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© 2015 SAP SE or an SAP affiliate company. All rights reserved. SAP HANA Ukázka tvorby analytické aplikace Michal Marko, SAP Presales – Platform Solutions Consultant

Transcript of SAP Business Intelligence...©2015 SAP SE or an SAP affiliate company. All rights reserved. Type...

Page 1: SAP Business Intelligence...©2015 SAP SE or an SAP affiliate company. All rights reserved. Type Appliance OS SUSE Linux Enterprise Server 11.3 CPU 60cores (2x Intel Xeon E7-4880 v2,

© 2015 SAP SE or an SAP affiliate company. All rights reserved.

SAP HANAUkázka tvorby analytické aplikace

Michal Marko, SAP Presales – Platform Solutions Consultant

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© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Type

Appliance

OS

SUSE Linux Enterprise Server 11.3

CPU

60cores (2x Intel Xeon E7-4880 v2, 2x15cores per CPU)

RAM

512 GB

HDD

~6 TB (3 TB Data; 750 GB Logs; 2,5 TB Trace)

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Vstup:

Pročištěná, volně dostupné data z internetu, náhodně generována data o nákupu a reklamacích

Manuálně obohacená o dimenzionální tabulky

Scénáře

1. Prediktivní analýza

Logika kompletně v HANA studiu (SQLScript, …)

Vizualizace HANA Studio, Predictive Analytics / Lumira

2. Clustering

Algoritmus stavěný v Predictive Analytics

Vizualizace Predictive Analytics / Lumira

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HANA Studio Connection

• Eclipse Based

• Server Overview

• Health Check

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Scenář: Prediktivní analýza – Data definice

• Catalogue -> Schema

• FCT_TRANSACTION_LOG

• ~ 800 000 rows

• Dimensional tables

• Attribute Views – logical

views on the master data

from different point of

views

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Scenář: Prediktivní analýza – Data vizualizace

• Catalogue -> Schema

• FCT_TRANSACTION_LOG

• ~ 800 000 rows

• STORE_ID

• TRANSACTIONS

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Scenář: Prediktivní analýza – Analytický pohled

• Content -> SAP -> rds-

pan

• AN_FORECAST_CASHIERS

• Join facts with attribute

views

• AT_RETAIL

• Cannot join another

analytical views

• Simpler tasks and

modelling

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Scenář: Prediktivní analýza – Kalkulační pohled

• Content -> SAP -> rds-

pan

• CA_FORECAST_CASHIERS

• More complex modelling

and calculations. 1 or

more analytical or

calculation views

• Call the prediction

function SQLScript

• Triplesmooth – HANA

help

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© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Scenář: Prediktivní analýza – Vizualizace vysledku

• Content -> SAP -> rds-

pan

• CA_FORECAST_CASHIERS

• Data preview

• DateTime

• ItemsActual

• ItemsForecast

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© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Scenář: Prediktivní analýza – Vizualizace vysledku – Alternativa PAL

• Content -> SAP -> rds-

pan

• CA_FORECAST_CASHIERS

• Data preview

• DateTime

• ItemsActual

• ItemsForecast

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Scenář: Clustering – Data definice

• Catalogue -> Schema

• FCT_SALE_RETURN_ACTU

AL

• ~ 800 000 rows

• Dimensional tables

• Attribute Views – logical

views on the master data

from different point of

views

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Scenář: Clustering – Data vizualizace

• Catalogue -> Schema

• FCT_SALE_RETURN_ACTU

AL

• ~ 800 000 rows

• RETAILSTOREID

• SALESQUANTITY

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Scenář: Clustering – Analytický pohled

• Content -> SAP -> rds-

pan

• AN_SALES_ACTUAL

• Join facts with attribute

views

• AT_ITEM

• AT_RETAIL

• AT_TIME

• Cannot join another

analytical views

• Simpler tasks and

modelling

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© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Scenář: Clustering – Kalkulační pohled

• Content -> SAP -> rds-

pan

• CA_STORE_CLUSTERING_

STORE_LEVEL_V03

• More complex modelling

and calculations. 1 or

more analytical or

calculation views

• Clustering Logic will be

done in Predictive

Analytics interactively

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Scenář: Clustering – Priprava analytického flow – PAL Vizualizace

• Predictive Analytics ->

Expert mode

• CA_STORE_CLUSTERING_

STORE_LEVEL_V03

• Visualize Tab

• Gross Sales Amount

• Store Name

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Scenář: Clustering – Priprava analytického flow – PAL Predikce

• Predictive Analytics ->

Expert mode

• CA_STORE_CLUSTERING_

STORE_LEVEL_V03

• Predict Tab

• HANA K-Means, help

available on sap.com

Advanced:

Exit threshold = faster

convergence / 0.00001

Threads 10

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Scenář: Clustering – Vizualizace vysledku

• Content -> SAP -> rds-

pan

• CA_STORE_CLUSTERING_

V03

• Gross Sales

• Expenditure

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© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Thank you

Michal Marko

Presales - Platform Solutions

SAP ČR, spol. s r.o.

Budova BBC Beta

Vyskočilova 1481/4

140 00 Praha

M +420 608 636 116

E [email protected]

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© 2015 SAP SE or an SAP affiliate company. All rights reserved. 19

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