3_HANA_Modeling

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Information Modeler
Quick Launch View Navigator View
Properties View
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Navigator View - Information Models
Information Models organized in Packages
Is a HANA-specific functional script language
Think of a ‘SELECT FROM HANA’ as a data flow You can move functions into that data flow in order to Enrich data (e.g. Add columns for calculated measures on the fly) JOIN or UNION two or more data flows Include complex logic such as ‘CASE’ statements
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Navigator View - Default Catalog
HANA Instance (<USER>)
HANA Server Name and Instance Number User Database schema Schema Content: Column Views, Functions, Tables, Views
Set ‘Default Client’ to the client used in customer system Leave ‘Default Language’ on preset value (‘dynamic’)
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Modeling for HANA 1.0
Data Preview
Physical tables Information Models
Import/Export
Models Data Source schemas (metadata) – mass and selective load Landscapes
Data Provisioning for SAP Business Applications (both initial load and replication) Analytic Privileges / Security
Properties View
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Perspectives are built up based on views
Choose perspective from main menu
Fast Perspective Switch
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© 2011 SAP AG. All rights reserved.
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Modeling for HANA 1.0
Using In-Memory Computing Studio (II) Idea 3: If simple joins are not sufficient use SQL Script
VIEWS!
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Tips & Tricks
RESET PERSPECTIVE will restore your screen!
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Levels of modeling
Leveled – based on multiple attributes Parent-child hierarchy
Analytic Privilege – security object
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Features
SAP in-memory computing studio: Information Modeler Features Modeling
SAP HANA – Modeling
Bernd Ecker – In-Memory Platform Sebastian Baumgärtner – Technology CoE BW/BI/In-Memory June 2011
© 2011 SAP AG. All rights reserved.
© 2011 SAP AG. All rights reserved.
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Agenda
HANA 1.0 Modeling Look and feel – In-Memory Computing Studio Levels of modeling
– Attribute views – Analytic views – Calculation views
Attribute views Analytic views Calculation views
Set Information Modeler Preferences
Select Windows Preferences Information Modeler Default Model Parameters Allows setting of default values for information models created by user
Attribute Views, Analytic Views, Calculation Views, Analytic Privileges organised in folders
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Perspectives are built up based on views
No materialized aggregates Database Views Choice to publish and consume at 4 levels of modeling
Attribute View, Analytic View, Analytic View enhanced with Attribute View, Calculation View
Views
Analytic Views – i.e. cubes Attribute Views – i.e. dimensions Calculation Views – similar to virtual provider with services concept in BW
Hierarchies
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In-Memory Computing Studio
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Administration View
Navigator View
Cheat Sheets
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Demo
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Terminology
SAP in-memory computing studio: Information Modeler Data
Attributes – descriptive data (known as Characteristics SAP BW terminology) Measures – data that can be quantified and calculated (known as key figures in SAP BW)
Idea 2: create ‚Cube-like‘ view by joining attributes view to ‚Fact data‘
Build a ‘Data Foundation’ based on transactional table Selection of ‘Measures’ (key figures) ... ... and attributes (docking points for joining attribute views) this is basically your ‘fact table’ (key figures and dimension IDs) Join attribute views to data foundation Looks a bit like a star schema
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Disclaimer
This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent.