2241 extending the reach of lsa++ using the new artifacts from release 7.40 of the sap business...

8/19/2019 2241 Extending the Reach of LSA++ Using the New Artifacts from Release 7.40 of the SAP Business Warehouse Application

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Extending the Reach of LSA++ UsingNew SAP BW 7.40 Artifacts Pravin Gupta, TekLink International Inc.Bhanu Gupta, Molex

SESSION CODE: BI2241


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What is Enterprise Data Warehousing (EDW)?

Introduction to Layered Scalable Architecture (LSA)

Migration from LSA to LSA++

New SAP BW 7.40 Modeling and Provisioning Artifacts

Operational Data Provisioning (ODP) and Operational Data Queue (ODQ)

Open ODS View

Advance DSO Composite Provider

Automatic HANA View Generation

Actual Use Cases

Conclusion

Agenda


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Consolidate the data across the enterprise to get a consiste

agreed view on your data

"Having data is a waste of time when you can't agree on an inter

EDW requires a database + “X”

SAP BW (BW) is the “X” as EDW with BW provides a flexib

scalable EDW solution

Highly integrated tools for modeling, monitoring and managing th

Open for SAP and non-SAP systems

Why Enterprise Data Warehousing


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EDW vs. Datamarts


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LSA is the accepted approach for building EDW guaranteeing a cons

highly available and maintainable data foundation for an agreed interpBI & Reporting

Layered Scalable Architecture

Data Acquisition Layer

Quality & Harmonization Layer

Corporate

Memory

Data Propagation LayerBusiness transformation Layer

O p er a

t i on al

D a t a S

t or e

Reporting layer (Architected Data Marts)

Visualization Layer

Enterprise

Data

Warehous

e Layer

Architected

data mart

layer


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Planning Engine

Analytic Engine

Data Manager

InfoCubes

DataStore Objects

EDW Processes E n t e r p r i s e D a t a W

a r e h o u s e a n d D a t a M a r t

M o d e l i n g w i t h S A P N e t W e a v e r s B W

In Memplanning

Additiocalculatin-mem

ConsumpHANA mod

SAP HAoptimize

Cube

SAP HAoptimized D

Obje

HANA daBW sta

First calculationscenarios in BWA

Multi providerhandling and

flexible joins

BWA-onlyInfo Cubes

BWA reportingfor DSOs

Filter + aggregation

BWA instead ofaggregates

Data

Modeling

Data

Persistency atRuntime

BW 7.0

DB + BWA 7.0

BW 7.3

DB + BWA 7.2

BW 7.4

SP5on HAN

In-Memory Evolution


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LSA++ Holistic Framework

BI Streamlined: On EDW, Operational BI, Agile BI, Virtualiza


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Journey From LSA to LSA++

Migrate to Hana- Optimized objects

Streamline EDW Core

Enhance Virtualization Layer

Introduce additional layers

Open Operational Data Store

Agile Data Mart Layer

BW Workspace Layer

Resulting LSA++


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LSA

No reporting on Propagator. Result of transformations stored in additional persistent Layer, i.e. Archite

Mart.

Virtualization Layer only on top of Architected Data Mart and only UNION(Multiproviders).

LSA++

Reporting on Propagator is allowed. Consequently, necessary transformation are moved from the Business T

Layer into Query Design and are thus executed upon query execution.

Virtualization layer on top of both Architected Data Marts and PropagatorUNION (Multiproviders) and JOIN (Composite Provider).

LSA vs. LSA++


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Reducing number of persistent provider, esp. InfoCubes.

Optimized design and implementation of persistent providers.

Reducing change impact on persistent providers.

Streamline the Consistent EDW

Streamlined EDW Virt ali ation of


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Obsolete: InfoCubes as Accelerator on Business Transformation Lay

Streamlined EDW: Virtualization ofInfoCubes

A r c h i t e c t e d

D a t a M a r t

L a y e r

B

u s i n e s s

T r a n s f o r m a t i

o n L a y e r

E D W

P r o p a g a t i o n

L a y e r SalesSales Delivery Delivery

LSA & BW on RDBMS LSA++ & BW on HANA

US AP EU US AP EUUS AP EU US AP EU

US AP EU US AP EU

US AP EU

1:

1


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EDW Propagation Layer as Query Target

Streamlined EDW: Query on granu

A r c h i t e c t e d

D a t a M a r t

L a y e r

B u s i n e s s

T r a n s f o r m a t i

o n L a y e r

E D W

P r o p a g a t i o n

L a y e r

LSA & BW on RDBMS LSA++ & BW on HANA

US AP EU

US AP EU

1:

1

US AP EU


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Layers and Data Persistency


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Reporting on Cubes vs. DSO


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BW EDW Services

Open ODS Layer as source for persistent EDW providers Open ODS Layer Provider as virtual part of the EDW

BW Operational Data Services

Real time replication into BW - SLT

Immediate querying on any delivered data – no staging into EDW n(Operational BI)

Data Modeling

BW Integration Services

Transfer/Consume HANA Modeler schemas in BW and vice versa

LSA++ Open ODS Layer: Services


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Decision Criteria on Using Composite Provider

Replace Data Mart

Investigate Keep Data Mart

Investigate

no low Complex

High/same

low

Transformation / Join logic

G

r a n u l a r i t y / C a r d i n a l i t y

Goal: Virtualization of Architectured Data Mart Layer

LSA H li i F k Vi l D M Vi l W


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Virtual Data Marts increase overall LSA++ framework flexibility an

manageability.

LSA++ Holistic Framework – Virtual Data Marts: Virtual WrapCombining Data


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Data Provisioning

Operational Data Provisioning through ODQ

Data Modeling

Open ODS View

Quick Prototyping and Direct meta-data access

Toggling between Virtualization and Persistence through Direct access

PSA elimination

Field-based DSO

Composite Provider

Automatic Generation of HANA Models

Data Federation

Smart Data Access

New Artifacts with BW 7.40


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Operational Data Provisioning (OD

Enables extract once deploy

many with EOIO Quality ofService

Time stamp based recovery

mechanism with configurable

data retention periods

Highly efficient compression

(up to 90%)

Source: SAP


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Complementary to DB Connect

Direct loading of HANA views via DTP into BW infoproviders (PSA op

ODP – HANA Context

O D P

/ O D Q

BW non BW schema

analytic view

calculation view

attribute view DTP B W

D a t a

S o

u r c e


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ODP – Extractor Context

Keeping rolling data window for re

Direct loading into BW infoproviders (PSA optional)

Scheduled or real-time daemon (Auto change notification)

Synchronous RFC instead of ALE/IDOC

Flexible Recovery

Multiple Subscribers

NW ABAP

WebAS

field-based

DSO

ODP

ODQ

DTP

DataSource / Extractors

NW

BW

BW DataSource

DTP

O Q i O Q O S


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ODQ Monitor (t/c ODQMON vs. RSA

O ODS Vi


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Open ODS View

Table

ERP / BW / HANA / anyDB* Source System

Table

Virtual Access Persistent Staging

Query Query

BW onHANA

Open ODS Layer

Field based DSO

BW on

HANA

Open ODS View

Table / View

ODP DataSource

Operational Delta Queue

(ODQ), SLT, SAPI

DTP w/o PSA

DataSource

DB/Virtual Table

Open ODS Layer

Open ODS View

SAPI, DB Connect, SDA

O ODS Vi S & O i


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Open ODS View – Summary & Opti

BW 74 SP 8 / SP9


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BW 74 - SP 8 / SP9


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C it P id


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Single BW artifact to combine data from otherHANA based applications on the same instance

of HANA (consumption of native HANA modelsor tables) with data in BW

Faster Implementations

More flexibility – Unions and Joins

Easier consumption of data

HANA optimized query runtimes

Modern Eclipse based UI

Option to include Inventory key figures

Possibility to include in planning scenarios

Composite Provider

A t ti HANA Vi G ti


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Automatic HANA View GenerationInfo cube Info objects

DSO

Query

Composite Provider

U C S /POS D t I t ti


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Use Case: Scan/POS Data Integration

NielsenQuofore / DWH

Customer Master Data

P Store No - Account.StoreChainNo

P Banner – Account.Primarygroup_ID

Store Name – Account.AccountName

Territory ID - Territory.Territory_IDTerritory NameRegion – Customer Level 1

Zone – Customer Level 2

State – Address.State_ID

P Sector Name – Sector Name

Product Master Data

P EAN – Unit EAN Code

Category – Product.ProductCategory_ID

Pack Group – Product.BrandSub_IDProduct Name -Product Name

SKU – SKUCode

Sector Name – Sector Name

Activity Transaction Data

P Activity Name – Survey.SurveyName

P Store No - Account.StoreChainNo

Display Type - ???????????

Location - ????????????

Store Scan Data

P Store No - STORECODE

P EAN – ITEMCODE

Sales Units – SALESUNITS

Price - PRICEWeek End Date – MBDCODE (Firs

Activity Master Data Spre

Activity Master Spreadsheet – H

P Activity Name

Banner

Start Date

End Date

Activity Master Spreadsheet

Activity Sub-Group Code

Store No

Target W1-12

Scan Data Reporting

Data Sources Relationship

Diagram

Activity Master Spreadsheet – Ac Activity Sub-Group Name

Activity Sub-Group Code

EAN 1-40

P = Primary Key

Conclusion


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SAP BW 7.40 SP8+ provides many new artifa

Quickly consume external data in a direct or lightwpersistent manner.

Combine and integrate such external data with exmodels using union and join operations that are Hoptimized

Provide a new robust provider/subscriber framewodata provisioning with reduced latency and persistdirect access

Conclusion

THANK YOU FOR PARTICIPAT


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THANK YOU FOR PARTICIPAT

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2241 extending the reach of lsa++ using the new artifacts from release 7.40 of the sap business...

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