© SAP AG 2004, Enterprise Wide BW, J. Haupt / 2
Content
Enterprise Wide BW Enterprise Wide BW -- BackgroundBackground
Elements of a Corporate BW StrategyElements of a Corporate BW Strategy
The BW Data Model Prevents SilosThe BW Data Model Prevents Silos
BW Data Layers Guarantee Reliability and FlexibilityBW Data Layers Guarantee Reliability and Flexibility
BW Corporate Landscape PatternsBW Corporate Landscape Patterns
Content
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 3
Enterprise Wide BW
Background Continuously increasing number of BW installationsSteady growth and coverage of BW installations High degree of customer-satisfaction with BWBroad analyst acceptance of BW and the packaged solution approach In general a renaissance of data warehousing
Introduce an enterprise wide BW Strategy and Guidelines that guarantees :FlexibilityReliability
at low costs
What offers BW to help you realizing an enterprise Data Warehouse Strategy ?What are the elements of an enterprise BW Strategy ?
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 4
Enterprise Perspective on BW
Enterprise perspective on BW:Higher level organizational units wantto harmonize the lower level BW initiatives
Architecture-based BW implementationfrom the very beginning Stabilize a mature BW landscape(Overhaul the architecture)
GroupGroup
Division ADivision A Division BDivision B Division CDivision C Division DDivision D
............ RetailRetailBusinessMarketing
BusinessMarketing
..............
EuropeEurope AmericasAmericasAsia/
PacificAsia/
Pacific
GermanyGermanySpainSpain
UKUKFranceFrance
NordicNordic
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 5
Multiple BW Implementations – Challenges
Source
Source
Source
Source
Source
Source
Source Source
LocalBW
LocalBW
Source
Source
SourceLocalBW
Unit 2BW
Successful Data Warehousing means: controlled redundancy !
LocalBW
LocalBW
Stream BBW
Stream C BW
GroupBW Stream A
BW
Unit 1BW
Consistency issues:Uncontrolled data flowsMultiple extractions of same dataCostly developmentNot aligned data models
Danger of ‘high level’ Silos
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 6
Local BW Implementation – Challenges
....Real World
Informationrequirements
Schema-Modeling
Data Marts-InfoCubes
Extraction
Sources
Business Rules
Transformation
BW
Project Team
Observations:Incremental set upSolution-Focus (Data Marts)Departmental viewProject is responsible for the entire Data Warehouse Process
Potential consequences:Departmental islands (silos) Consistency problemsCompleteness not sufficientFlexibility restrictedTrace back not possible
Successful Data Warehousing means: controlled redundancy !
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 7
Corporate Data Warehousing Strategy
Missing corporate strategy and guidelinesPotential consequences:
Silo solutionsDoubtful reliabilityRestricted flexibilityHigh costs
Means:Uncontrolled RedundancyLimited Solution Focus
Prerequisites to set up a proper strategy:Awarenessabout accepted data warehousing concepts and their benefits
Support of corporate management (Sponsorship)
If there is no organizational momentum toward a common goal, then the best architecture, the best framework in the world is bound to fail.
W.H. Inmon“
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 8
Who needs a Corporate BW Strategy?All, but the prerequisites are different!
Group
Stream A Stream B Stream C Stream D
...... Retail BusinessMarketing ......
Regions/ countries
Headquarter
Region A Region B Region C
countries
Architecture-, SAP-based,
‚single Instance‘
Legacy R/3
Legacy R/3
Legacy Legacy
Legacy
Organization,Business
OLTP landscape
Necessity of a corporate BW Strategy
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 9
Content
Enterprise Wide BW Enterprise Wide BW -- BackgroundBackground
Elements of a Corporate BW StrategyElements of a Corporate BW Strategy
The BW Data Model Prevents SilosThe BW Data Model Prevents Silos
BW Data Layers Guarantee Reliability and FlexibilityBW Data Layers Guarantee Reliability and Flexibility
BW Corporate Landscape PatternsBW Corporate Landscape Patterns
Content
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 10
Elements of a Corporate BW Strategy
BW Enterprise Data Warehousing Decision Areas
Architecture Application Development
IntegrationStrategySupport
Data Layer Data Model Landscape
Tactical/Strategic
Decision-Making
OperationalDecision-Making
Think of: Building a ‘Corporate Information Factory’ *- Avoid Silos
*The Corporate Information Factory: introduced by Inmon, Imhoff
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 11
The Role of a Consistent Data Warehouse Data Model
Consistent Data Warehouse Data Model ⇒ long term success
A challenge forData Warehouse
consistency
MaterialManagement
OLTP
SalesOLTP
Consistent corporate Data Model
?
HROLTP
Not aligned operational Data Models
Inconsistent Data Warehouse Data Models ⇒ Island-solutions (silos, stovepipes)
?
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 12
The BW Data Warehouse Data Model
BW offers as part of the Business Content a predefined expandable Data Warehouse Data Model
BW Data Warehouse Data Model for SAP und other
applications(InfoObjects & InfoSources)
SAP Corporate Data Model
Legacy Data Models
Consistent mapping of operative data models
For all SAP applicationsFor SAP industrial solutions(e.g. Retail, Utilities..)For non SAP application
Ascential PartnershipSiebel, Oracle ....
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 13
BW Extended Star Schema built on the BW Data Model
BW Extended Star Schemasbuilt on BW Data Model
0SALESPERS0SALESORG.....
0CUSTOMER00CUSTGR......
0MATERIAL0MATGR0MATTYPE......
BW InfoObject Master Data:
0CUSTOMER 0MATERIAL 0AMOUNT
BW InfoCube:
Customer Material Sales Person
Sales Transaction
Materialgroup Sales ORGMaterialType
Corporate Data Model:SAP Components
Shared/ Conformed Dimensions
scope-specific
BCT Extractors/ DataSources
BCT InfoSources ≡Subject Areas
Master Data Transaction Data
0MATERIAL 0MATGR 0MATTYPE 0DOCNO 0CUSTOMER 0SALESPERS 0MATERIAL 0AMOUNT
BW Data Model definedby Business Content
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 14
BW Extended Star Schemas Prevent Silos
Conformed dimensions enable virtual BW MultiProvider scenariosConformed dimensions enable virtual BW MultiProvider scenarios
FACT Table
Material_Dimension_ID..........._Dimension_ID.............Dimension_ID.............Dimension_ID
Key figure 1Key figure 2InfoCubeInfoCube
BB
LocalLocal Part of Material Dimension
Material_Dimension_ID
0MATERIAL0PROD_HIERMaterial Dimension
Table
FACT Table
Material_Dimension_IDSalesOrg_Dimension_IDTime_Dimension_IDCustomer_Dimension_ID
Sales AmountQuantity InfoCubeInfoCube
AA
Material_Dimension_ID
0MATERIALMaterial Dimension
Table
Gebiet 1 Gebiet 2 Gebiet 3
Bezirk 1
Gebiet 3a
Bezirk 2
Region 1
Gebiet 4 Gebiet 5
Bezirk 3
Region 2
Gebiet 6
Bezirk 4
Gebiet 7 Gebiet 8
Bezirk 5
Region 3
Vertriebsorganisation
Material Hierarchy Table
0MATERIALLanguage CodeMaterial Name
Material Text Table
Material Master Table
0MATERIALMaterial Type
LocalLocal Part of Material Dimension
Conformed, SharedConformed, SharedPart of
Material Dimension
Material Dimension:Material Dimension:local & conformed partlocal & conformed part
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 15
BW DWH Data Model and Enterprise Wide BW
The BW Data Warehouse Data Model is the glue,which ties everything together!
It protects against ‘silos’ (‘stove pipe solutions‘, ‘islands’)Within a BW InstanceWithin a BW Landscape
It is the basis for communication‘Drill Thru’ between BW solution structures (InfoCubes, ODS-Objects)
within a BW Instancewithin distributed BW Instances
‘Drill Thru’ between BW solution structures and SAP applicationsBetween people
Enterprise BW Strategy:Usage of delivered BW DWH data model whenever possibleCentral controlled guidelines for modifications and expansions
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 16
Content
Enterprise Wide BW Enterprise Wide BW -- BackgroundBackground
Elements of a Corporate BW StrategyElements of a Corporate BW Strategy
The BW Data Model Prevents SilosThe BW Data Model Prevents Silos
BW Data Layers Guarantee Reliability and FlexibilityBW Data Layers Guarantee Reliability and Flexibility
BW Corporate Landscape PatternsBW Corporate Landscape Patterns
Content
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 17
Introducing a BW Layer Architecture to Guarantee Reliability and Flexibility
PrimaryPrimaryData Data
ManagementManagement
DataDataAcquisitionAcquisition
Data Data DeliveryDelivery
SAP Business Information Warehouse andthe Corporate Information Factory (CIF)*
OperationalOperationalDataDataStoreStore
StagingStagingAreaArea
Extr
acti
on /
Ope
n St
agin
g
any
sour
ce
CleansingCleansingTransformTransform
MasterReference
Data
Data Data WarehouseWarehouse
TransactionData
any
targ
et
Open
Dis
tribu
tion
ArchitectedArchitectedData MartsData Marts
Finance
Logistic
‘The Data MartThe Data Mart is customized and/or summarized data derived from the data warehouse’
* Source: Bill Inmon
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 18
BW Architected Data Mart Layer: The Departmental Layer – What can we expect?
0CUSTOMERmaster
0MATERIALmaster
BW Extended Star Schema:InfoCubesInfoObject Master Data(‘conformed dimensions’)
0CUSTOMER
0MATERIAL
InfoCube A
0CUSTOMER
InfoCube B
0CUSTOMER
0MATERIAL
InfoCube C
The BW Data Mart Layer based on the BW Data Model and a proper Project Method offers
Consistency within the Data Marts (InfoCubes, ODS-Objekte)Control of data redundancy (MultiProvider, Queries)All desired historical views ...
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 19
BW Architected Data Mart Layer: The Departmental Layer – Corporate Needs ?
It is not the task of the scope-oriented Data Mart layer to anticipate all kinds of future arising needs – this would overload the schemas and corrupt performance
It cannot be expected that the data mart project teams have the 360°corporate view
We are limited from a corporate perspective in terms ofFlexibility, Completeness Reliability, Consistency
if we concentrate ourselves just on Data Marts.
BW Data Warehouse Layer – the corporate layer
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 20
The BW (Enterprise) Data Warehouse Layer:The Corporate Layer
SAP Business Information Warehouse andthe Corporate Information Factory (CIF)*
Open
Dis
tribu
tion
StagingStagingAreaArea
CleansingCleansingTransformTransform
MasterReference
Data
Data Data WarehouseWarehouse
OperationalOperationalDataDataStoreStore
PrimaryPrimaryData Data
ManagementManagement
Extr
acti
on /
Ope
n St
agin
gDataData
AcquisitionAcquisitionData Data
DeliverDeliver
any
targ
et
any
sour
ce TransactionData
ArchitectedArchitectedData MartsData Marts
* Source: Bill Inmon
Finance
LogisticThe result of the data transformation and cleansing process is stored persistently:
Subject orientedIntegratedGranularNon volatile (historical)Not scope-specific (not flavored)
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 21
The BW (Enterprise) Data Warehouse Layer The Corporate Layer – What can we expect?Reliability, Trace back – Prevent Silos
‘Single point of truth’All data have to pass this layer on it’s path from the source to the summarized edw-managed data marts
Controlled Extraction and Data Staging (transformation, cleansing)
Data are extracted only once and deployed manyMerging data that are commonly used together
Flexibility, Reusability, CompletenessThe data are not manipulated to please specific project scopes (unflavored)Coverage of unexpected ad hoc requirements (Support the Unknown)The data are not aggregatedOld versions are not overwritten or changed but useful information may be added
IntegrationData are integrated (as far as possible)Realization of the corporate data integration strategy
...
The BW Data Warehouse Layer is the corporate memory, thecorporate information repository
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 22
Introducing the BW Data Warehouse Layer
Business Logic
Web templates,ReportsQueries
Data MartsData Marts(InfoCubes) (InfoCubes)
(E)DW Layer(E)DW Layer(ODS(ODS--Objects)Objects)
Extraction
Sources
Staging-Transformation,
Cleansing
Project Team(E)D
WA
dmin Team
1
1
1 1
1
1
2
2
Business Logic
Set upIncremental set up in parallelwith data marts guarantees buy in from business users
TechnologyBW ODS-ObjectsExpanded InfoSources define ODS-Object structures BW flexible staging for Master Data
OwnershipCorporate Guidelines must be defined and administrators must be establishedto achieve the goals of a Data Warehouse layer
1 Increment
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 23
BW and Operational Decision-Making
SAP Business Information Warehouse andthe Corporate Information Factory (CIF)*
Open
Dis
tribu
tion
StagingStagingAreaArea
CleansingCleansingTransformTransform
MasterReference
Data
Data Data WarehouseWarehouse
OperationalOperationalDataDataStoreStore
PrimaryPrimaryData Data
ManagementManagement
Extr
acti
on /
Ope
n St
agin
gDataData
AcquisitionAcquisitionData Data
DeliverDeliver
any
sour
ce TransactionData
ArchitectedArchitectedData MartsData Marts
any
targ
et
Finance
Logistic
* Source: Bill Inmon
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 24
Operational, Tactical and Strategic Decision-Making in ‘Traditional’ BW Implementations
Most BW customers do not distinguish between strategic/ tactical and operational decision-making using BW features:
Precalculated aggregates of InfoCubes (aggregation awareness)‘Drill thru’
tactical/ strategicon
summarized data:Data Marts
operationalon detailed, slightlysummarized data:
Standard CollectionsInfoCube withprecalculated aggregates
Two InfoCubes with ‘Drill Thru’
ODS-Object
InfoCube and ODS-Object
with ‘Drill Thru’
BW Architected D
ata Marts
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 25
Flexibility of BW Architected Data Marts: Data Marts & Standard Collections
Focus of traditionalFocus of traditionalBW implementations:BW implementations:
support support the unknownthe unknown
support support the knownthe known
data martscenarios• InfoCubes
• summarized
tactical / strategicdecision-making
edw base tables• granular• complete history• ODS-Objects
flexibility &reliability
standard collections•detailed, slightly summarized• InfoCubes, ODS-Objects
operationaldecision-making,flexibility
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 26
Limits of Using BW the Traditional Way: Introducing BW Operational Data Stores
The traditional usage of BW (with or without dwh-layer), which supports all kinds of decision-making using Architected Data Marts has its limits
If we want to provide event-level or close to event-level operational reporting (‘near real time data warehousing’) and/ orIf we are confronted with high data volumes (e.g. Retail)
s ev eral -> ev ent l oads
G ranul arity XP SA
Sou rce G ranul arity X
DWHDWH
G ranul arity >=X
DWHOD S-Ob j ect
Data MartsData Marts
G ranul arity > XI nf oCub e
d aily-w eekly…
Dedicated ODS-Objects (or InfoCubes) with granular data support operational decision making
Directly loaded from PSA Short life cycle of data
( Archiving, Near line Storage)They build a BW Operational DataStore
G ranul arity X
I nf oCub e
OD S-Ob j ect
BW BW Operational Operational Data StoreData Store
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 27
Abstract Layer Architecture and the Reality of BW as ‚Packaged Solution‘
Focus of traditionalFocus of traditionalBW implementations:BW implementations:
support the unknown
support the known
data martscenarios• InfoCubes
• summarized
tactical / strategicdecision-making
edw (base tables)• granular• complete history• ODS-Objects
flexibility,reliability &data mining
standard collections•detailed, slightly summarized• InfoCubes, ODS-Objects
operationaldecision-making& flexibility
operational decision-making& data mining
supportlow latency &high volume
Operational Data Stores• BW ods / BW PIPE for retail• others• most granular
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 28
Content
Enterprise Wide BW Enterprise Wide BW -- BackgroundBackground
Elements of a Corporate BW StrategyElements of a Corporate BW Strategy
The BW Data Model Prevents SilosThe BW Data Model Prevents Silos
BW Data Layers Guarantee Reliability and FlexibilityBW Data Layers Guarantee Reliability and Flexibility
BW Corporate Landscape PatternsBW Corporate Landscape Patterns
Content
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 29
Enterprise Data Warehouse as ‘Single Point of Truth’
DSS Applications Departmental Data Marts
EDW
MarketingAcctg Finance
Sales ERPERP
ERP
CRM
eComm.
Bus. Int.
ETL
GlobalODS
Oper.Mart
Exploration warehouse/data mining
* Source: Bill Inmon
Stag
ing
Are
a
localODS
DialogueManager
CookieCognition
Preformatteddialogues
Cross mediaStorage Management
Near lineStorage
Web Logs
SessionAnalysis
Internet
ERPCorporate
Applications
ChangedData
GranularityManager
Archives
The Corporate Information Factory*
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 30
Basic Landscape Types
The ideal corporate BW landscape that supports all kindof decision-making needs ?
EnterpriseBW
Hub & SpokeBW Enterprise
Data Warehouse SpokeBW
SpokeBW
Others
SpokeBW
‘Local’BW
‘Local’BW
‘Local’BW
GlobalBW
Outside-INMultiple Hubs &
Global BW
Others
Select the [IT] approach that fits most closely with corporate strategy Prof. Sethi, University of Texas
Information&Management, 2/01“
There is no ‘one size fits all’ BW landscape!
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 31
Some Influencers of a Corporate BW Landscape
More and more operational, low-latency decision-making using BW
operationaldecision making
tactical/ strategic decision making
edw &edw managed
data marts
operational BW Objects
Mission critical BW applications in BW
mission criticalapplications
business criticalapplications
Local interests
central governancelocal freedom
Flexibility for time of migration and future acquisitions
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 32
Single Corporate Wide BW Instance
ParametersCompany time zones Mission critical dominates othersWorkload from operational reportingScalability
BW EDWBW EDW
BW BW Architected Data MartsArchitected Data Marts
PSAPSA
Stag
ing
Area
BW ODSBW ODSlatency: near real time
External Data MartsExternal Data Marts
• mission critical• business critical• others
Standard Standard Collections Collections
DataDataMartsMarts
• mission critical• business critical
latency: >= 1 day
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 33
Handling Mission Critical and Operative Decision-Making Separately
• mission critical• strategic
BW EDWBW EDW
BW O
DS
BW O
DS
• mission critical• strategic
BW O
DS
BW O
DS
• business critical• others
BW O
DS
BW O
DS
ParametersCompany time zones Mission critical dominatesEDWMigration path from singleInstanceEDW separated from majority of data marts
• business critical• others
BW EDWBW EDW
BW O
DS
BW O
DS
ParametersCompany time zones EDW close to majority ofdata marts
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 34
Multiple Central Managed Local BWs to Support Business Critical Scenarios
Asia Europe Americas
EDWEDWO
DS
OD
S
• business critical• others
• business critical• others
• business critical• others
• mission critical• strategic
Local BWLocal BW Local BWLocal BW Local BWLocal BW
Global BWGlobal BWParameters
ScalableMission critical dominatesEDWEDW separated frommajority of data marts
OD
SO
DS
OD
SO
DS
OD
SO
DS
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 35
Summary
BW offers a wide range of features that support enterprise wide data warehousing needs.
Nevertheless a strategy and an organizational momentum must exist to realize an enterprise wide BW strategy.
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 37
Further Information
Public Web:www.sap.com > Solutions > SAP NetWeaver
SAPNet:Use ALIAS: /BW
SAP Service Marketplace:
www.service.sap.com/bwBW InfoIndex – Data ModellingBW InfoIndex – Enterprise Data WarehousingBW InfoIndex – ODS FunctionsEDW Whitepaper :
http://service.sap.com/~sapidb/011000358700003703852003E/EnterpriseDWOverviewEN.pdf
www.service.sap.com/educationPDEBW1 ‘Enterprise Wide Data Warehousing with
SAP BW’ (Workshop - 2 days)
© SAP AG 2004, Enterprise Wide BW, J. Haupt / 38
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