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Customer Use Case: Efficiently Maximizing Retail Value Across Distributed Data Warehouse Systems Klaus-Peter Sauer Technical Lead SAP CoE EMEA at Teradata
Customer Use Case: Efficiently Maximizing Retail Value Across
Distributed Data Warehouse Systems
Klaus-Peter Sauer Technical Lead SAP CoE EMEA at Teradata
Summary 5
The Implementation 4
Why HEMA choose Teradata 3
Teradata Overview 2
HEMA Company Background 1
Agenda
2
A new store in the Netherlands in 1926
3
Facts
Brand awareness in the Netherlands 100%
4.4 million customers per week
Daily number of visitors on www.hema.nl: 50.000
HEMA sells a sausage every 3 seconds
(10 million a year)
One out of three Dutch boys wears
HEMA underwear
One out of five Dutch women
wears HEMA bra
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Distinguished style
This is one of our strongest USP’s
Together with low price and high quality
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Formats
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High traffic XL
HEMA
international
AA / D
6
Hema.nl
7 7
Summary 5
The Implementation 4
Why HEMA choose Teradata 3
Teradata Overview 2
HEMA Company Background 1
Agenda
8
Teradata – Company Overview
Teradata Corporation
Founded in 1979 > Independent since Oct 2007 > S&P 500 Member, listed NYSE (TDC)
2010 Revenue: $1,936M
8,000 Associates in 70 countries
Global Leader in Enterprise Data Warehousing > First TB+PB DWH on Teradata > Database Technology, Analytic Solutions, Consulting Services
Since 1999 #1 Position in “Gartner’s Leader’s Quadrant in Data Warehousing”
Teradata Key Offerings Teradata DBMS Teradata MPP Platform
The Magic Quadrant is copyrighted January 2011 by Gartner, Inc. and is reused with permission. The Magic Quadrant is a graphical representation of a marketplace at and for a specific time period. It depicts Gartner's analysis of how certain vendors measure against criteria for that marketplace, as defined by Gartner. Gartner does not endorse any vendor, product or service depicted in the Magic Quadrant, and does not advise technology users to select only those vendors placed in the "Leaders" quadrant. The Magic Quadrant is intended solely as a research tool, and is not meant to be a specific guide to action. Gartner
disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
2011 Magic Quadrant Data Warehouse DBMS
Teradata SAP Partnership Overview
Business Objects Partner since 1995
320+ joint customers globally, across industries
Teradata Advisory Group
Business Objects is included in both BI and Data Integration portfolios
SAP NetWeaver Partner since 2004
Teradata is committed to the SAP NetWeaver platform to provide better, seamless integration between SAP applications and Teradata.
Teradata certified SAP NetWeaver Interfaces.
Teradata SAP integration development lab in San Diego.
Teradata CoE SAP to support the field organizations.
Teradata SAP Integration Lab EMEA in Prague.
Teradata Office at SAP Partner Port Building in Walldorf.
Partner Port Building in Walldorf
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SAP NW Integration Products
Teradata Extract and Load Solution > Use Open Hub to load data from BW to Teradata
> Easy extraction of SAP data into Teradata environment N
ov 2
00
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Teradata Supply Chain Accelerator > Use Teradata to power SAP Demand Planning Solution
> Faster, more frequent planning cycles using greater detail and history J
un
20
07
Teradata JMS Universal Connector > Teradata Active Data Warehouse for SAP
> Message-Bus Integration with SAP NetWeaver PI
Jan
20
08
Teradata Virtual Access for SAP > Using Virtual Info Cubes to access data held in Teradata
> Easily combine SAP and non-SAP data in BW queries O
ct
20
05
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Summary 5
The Implementation 4
Why HEMA choose Teradata 3
Teradata Overview 2
HEMA Company Background 1
Agenda
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HEMA Expansion
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We became Holland’s favorite and we still are!
1926 2 stores 1940 24 stores 1970 95 stores
1985 193 stores 1995 242 stores 2011 +550 stores
in the Netherlands, Belgium, Germany, France, Luxembourg
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Expansion is key to HEMA …
Consequence
New formats do not always fit in the current model
Local influences (store level) become more important
Conclusion: new Supply Chain model is required:
Demand driven
Based upon local influences
Management by Exception
Teradata selected to support HEMA strategy:
DCM application
SAP BW integration
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…but that puts pressure on HEMA supply chain
Challenges
Demand Chain Management
New Demand Chain (DCM) application on Teradata chosen as foundation of HEMA’s new Supply Chain model
Analysis did show, that most of the data needed to feed the DCM application already stored in SAP BW
Potential Data duplication issue raised
SAP Business Warehouse
Fast data SAP BW volume growth expected
Query performance issue with SAP BW on Oracle perceived
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Strategy and Project Rules
Leverage the Teradata DCM investment also to
solve SAP BW (Oracle) performance issue
Avoid data redundancy - “Single version of the
truth”
Data scope: Sales and Stock subject area
(~50% of SAP BW data)
(Re-)Use current SAP BW ETL / Reporting
Keep or improve query performance
Performance test halfway the project!
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Summary 5
The Implementation 4
Why HEMA choose Teradata 3
Teradata Overview 2
HEMA Company Background 1
Agenda
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SAP BW at HEMA
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sizing
2,5TB+ data at this moment
150+ InfoCubes
1000+ report queries
used tools
BEX (Web) Analyzer
BEX Report Designer
BEX Broadcasting
usage
About 500 HQ users +
Distribution Center Users
All shops in all countries(550+)
Monday morning peak
data
Sales (per day-article-plant)
No receipts
Stock (article-week-shop)
Remote cube to R/3 (actual stock)
Article movements
Financial data (pca, cca, sl)
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Implementation in a nutshell
1. Teradata infrastructure implementation and set up
2. Integration Teradata and SAP BW: – Data flows from SAP BW to Teradata via SAP OpenHub
and Teradata TELS
– Queries get data out of Teradata via Teradata TVAS
3. Implementation Teradata DCM on top of Teradata DW
SHS (SAP HEMA Store)
SAP BW
Teradata DW
DCM
Daily replenishment
order proposals
Stock / Sales /
Master Data SAP Retail (ECC 6.0) TVAS
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Teradata Virtual Access Solution
TVAS allows SAP BW End-users to run reports against data which is physically stored in Teradata only.
TVAS avoids data duplication and ETL implementation.
TVAS gives SAP BW End-users high performance access to detailed data in Teradata.
TVAS key functionality is a Teradata specific SQL generator.
TVAS runs on SAP NetWeaver Java Application Server and supports multiple BW instances including SAP Java load balancing.
TVAS supports multiple Teradata systems and Teradata query banding.
Reduced Cost Improved Performance Increased Business Value by
more fresh and detailed data
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TVAS Use Cases
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Illustrative
HEMA Solution Architecture
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Teradata Complements SAP BW Illustrative
Step 1: Simplify the Data Model
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Illustrative Basic Design Idea – Store once, use many!
Step 2: Initial Data Load
• Load historical info available from 2006
– Sales Data
– Stock Data
– Master Data
• Method:
– Export from SAP BW to a Flat File
– Import in Teradata with Loader
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Step 3: Data Mapping
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SAP BW Virtual Provider to Teradata (TVAS GUI)
Step 4: Daily ETL
Embedded in existing HEMA/CapGemini environment, use of: – BMC Control-M scheduling
ETL – Export : via SAP BW export via Open Hub
– Load: via Teradata Load Solution (TELS) and FTP/Teradata loader: load SAP BW data in Teradata Staging Area
– Transform: via Teradata SQL: update Data model
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BW & Teradata in Production
Results & Findings
Query performance improved significantly
Users do not complain (so much) anymore
Very stable environment
New queries developed to combine SAP and DCM data
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Group Previous response time Current timings
(average)
A < 10 sec 2x faster
B 10 < > 60 sec 2x faster
C 60 < > 300 sec 10x faster
D > 300 sec 24x faster
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Summary 5
The Implementation 4
Why HEMA choose Teradata 3
Teradata Overview 2
HEMA Company Background 1
Agenda
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Implementation Summary
No difference for BW End-User
Substantial performance improvement
Store once, use many
Simplified Data Model and structures
Implementation with a small team in 4 months
Cost savings on storage & maintenance
Compare before and after
– More users and more usage
– More historical data on the system
– More data requested in the reports
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Looking forward
Special reporting
Special Head office users only
Detailed data
Data supply to BW for non SAP data
Teradata
POS Data
Web Data
Commodity reporting
Large group of users: Stores and Head office
Aggregated data
Data hub to Teradata
SAP BW
SAP Merchandise and Assortment Planning
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Teradata role for HEMA is changing…
Contact
Klaus-Peter Sauer Technical Lead SAP Program Europe – Middle East – Africa Teradata GmbH Altrottstr. 31 69190 Walldorf / Germany Tel: +49 (0) 6227 / 733 511 Mobile: +49 (0) 172 / 8238 665 Fax: +49 (0) 89 / 3221 1974 [email protected] Teradata.com
