1302 - BusinessObjects with HANA - Best Practices.pdf

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© 2011 SAP AG. All rights reserved. 1

SAP HANA 1.0

Best PracticesSAP BusinessObjects 4.0




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

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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.




Agenda

General Modeling Principles

Restricted Measures vs Logical Partitioning

Calculated Attributes - Row vs Sets

Calculation Before Aggregation

Calculation Views - SQL vs Calculation Engine Functions

Join Types and Referential Integrity

Do’s and Don’ts with SBO Explorer

Importance of Drill Functionality in SBO WebIntelligence





Column

Store

Analytical

Views

Attribute

Views

Calculation Views

Client / Application

A B C D

A B C D G Y

A G Y

A G Y Z

Filter data amount as early as possible in the lower layers(CONSTRAINTS, WHERE Clause,Analytical Privileges..)

Aggregate data records (e.g usingGROUP BY, reducing Coulmns)

Avoid transfer data of large resultsets between the HANADB and client application

- Do calculation after aggregation.

- Avoid Complex expressions (IF, CASE, ... )

Join on Key Columns or IndexedColumns

Avoid calculations beforeaggregation on line item level

Reduce data transfer between views




Agenda












Modeling Example 1


Analytical View

• Define 3 Restricted Measures - once for each PLANT(A,B & C) within a single Analytical View

Multiple Analytical Views + 1 Calculation View• Create 3 Analytical views – one for each PLANT

• Define a design time filter (PLANT) on each Analytical View

• Create a Calculation view that reads each Analytical view

• Combine the results using Union Constants

100 200 300

PLANT A View PLANT B View PLANT C View




Agenda












Modeling Example 2


Calculation View

• Re-use the same Analytical View 3x• Define a Current Year Key filter in each Projection Node

• Combine results using Union Constants

Analytical View• Define 4 Calculated Attributes

Filter [3]

Filter [2]

Analytical View + 1 Calculation View• Create a Analytical View without any Calculated Attributes,

instead define Calculated Columns in a Calculation View

• Create a Calc. View reading from a single Analytical View

• Add one Projection Node above the Analytical View & add

Calculated Columns

• Stack 3 Projection nodes and Filter by Current Year Key

• Combine results using Union Constants

Filter [1]

Filter [1]

Filter [3]

Filter [2]

Current Year Filter

Current Year [midstr(now(),1,4)]

Previous Year [ (“current_year")-1]

Earliest Year [(“previous_year")-1]

Current Key [if(“cur"=“year",1,if(“prev"=“year",2,if(“earl"=“year",3),-1)]




Agenda












Modeling Example 3

Calculate Before Aggregation

Analytical View• Define Calculated Measure threshold

(i.e. NETWR > 99) using the Expression Editor

• Check Calculate Before Aggregation

• The result will either be 1 or 0 per row

• Use regular SUM aggregation to calculate count

based on threshold calculation

Use with caution, row based processing

significantly slower than set based processing




Agenda












Modeling Example 4

Calculation View – SQL vs CE Functions

Calculation Engine (CE) Functions• Preferred over SQL

• Improved performance, can be optimized by the engine (i.e. field pruning &

parallelized)

SQL

CE Functions

Even though only MATNR & NETWR are

requested by the front end tool all fields will be

retrieved from the table including all

calculations will be done irrespective.

Only MATNR & NETWR will be retrieved from

the database. Only NETWR will be calculated.

Columns requested by the front end tool can be

parallelized




Agenda












Join Types – Definitions and Referential Integrity

Join Type Use when you needto report on…

Be aware that…

INNER facts with matching

dimensions only

facts without any dimension will be excluded

dimensions without any fact will be excluded

JOIN is always performed

LEFT OUTERall posted facts whether there

is a matching dimension or

not

dimensions without any fact will be excluded

best for performance because JOIN is omissible

RIGHT OUTER all dimensions whether there

are matching facts or not

facts without any dimension will be excluded

JOIN is always performed

REFERENTIAL facts for the requesteddimensions

AND referential integrity is

ensured

• it is the default join type• acts as an INNER for Attributes Views

• join on attribute views is “optional”, which facts are

returned will depend on which attributes are

queried for

TEXT an SAP dimension table

joined to a text table for

translation purpose

only available for Attribute Views with SAP ERP tables

(SPRAS field) or equivalent design

acts as an INNER




Join Types - Example

Customer ( … Right table / Header / Dimension for sales)

( … Central / Left / Many table for s tate

Sales( … Fact table / Central / Left / Items / Many)

C_ID ORDER_ID AMOUNT

1 1 100

1 2 100

2 3 100

4 4 100

77 8 100

C_ID CNAME STATE AGE

1 WERNER MI 10

2 MARK MI 113 TOM TX 12

4 BOB TX 13

STATE SNAME

MI MICHIGAN

AL ALABAMA

State( … Right table / Header / Dimension fo r customer)

Notes: Order 8 does not have a customer master record

Customer TOM does not have any orders

State TX does not have a description

No customers reside in Alabama




Join Types – Referential Join in Attribute Views

C_ID CNAME STATE AGE SNAME

1 WERNER MI 10 MICHIGAN

2 MARK MI 11 MICHIGAN

SELECT

C_ID, CNAME, STATE, AGE, SNAME

C_ID CNAME AGE

1 WERNER 10

2 MARK 11

SELECT

C_ID, CNAME, AGE

*** Referential join is a feature available only in OLAP engine, when testing Attribute views outside the context of a

Analytical view then the Join Engine will perform a Inner Join. As a result TOM and BOM will not be returned.




Customer Sales2 table referential join in

Data Foundation. No

dimensions.

*** Customer table join will be omitted since onlyfields are selected from the left table

*** Since the field AGE is selected from the right

table then a inner join is preformed resulting in

order 8 not being returned.

*** Since there are no dimensions joined to C_ID

all the facts will be returned.

C_ID AMOUNT

1 200

2 100

4 100

77 100

Join Types – Referential Join in Analytic Views




Join Types – Text Join for multilingual reporting

Text Join is used when

translation for a dimension is

available

Designed for ERP table (and

typically SPRAS field)

Act as an INNER join

User language is used as a

filter at runtime to find the right

translation for that attribute




Agenda













Recommendation Description

1Only include dimensions (facets) the end user absolutely needs, 6-10

facets seem to work for most cases

2

If the end user needs more facets but response time is the priority, split the

Information Space in two spaces.

Restrict each Information Space to one or two hierarchies (navigationpaths)

3The first measure on the list should be one that leads to the easiest /

lightest calculation (among all available measures)

4aUse the "Show facets in the defined order" option when the facet order

matters to end users and select a “fast” dimension first

4bUse the "Order facets by filtering capability“ option if the facet order is not

so important, Explorer will determine the optimal order




SBO Explorer – Recommendation #1

Avoid selecting all dimensions available from the HANA view





Only include dimensions (facets) the end user absolutely needs

6-10 facets seem to work for most cases





If the end user needs more facets but response time is the priority, split theInformation Space in two spaces. Restrict each Information Space to one or two

hierarchies (navigation / drill paths).

Suggestion: present Information Spaces side by side if the user needs more hierarchies at once





The first measure on the list should be the easiest / lightest calculation




SBO Explorer – Recommendation #4a

Use the "Show facets in the defined order" option when the facet order matters toend users and select a “fast” dimension first




SBO Explorer – Recommendation #4b

use the "Order facets by filtering capability“ option if the facet order is not soimportant, Explorer will determine the optimal order




Agenda












Dril l functionality in SBO WebIntelligence

Navigate along a hierarchy defined as a navigation path in a universe

Only fetch data you need as you select a member and drill one level down

Query data on demand as opposed to everything upfront

Leads to (much) lighter reports, faster response times and better user

experience





Navigate along a hierarchy defined as a navigation path in a universe

Only fetch data you need as you select a member and drill one level down

HANA Universe (relational)





WebIntelligence

Query only the

top level of thehierarchy

As opposed to all

levels upfront





Start Drilling and navigate

along hierarchies…

Down Up

Alongside




More Info http://help.sap.com/hana

Previous Know How Webinars on SAP HANA :

http://www.sdn.sap.com/irj/scn/khnc Build ing Advanced Data Models with SAP HANA:

http://www.sdn.sap.com/irj/scn/events?rid=/library/uuid/208df7db-74bd-2e10-adac-b47ea848e5af

How to best leverage SAP BusinessObjects BI 4.0 on SAP HANA 1.0:

http://www.sdn.sap.com/irj/scn/events?rid=/library/uuid/201d220d-11cc-2e10-39bf-e6cf6d42438b

Lessons Learned from the Provimi HANA Project:

http://www.sdn.sap.com/irj/scn/events?rid=/library/uuid/30f565bb-2703-2f10-bab9-845b7a71da88 Upcoming white paper on SDN (January 2012) : “Creating a universe on SAP HANA: Best Practices”



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1302 - BusinessObjects with HANA - Best Practices.pdf