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Advantages of a Layered Architecture for Enterprise Data Warehouse Systems

1

Enterprise Data Warehouse Systems

Thorsten Winsemann, Veit Köppen, Gunter Saake

Otto-von-Guericke-Universität, Magdeburg/Germany

(2)

Table of contents

1. Characteristics of Enterprise Data Warehouses 2. Traditional Data Warehouse Architecture

1. Reference Architecture 2. Dataflow-Example

3. Architectures for Enterprise Data Warehouses 1. SAP’s Layered, Scalable Architecture

2

1. SAP’s Layered, Scalable Architecture 2. Layers in Detail

3. Dataflow-Example

4. Simple, but Detailed Example 4. Architectural Differences

1. Overview

2. Advantages of a Layered Architecture

(3)

Characteristics of Enterprise Data Warehouses (EDW)

• Business DW, thus covering all business areas

• Data basis for several applications, such as BI, planning, CRM, …

• Single Version of Truth of company’s data

3

• Single Version of Truth of company’s data

• Multiple, heterogeneous source systems

• Huge amount of data (granular, detailed, old)

• World-wide scope, different time zones

• 24*7-hours availability

• …

(4)

Traditional Data Warehouse Architecture:

Reference Architecture

User

D a ta W a re h o u s e S ys te m

Data Marts O p e ra tio n a l D a ta S to re

4

Data Sources

D a ta W a re h o u s e S ys te m

O p e ra tio n a l D a ta S to re

Basis Data Base

Staging Area

(5)

Traditional Data Warehouse Architecture:

Dataflow-Example

Sales Data Sales

Data Year 1

Sales Data Year 2

Sales Data Year 3

Basis Data Base Data Marts

5

Staging Area

Sales Order Header Data

Sales Order Item Data

Sale Invoice Header Data

Sale Invoice Item Data

ERP System

DW System

Transformation

(6)

Architecture for Enterprise Data Warehouses:

SAP’s Layered, Scalable Architecture

User

D a ta W a re h o u s e S ys te m

Reporting & Analysis Layer Business Transformation Layer

O p e ra tio n a l D a ta S to re

6

Data Sources

D a ta W a re h o u s e S ys te m

Business Transformation Layer

O p e ra tio n a l D a ta S to re

Data Propagation Layer Quality & Harmonisation Layer

Corporate Memory

Data Acquisition Layer

(7)

Architecture for Enterprise Data Warehouses:

Dataflow-Example

Sales Data Year 1

Sales Data Year 2

Sales Data Year 3 Reporting & Analysis

Sales Order

Data

Sale Invoice

Data

DW System

Sales Sales Sale Sale

Transformation

Transformation

Data Propagation Business Transformation

Transformation Transformation

Transformation

Special Sales

Data

Transformation

Special Sales

Data

7

Sales Order Header Data

Sales Order Item Data

Sale Invoice Header Data

Sale Invoice Item Data

ERP System

Transfor- mation

Data Acquisition + Corporate Memory Sales

Order Header Data

Sales Order

Item Data

Sale Invoice Header Data

Sale Invoice

Item Data

Transfor- mation

Transfor- mation

Transfor- mation

Quality & Harmonization

Sales Order Header Data

Sales Order

Item Data

Sale Invoice Header Data

Sale Invoice

Item

Data

(8)

Architecture for Enterprise Data Warehouses:

Layers in Detail (1)

• Data Acquisition Layer

– „DW Inbox“ (temporary)

– Data stored immediately without changes

• Corporate Memory

8

• Corporate Memory

– „DW Life Insurance“ (long-term, granular, complete)

– Data for non-predictable demands („master the unkown“)

• Quality & Harmonization Layer

– Technical and semantical data integration

– Usually no data storage

(9)

Architecture for Enterprise Data Warehouses:

Layers in Detail (2)

• Data Propagation Layer

– „Single Version of Truth“

– Harmonized, integrated data without business logic

• Business Transformation Layer

9

• Business Transformation Layer

– Data are transformed according to business‘ needs – E.g., combination of sales + finance figures

• Reporting & Analysis Layer

– Data are transformed according to requirements for

usage and fast access performance

(10)

Architectures for Enterprise Data Warehouses:

Simple, but Detailed Example (1)

Data Aquisition Layer + Corporate Memory

ORDNR ITMNO MATNR QUASU UNITS AMDCO CURRD

Char10 Char4 Char15 Dec10,3 Char3 Dec15,2 Char3 0000012345 0001 ABT00471 2,000 BOX 300,00 EUR Sales Order

Sales Order - Item

Harmonization & Quality Layer (no persistence!)

INVNR DATEI CUSTOM ORDNR DATEP

Char10 Char8 Char10 Char10 Char8

IN02085 20100805 0007410000 0000012345 20100820

INVNR ITMNI MATNR QUABU UNITB AMDCI CURRD

Char10 Char4 Char15 Dec10,3 Char3 Dec10,2 Char3

IN02085 0001 ABT00471 4,000 PC 285,00 EUR

Sale Invoice

Sale Invoice - Item

ORDNR DATEO CUSTOM

Char10 Char8 Char10

0000012345 20100730 0007410000

Data types adapted Homonyms split Synonyms merged

10

DOCNR ODATE BUYER

Numc10 Char10 Char10 12345 30.07.2010 0007410000

DOCNR ITMNR ARTNR QUASU SUNIT AMDCI DCURR

Numc10 Numc4 Char15 Dec10,2 Char3 Dec15,2 Char2

DOCNR INVDT PAYER ORDER PDATE

Char7 Char6 Char7 Numc10 Char6 IN02085 100805 7410000 12345 100820

DOCNR ITMNR MATNR QUANT BUNIT AMDCI DCURR

Char7 Numc3 Char8 Dec10,3 Char2 Dec10,2 Char3 Sales Order

Sales Order - Item

Sale Invoice

Sale Invoice - Item

System A:

Ordering

System B:

Invoicing

DOCNR ITMNR ARTNR QUASU SUNIT AMODC DCURR SYSID

Numc10 Numc4 Char15 Dec10,2 Char3 Dec15,2 Char2 Char3

12345 1 ABT00471 2,00 BOX 300,00 EU SAO

Sales Order

Sales Order - Item

DOCNR INVDT PAYER ORDER PDATE SYSID

Char7 Char6 Char7 Numc10 Char6 Char3

IN02085 100805 7410000 12345 100820 SBI

DOCNR ITMNR ARTNR QUANT BUNIT AMODC DCURR SYSID

Char7 Numc3 Char8 Dec10,3 Char2 Dec10,2 Char3 Char3

IN02085 1 ABT00471 4,000 ST 285,00 EUR SBI

Sale Invoice

Sale Invoice - Item

DOCNR ODATE BUYER SYSID

Numc10 Char10 Char10 Char3

12345 30.07.2010 0007410000 SAO

Synonyms merged Field names changed

System-ID added

(11)

Architectures for Enterprise Data Warehouses:

Simple, but Detailed Example (2)

Sales Orders

Business Transformation Layer

CUSTOM MATNR MATGR DATEO QUABU UNITB DATEP AMDCI CURRD

Char10 Char15 Char3 Char8 Dec10,3 Char3 Char8 Dec10,2 Char3

0007410000 ABT00471 ABT 20100730 4,000 PC 20100820 285,00 EUR Sales

Reporting & Analysis Layer

CUSTOM MONTH AMLCI CURRL PRPPC

Char10 Char6 Dec10,2 Char3 Dec10,2 0007410000 201008 200,00 GBP 50,00

Report Execution (no persistence!)

Further information added

Data combined (according to usage)

11

ORDNR ITMNO MATNR QUASU UNITS QUABU UNITB AMODC CURRD

Char10 Char4 Char15 Dec10,3 Char3 Dec10,3 Char3 Dec15,2 Char3

0000012345 0001 ABT00471 2,000 BOX 4,000 PC 300,00 EUR

Sales Order

Sales Order - Item

INVNR DATEI CUSTOM ORDNR DATEP

Char10 Char8 Char10 Char10 Char8

IN02085 20100805 0007410000 0000012345 20100820

INVNR ITMNO MATNR QUABU UNITB AMODC CURRD

Char10 Char4 Char15 Dec10,3 Char3 Dec10,2 Char3

IN02085 0001 ABT00471 4,000 PC 285,00 EUR

Sale Invoice

Sale Invoice - Item

ORDNR DATEO CUSTOM

Char10 Char8 Char10

0000012345 20100730 0007410000

Harmonization & Quality Layer Data Propagation Layer

ORDNR ITMNO DATEO CUSTOM MATNR QUASU UNITS QUABU UNITB AMDCO CURRD

Char10 Char4 Char8 Char10 Char15 Dec10,3 Char3 Dec10,3 Char3 Dec15,2 Char3

0000012345 0001 20100730 0007410000 ABT00471 2,000 BOX 4,000 PC 300,00 EUR

INVNR ITMNI MATNR DATEI CUSTOM ORDNR DATEP QUABU UNITB AMDCI CURRD

Char10 Char4 Char15 Char8 Char10 Char10 Char8 Dec10,3 Char3 Dec10,2 Char3

IN02085 0001 ABT00471 20100805 0007410000 0000012345 20100820 4,000 PC 285,00 EUR Sale Invoices

Additional information added Data configured

(according to business‘ needs)

(12)

Architectural Differences:

Overview

Matter Reference Architecture Layered Architecture

Complexity Medium High (several layers)

Data volume High Very high

Conceptual work Medium (requirement-driven) High (overall concept view)

Implementation effort Medium High

12

Enhancement & scalability Possible Supported

(13)

Architectural Differences:

Advantages of a Layered Architecture

Matter Reference Architecture Layered Architecture Change of transformation

rules (e.g., changed key- figure calculation)

Reload/-build from source system

Rebuild from propagation layer

Change of data (e.g., new key-figure calculation)

Reload/-build from source system

Rebuild from propagation layer

13

Need for new data Dataflow enhancement and reload/-build

Load from propagation layer or corporate memory

„Single Version of Truth“ No Yes

Decoupling of data load and availability

No/limited Yes/supported

Detailed previous data Limited Available (corporate memory)

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Appendix

2 3

4 5

CSDM 2011 Poster Layout

Slides‘ Arrangement on Panel

Panel: 150x125cm

6 7

8 9 1

Panel: 150x125cm Slides: A3 + A4

12

13 10

11

Referenzen

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