SAP/HANA Financial Closing can help you ACCELERATE your financial closing cycle. Benefit from increased governance, higher user efficiency and automation, strong collaboration, and real-time insight.

1. Finance on Retail Business using SAP/HANA
1
Author: Douglas Bernardini

2. Company Profile
2
• SBF Group: Centauro & Nike Store
• 230 Stores. 04 Distriub. Centers
• 9200 employees
• USD 2.1 Billion revenue
• 35% from e-commerce
IT Highlights
• ERP: Sispac (Informix/4GL IBM based)
• 04 Tera. 1200 users
• SAP/ECC 6.0 IS retail only in finance process.
• 700GB Oracle 9g. 300 users
• WebStore: Java based solution.
• 1800 POS machines.
• E-commerce: 09 million consumer registered
• 900k active.

3. Business Case
3
Context
• Family-owned company
• 2014: Trades 35% for GP Investiments
• 2015: GP requires mature compliance process in finance closing results.
Problem
• 350MB/day generated by systems
• 350k registers (lines)/day
• Federal Tax Revenue Office requires 100% detailed data
• Legal requirements are diferent in each SKU and in each state.
• Finance closing demands machine processing.
• Data came from diferente systems in diferente formats.

4. Solution
4
Finance closing using SAP/HANA
• Analyze all transactional and analytical data in real
time: many applications and data sources
• SAP Business Objects BI solutions for insight and
analytics.
• Unified information modelling and design environment.
• Simplification of existing models, of modelling and re-
modelling.
• Reduced costs through simplifications in hardware,
maintenance and testing.
• Simplified Operations and Monitoring with the
integration of basic HANA administration capabilities
with the BW Admin Cockpit.

5. 5
Fast In-memory Database
 100x faster
 Traditional RDBMS: SQL interface, Transactional isolation
and recovery (ACID).
 Parallel Data Flow Model: calculations can be executed in
parallel with distribution across hosts.
 Last generation Data Storage:
 Columnar and Row-Based
 Near to eliminate of indexes.
 High Data compression
 Automatic recovery: From memory errors without system
reboot.
 Native tools: Predictive Analysis Library & Analytical and
Special Interfaces
What is SAP/HANA?
Response (Msec)

6.  Starting Point: SAP Landscape consists of
SAP ERP running on a relational database,
connected to a OLAP engine (e.g. SAP BI)
and perhaps using Business Intelligence
Accelerator like BOBJ
Analytics
SAP/BOBJ
OLTP
SAP/ECC
ETL
OLAP
SAP/BW
SAP/Hana Implementation Strategy
 Introducing HANA in parallel: Install and
run the In-Memory engine (HANA) in
TOGETHER with traditional SAP instances
 02 BW extractors running at same time and
exporting same data
 Key factor: Real data performance
processing COMPARISON
Analytics
SAP/BOBJ
SAP/HANA
2nd ETL
Analytics
SAP/BOBJ
OLTP
SAP/ECC
ETL
OLAP
SAP/BW
Additional Layer

7. 7
How SAP/HANA works?
Hana
RDBMS
Column Database: Columnar storage increases the amount of data that can be
stored in limited memory (compared to disk)
Column databases enable easier
parallelization of queries
Row buffer fast transactional
processing

8. 8
How SAP/HANA works?
Dictionary Compression: Efficient compression methods (dictionary, run length, cluster, prefix, etc.)

9. 9
How SAP/HANA works?
Parallelization:
• Concurrent users
• Concurrent operations within a query
• Data partitioning, on one host
or distributed to multiple hosts
• Horizontal and vertical
parallelization of a single query
operation, using multiple
cores / threads
quant.
150
60
100
45
75
84
96
162
45
366
sales
$1000
$900
$600
$800
$500
$750
$600
$600
$1100
$450
$2000
type
43
12
12
33
33
12
32
43
12
33
core
3
core
4
core
1
core
2

10. 10
How SAP/HANA works?
Persistence Layer:

11. • Scale Out Landscape
• N servers in one cluster
• Each server hosts a name and index server
• One server hosts a statistics server
• Scale Out Capabilities
• Large tables distributed across servers
• Queries can be executed across servers
• Distributed transaction safety
• Maximum Scale Out
• Up to 56x1TB certified configuration
• HW vendors certify larger configurations
32/40 cores 512 GB
32/40 cores 512 GB
32/40 cores 512 GB
32/40 cores 512 GB
32/40 cores 512 GB
= 1 Supercomputer
Server 1
Server 2
Server 3
Server 4
Server 5
192/240 cores 3 TB
6 standard servers
32/40 cores 512 GBServer 6
11
SAP HANA: Scale Out

12. 12
• Tables can be partitioned, and distributed across multiple hosts
• Huge tables; cross machine parallelization
• Hash, Range, Round Robin Partitioning
• All HANA hosts act as SQL servers; distributed execution
• Planned for multi-tenant deployments (future)
Product Group Color
10 A red
20 B blue
30 A green
40 A red
50 C red
60 A red
Host 1
Host 2
Product Group Color
10 1 3
30 1 2
40 1 3
60 1 3
Product Group Color
20 2 1
50 3 3
Select * from table
where Group = “A”
Select * from table
where Color = “red”
12
SAP HANA: Data Partitioning

13. • High Availability configuration
•N active servers in one cluster
•M standby server(s) in one cluster
•Shared file system for all servers
• Services
•Name and index server on all nodes
•Statistics server (only on active servers)
• Failover
•Server X fails
•Server N+1 reads indexes from shared
storage and connects to logical
connection of server X
Server 1
Server 2
Server 3
Server 4
Server 5
Server 6
Cold Standby Server
SharedStorage
13
13
SAP HANA: High Availability

14. Typical Hana Upgrade Project
14
• No Blue print
• 100% technical
• Custom Code
• Hard functional test
Main Objective:
Preserve current
funcionalities

15. Project Schedule: 12 weeks
15

16. Testing Protocol
16
• Testing is commonly the largest area of effort in an implementation project.
• Testing requirements:
• How well the test scripts are defined prior to testing, whether testing is automated or has to be done manually
• Approval requirements and practices of organization
• Key factors that influence the time required for testing and the number or type of testing periods.

17. Risks
17
• Pool and Cluster Tables:
• The size of these tables influences the
time required for converting the tables
into transparent tables.
• Level of Customization:
• The number of custom objects influences
both the SAP ERP enhancement package
update and the effort needed to
recognize the full benefit of the SAP
HANA database because custom objects
need to be evaluated for code
optimization. For more information and
detailed guidance, see Custom Code
Migration and Optimization linked in the
information section..
• Current System Release and Versions:
• The current application release may require
an enhancement package upgrade, which
may introduce additional steps including
regression testing. There may also be
upgrades needed for integrated systems or
add-ons.
• Project Team Expertise:
• The SAP HANA skills and experience of key
project team members impact the project
schedule and efficiency of completing many
tasks. Also, the general experience of the
team related to the specific application that
has to be upgraded or to implementation
projects in general is very important.

18. douglas.bernardini@d2-data.com
Questions?
18