8 Simple: Internal dimension = reporting dimensionDimension members = dimensions members

Internal dimension External dimension

Region Country

9 Different dimension names

Internal dimension External dimension

Domestic Spain

Verenigde Staten USA

10 Different member names

Dimensional mapping

11 Internal dimension External dimension

Region Country

USA

Canada

Different members

North America

Internal dimension External dimension

Region Country

USA

Canada

North America

Dimensional mapping Checks

Correct content Correct dimension definitions Correct translations Completeness

Cross totals over all dimensions Match with Account mapping

Audit trail, change log

Mapping summary

XBRL is a great global standard for financial reporting and

business intelligence/Data warehousing

XBRL can contain multiple data models

Data mapping requires attention and specific

functionalities

Account mapping, data transformation

Dimensional mapping, dimensional transformation

Audit and control on mapping is advisable

Advanced Import Mapping Functionality

TaxonomyMapping

DBMapping

Gap Analysis

Audit &Control

InstanceGeneration

Account Mapping - Simple - data transformation - conditional mapping - sign conversion - Add/replace/subtract values

Dimensional mapping - Simple - dimension name change - dimension member change - conversion mapping

DB integration- Database integration- automatic load- Multiple database API’s

Accept Transform Import

Semansys’ software support

Specific customizationScriptingData controlAudit trail

Todo’s

Understand the mapping issue Investigate current databases Investigate XBRL reporting data models

Customize and automate the Mapping Account mapping Data transformations Dimensional mappings

Audit and control Check the mapping and transformations Implement process control

Thank you

paul.snijders@semansys.com

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