Best practices reporting on hana

Best Practices for Universe Modeling and Web

Intelligence Reporting Against SAP HANA

Romaric Sokhan, Vishal Dhir – CSA October 31, 2012

© 2012 SAP AG. All rights reserved. 2

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Agenda

SAP HANA Overview

SAP HANA and SAP BI4

BI4 Universes with SAP HANA

Web Intelligence with SAP HANA

Demo

Key Takeaways

More Information

SAP HANA Overview


SAP HANA in a nutshell

SAP HANA is a super-fast in-memory database and platform enabling

new possibilities in terms of analytical reporting and real-time data

acquisition and consumption.

• Real-time Analytical reporting : HANA is designed for on-line analysis. It

can calculate and execute millions of data at sub-second speed.

• Real-time data acquisition : HANA is shipped with ETL and replication

tools that brings loads data from operational systems to HANA in near

real-time

• Real-time consumption: HANA solves the issue of maintaining

aggregate tables for performance. You don’t need aggregate tables

anymore.


SAP HANA Pushing calculations down to the database layer

Avoid movement of detailed data

MOVE calculations into HANA

Only transfer RESULTS

APPLICATION

LAYER

Calculation

DATABASE

LAYER Calculation

Classic Approach

HANA Approach


HANA models

• Today HANA is consumed mostly by BI4 client tools using SQL interfaces, directly or via Universes (Semantic Layer)

• The modeling of HANA models can done in an authoring tool called “HANA Studio” where you will be able to design an Analytic View or a Calculation View.

• The most performing and optimal way to consume data in HANA is by using Analytic / Calculation Views.

Analytical Cubes (ROLAP) - Recommended

• Facts spread amongst several tables

• More complex joins

• Available for reporting like other RDBMS

Classical Models

SAP HANA and SAP BI4


HANA Connectivity

Web

Intelligence

Dashboards

Exce

l

Crystal Reports

for Enterprise

Semantic Layer (universe UNX)

SQL

ODBO

An

aly

sis

Off

ice

v1

.1

BICS

ODBC

Exp

lore

r

JDBC JDBC ODBC

CR

2

01

1

JDBC ODBC

SQL SQL

Are part of SBO BI 4

SQL SQL

CR

2

00

8

JDBC ODBC

SAP HANA

Outside or as part of SBO BI 4

Outside of SBO BI 4


The Semantic Layer in the BI Architecture

10

Semantic Layer Data Sources

Query and Analysis

Dashboards and

Visualizations

Reporting

Connectivity

Universe

Information

engine

Data Foundation Business Layer


HANA and the Semantic Layer

Web

Intelligence

Dashboards

Crystal Reports

for Enterprise

Semantic Layer (universe UNX)

JDBC ODBC

SQL

Are part of SBO BI 4

SAP HANA

© 2012 SAP AG. All rights reserved. 12 Public

HANA and the Semantic Layer

Support of HANA by the Semantic Layer via Relational Universes

New BI4 Universe format (UNX) via a JDBC or ODBC relational connection

Access to Tables (row or column store) and SQL views

Access to Analytic and Calculation Views

New SQL features in HANA are immediately available for universes

Universes do not store data from HANA or add any performance overhead

Universes are just a translation layer

Universes are just like any other client tool using SQL to access HANA

The latest data from HANA is sent to the client tool on query refresh

BI4 Universes with SAP HANA


Business answers can be spread over several HANA views

HANA Analytic / Calculation Views

Where can I find the answer to my business question?



HANA Analytic / Calculation Views

What is the actual revenues of my product for this year?

What are the planned profits for this product for the next year?



What do I want to do

Product

Time

Planned

Product

Time

Actual

Geography

Time

Planned

Geography

Product

Actual

Time

Actual

• I can choose any object that will help to answer my business question

• I don’t know the content of each view and I can mix objects that are not common to the selected views

• I can specify which view(s) I want to use

• I can filter my query

• I can see the result in a single table/chart whenever possible

• I can create as many queries as I want


What is I need one or more HANA views to answer my business questions?

Product

Time

Planned

Product

Time

Actual

Geography

Time

Planned

Geography

Product

Actual

Time

Planned

Calculation view Universe Federated Universe

Answer to

multiple

business

questions


No impact on

HANA

performance


Solution: Use Universes with HANA views for flexible reporting

Leverage the Semantic Layer for flexible ad-hoc query

Access multiple HANA Views and synchronize the datasets locally without impacting performance.

Use advanced Universe features like contexts, aggregate awareness to navigate through HANA views seamlessly

Create your Navigation Paths to enable drill-down analytical reporting in Information Design Tool

Benefits

Answer to multiple business questions from the same Universe federating multiple HANA views

Optimize how users ad-hoc queries are sent to HANA

No joins between HANA Views = No impact on performance


How to write a performing universe on SAP HANA?

Fine tune the connection options for best performance

Default Array Fetch Size changed to 1000

Make sure that query synchronization is performed in HANA and not in the

client tool

The Join_by_SQL data

foundation parameter will

force a single query to the

server with COALESCE


HANA Variables and Input Parameters

HANA variables

Are used to filter the content of an information model. They

don’t impact the execution workflow of the information model and

are applied to a query to filter out some values

Applied to the where clause

Input Parameters

Are used to manipulate the execution of the information model

In SQL, parameters values are passed via the PLACEHOLDER reserved word


Contexts in IDT

Contexts

Defines the path between tables

Is a set of joins

In HANA, it’s used to send different SQL to each view

Sales View Inventory View


Aggregate Awareness in IDT

Steps involved in using Aggregate Awareness

Define the aggregate aware object

Define objects that are incompatible with that object


Index Awareness in IDT

Helps create more efficient SQL

The universe can substitute IDs for descriptions

Primary and foreign keys must be programmed and must be done for every object to be made

“index aware”

Which is faster?

Without Index Awareness With Index Awareness


Hierarchies in IDT

Hierarchies defined in HANA are not accessible in IDT. However, you can create a hierarchy using IDT

An example of a time hierarchy is

Year > Quarter > Month > Week

Prompting “Equal To” vs “In List”

“Equal To” allows only the lowest level to be selected

“In List” allows multiple levels to be selected

Demo

Web Intelligence with SAP HANA


SAP Web Intelligence

Web Intelligence is an interactive reporting tool that can access relational as well as

multidimensional datasources via the concept of Universes. The reports can be viewed

online or offline thanks to the microcube, an embedded local in-memory cache engine

(microcube). In case of Hana, WebI will access it through relational access using SQL,

• Enables off-line (microcube) as well as interactive analysis

(e.g,HANA)

• Access to heterogeneous data sources

• Basic dashboarding capabilities (Drill, CVOM charts, dynamic

filters)

• Advanced Reporting capabilities (Desktop Rich Client, DHTML,

Mobile)


SAP Web Intelligence with SAP HANA

Recommendations

• Avoid querying high volume of detailed data

• Push calculations down to HANA

• Retrieve only the results the Webi report needs (Summary data)

• Create reports on summary data with refresh on open

• Let your users explore the data using drill actions in real-time


SAP Web Intelligence with SAP HANA : Benefits

Benefits

With traditional databases, when huge volume of data needs to be queried, aggregate tables might need to be created

to overcome performance degradations, not with SAP HANA

Another inconvenient is that you might wait for the next ETL load to have up-to-date data.

Thanks to SAP HANA in-memory engine and replication capabilities, the data is aggregated on-the-fly in real-time and

the user gets “live” data every time he/she accesses or drills into the report.


SAP Web Intelligence - Microcube

Why Web Intelligence is using a microcube / local cube?

The micro cube is mandatory and an important part of the Webi architecture design. Having a microcube

has a lot advantages when designing and consuming a Web Intelligence reports, and it has been designed

for a vast majority of databases. The main benefit is that it can offer offline analytical capabilities like report

viewing, drilling, quick filtering, local calculations:

The WebI calculation compensates missing data source expressiveness (cross table, multi-context

evaluation, advanced functions like Previous, …) . It requires to fetch raw data first before performing local

data processing

It enables Multi-data Provider support, which requires local data materialization for data synchronization

It enables data historization (if not available from the data source) which allows users to create data

snapshots, and make features like Track Data Change possible.

Demo


Key Takeaways

Leverage the Semantic Layer for flexible ad-hoc query

Access multiple HANA Views and synchronize the datasets locally.

Use advanced Universe features like contexts and aggregate awareness to navigate through HANA views seamlessly

Create your Navigation Paths to enable drill-down analytical reporting

Use index awareness

Don’t

Join HANA views in the data foundation

Optimize your Web Intelligence reports for HANA

Make sure your report is HANA optimized by “stripping” your query. Push calculations down to HANA and retrieve only

the results.

Enable drill workflows to make the most of with SAP HANA performance.


More Information

SAP Public Web

Frequently Asked Question: WebIntelligence on HANA

Best Practices: WebIntelligence on HANA

Creating a universe on SAP HANA: Best Practices

SAP Education and Certification Opportunities

www.sap.com/education

Watch SAP TechEd Online

www.sapteched.com/online

http://scn.sap.com/community/businessobjects-web-intelligence/blog/2012/07/23/faq--sap-bi4-webintelligence-on-hana










http://scn.sap.com/docs/DOC-30614







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http://www.sap.com/education

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Thank You!

Romaric Sokhan – [email protected]

Vishal Dhir – [email protected]

SAP Customer Solution Adoption

mailto:[email protected]

mailto:[email protected]


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