Hans-J Lenz

Manfred Jeusfeld

Martin Staudt

Panos Vassiliadis

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Report on the 5th International Workshop on the Design and 
Management of Data Warehouses (DMDW’03) 
Hans-J. Lenz1, Panos Vassiliadis2, Manfred Jeusfeld3, Martin Staudt4  
1 Freie Univ. Berlin, Germany, hjlenz@wiwiss.fu-berlin.de 
2 Univ. of Ioannina, Greece, pvassil@cs.uoi.gr 
3 Tilburg Univ., The Netherlands, Manfred.Jeusfeld@kub.nl 
4 Univ. of Applied Sciences Solothurn, Switzerland, martin.staudt@fhso.ch 
 
1 Introduction 
This article reports on the 5th International Workshop 
on Design and Management of Data Warehouses 
(DMDW) held in conjunction with VLDB’03 in 
Berlin, Germany, on September 8th, 2003. A short 
summary on the papers and the discussions held 
during the workshop is given. 
 
Data Warehousing embraces technology and 
industrial practice to systematically integrate data 
from multiple distributed data sources and to use that 
data in annotated and aggregated form to support 
business decision-making and enterprise 
management. Although many database techniques 
have been revisited or newly developed in the 
context of data warehouses, such as view 
maintenance and OLAP, little attention has been paid 
to the design, management and high quality service 
of the management of a given enterprise. Little 
attention is also paid to aspects that are intrinsic to 
the functionality and usage of data warehouses, either 
in the back-stage (like data cleansing or data 
extraction and loading) or in the front-end (like 
similar and uncertain queries, or what-if analysis). 
The DMDW workshop is intended as a forum to fill 
this gap. 
 
This year’s main theme for DMDW was “Business 
Intelligence for Data Warehouses: Functionality, 
Usability and Quality of Service”. In response to the 
call for papers, 21 papers were submitted. The 
Program Committee selected 9 papers based on their 
scientific contribution, novelty and relevance to the 
workshop. In a popular research topic, DMDW 
included three papers on the problem of data 
warehouse design. A second area of interest for this 
year’s workshop included novel technologies and 
best practices, possibly showing a movement of data 
warehousing research towards novel technological 
challenges, like for example, XML, grid computing 
and spatial data warehouses. Finally, following a 
tradition of keeping DMDW close to practitioner 
problems, three experience reports were also 
accepted for this year’s workshop. 
Apart from the DBLP server, the electronic edition 
of these proceedings is also available from the CEUR 
series:   
http://CEUR-WS.org/Vol-77 
 
2 Data Warehouse Design 
Data warehouse design is a reoccurring theme to 
DMDW and appears to be one of the most popular 
fields for data warehouse research so far. Having 
matured from the era where data warehouse design 
was considered simply a selection of materialized 
views, the topics of this year’s DMDW on data 
warehouse design involve methodologies, correctness 
criteria and semi-automated support to the DW 
designer. 
The paper by S. Luján-Mora and J. Trujillo, 
entitled “A Comprehensive Method for Data 
Warehouse Design” presents a UML-based 
framework for the full span of DW design. The 
different phases and artifacts of a DW design process 
are identified and supported by the usage of UML. 
To this end, the authors start by identifying different 
kinds of important schemata for data warehouse 
design. Then, for each phase of the DW design the 
authors present different stereotypes for different 
uses. Packages are used to abstract schemata and 
their details are revealed through zoom out 
operations. 
In his paper entitled “Well-formed data warehouse 
structures”, M. Schneider models a DW as a graph 
with nodes being fact and dimension tables and edges 
representing the dependency relationships among the 
different nodes of the graph. Once the architecture of 
the graph has been established, constraints for the 
well-formedness of the graph are given. Furthermore, 
a mapping to relational structures is also given, both 
for star and snowflake schemata. 
Finally, the paper “Using Design Guidelines to 
SIGMOD Record, Vol. 32, No. 4, December 2003                                                                           113
 
Improve Data Warehouse Logical Design” by V. 
Peralta and R. Ruggia discusses how to automate the 
design process, taking into account performance 
requirements, in the context of mapping from the 
conceptual to logical structures. The goal of the paper 
is to formalize implementation-related information 
and then use this information in the form of 
guidelines for the production of the logical DW 
schema. Three types of guidelines are discussed in 
this paper: vertical fragmentation of dimensions, 
horizontal fragmentation of facts and aggregate 
materialization. 
 
3 Best Practices and Novel Techniques 
The two papers on novel approaches in data 
warehousing discuss the usage of XML in the 
integration of data to support OLAP queries and the 
issues around the architecture and usage of a spatial 
DW system. A discussion of best practices around 
the design, usage and deployment of a DW was also 
included in this session. 
The paper “Applying Grid Technologies to XML 
Based OLAP Cube Construction” by T. Niemi, M. 
Niinimäki, J. Nummenmaa and P. Thanisch discusses 
handling problems due to the huge volume of OLAP 
databases and the updates of data. The authors have 
developed a system for OLAP data collection from 
distributed XML sources. Whereas the user defines 
the information that he/she needs over a global 
schema, a “collection server” acts as a mediator and 
assigns local servers to do the job. XML is employed 
for describing the global schema fragmentation and 
representing the OLAP data, practically, as a 
selection – group by query. Grid techniques are 
applied for the security layer and the distribution of 
Java code. 
In another line of research, H. Bâazaoui Zghal, S. 
Faïz and H. Ben Ghézala authored the paper entitled 
“CASME: A CASE Tool for Spatial Data Marts 
Design and Generation”. The paper is focused on 
spatial decision support. A metamodel is presented, 
classifying data in spatial objects (location of a road) 
and non-spatial objects (name of a road).  Moreover, 
the paper describes user applications, the architecture 
of a tool that has been implemented and provides a 
set of steps for the design of a spatial DW. During 
the presentation of the paper, the validation of the 
tool through road accident databases was discussed. 
Most important, the usage of spatial DW’s was also 
highlighted: spatial data mining and spatial OLAP 
are employed to support queries which deviate from 
the traditional OLAP queries in the context of 
alphanumeric information (e.g., instead of a count(*) 
query the user can start with a query of the form 
“show me the accidents on the map”). 
Finally, in a paper entitled “Best Practice for 
Implementing a Data Warehouse: A Review for 
Strategic Alignment”, R. Weir, T. Peng and J. 
Kerridge make a three-way effort to shed light on 
elements of best practice in implementing a data 
warehouse. To this end they (a) provide a review of 
existing literature, (b) discuss a successful case study 
and (c) provide a framework to rationalize on the 
success of this particular case study. In terms of the 
first part, elements of best practice are discussed and 
compared as pre-2000 vs. post-2000. It appears that 
management buy-in, training and politics are more 
significant in the literature now than before; on the 
other hand, end-user buy-in and project goals seem to 
appear less important. Then, a case study of a 
company that was in a problematic situation is 
discussed. The company implemented a data 
warehouse and from $60M losses turned to $211M 
profit in 2 years. The paper discusses the 
management framework under which the data 
warehouse was originated and exploited for this 
success.  Yet, during the discussion that followed, it 
appears that the strategy of the organization plays the 
major role in this kind of success and the IT is still 
just one of the means to support it. 
 
4 Experience Reports 
DMDW nurtures a tradition of bringing academia 
close to practical problems. This year’s DMDW, in a 
very interesting session, hosted a performance tuning 
paper from IBM, a paper from Oracle discussing the 
incorporation of MOLAP functionality in the 
ROLAP server of Oracle and an experience report 
from Telecom Italia discussing their back-end ETL 
system. 
In a paper by M. Nicola and H. Rizvi, entitled 
“Storage Layout and I/O Performance in Data 
Warehouses” the problem of data placement on disks 
in DW’s is discussed and a comparison of storage 
layouts for data warehouses is performed. The 
authors, both coming from IBM, try to confront the 
DBA’s problem of optimizing I/O performance. The 
problem is typically translated to decisions such as 
how to spread data on disks or how to perform 
striping. Current solutions involve tricks like placing 
tables and indexes/logs/temporary space on different 
disks. Still, no practical systematical solution is 
offered, mainly due to the fact that research starts 
with the unrealistic assumption that a workload on 
which to place the design can be identified. 
Unfortunately, practical experience suggests that 
workloads are not always available, and if they are, 
they change too often. The paper reports two 
114                                                                               SIGMOD Record, Vol. 32, No. 4, December 2003
 
experiments: (a) on 1 TB TPC-H data over a cluster 
of 32 machines, where all data were uniformly 
distributed across the nodes and (b) experiments on a 
50GB star Schema, over an SMP system with 22 
disks. The findings of the paper suggest that (a) high 
I/O throughput is more important than seek times or 
I/O contention; (b) striping everything across all 
disks with a large to medium stripe size and a 
significant number of disks dedicated to fact tables is 
a performance winner (better than separating indexes 
from tables) as well as the easiest way to administer 
the DW. 
While the previous paper tackled the DW physical 
design and administration process, the support of the 
querying process from another vendor is discussed in 
the paper by M. Bastien, entitled “Accessing 
multidimensional Data Types in Oracle 9i Release 
2”. Oracle has incorporated the MOLAP Express 
Server in its relational engine and the paper discusses 
how an object-relational interface can be created, so 
that SQL queries can be dispatched to the MOLAP 
engine for processing. Two types of ADT’s are 
required to handle queries: one for cube rows and 
another to form tables out of these rows. The 
multidimensional structures are wrapped through a 
‘table’ function and potentially a view (to make the 
interface pure relational) before they are accessed 
through SQL queries. An extra feature of the 
discussed architecture is that the pre-aggregation of 
all possible cubes is not required in this environment. 
Finally, J. Adzic and V. Fiore in their paper “Data 
Warehouse Population Platform” discuss an ETL 
platform and a case study for Telecom Italia. The 
DW Population Platform (DWPP) is a general 
platform, comprising a set of libraries for common 
ETL tasks. The architecture of the system is 
discussed in the paper, with particular interest in (a) a 
“shared data area”, which is an in-memory area for 
data transformations, with a specialized area for rapid 
access to lookup tables and (b) the pipelining of the 
ETL processes in DWPP. A case study for mobile 
network traffic data is also discussed, involving 
around 30 data flows, 10 sources, and around 2TB of 
data, with 3 billion rows. The throughput of the 
population system is 80M rows/hour, 100M 
rows/day, exploiting low level OCI calls, in order to 
avoid storing data to files and then loading them 
through loading tools. With 4 hours of loading 
window for all this workload, the main issues 
identified involve (a) performance, (b) recovery, (c) 
day by day maintenance of ETL activities and (d) 
adaptable and flexible activities. The discussion 
revealed two main problems, specifically (a) the 
choice of partitions as the main design problem and 
(b) the need for practically real time DW, with 2 hour 
data freshness, due to user requirements! 
 
5 Keynote 
Data warehousing is mature enough an area to be 
able to host keynote speeches in its dedicated 
workshops and conferences. DMDW could not be an 
exception; this year we had the opportunity to enjoy a 
keynote speech by Prof. Stefano Rizzi from the Univ. 
of Bologna, with title “Open problems in data 
warehousing: eight years later”. 
Stefano began by surveying landmarks in the field 
of data warehousing both as a practical but mostly as 
a research area (actually, the “eight years later” part 
of the title refers to the seminal paper of J. Widom in 
CIKM’95). 
In terms of the relationship between research and 
practice, the following table summarizes Stefano’s 
assessment of the situation as of today. 
 
 
Tool 
implementation 
User 
satisfactio
n 
architectures  ☺ 
conceptual 
modeling   
OLAP ☺ ☺ 
query lang. and 
processing   
optimization and 
tuning   
physical aspects, 
indexing ☺ ☺ 
 
Stefano gave a list of open issues for different 
stakeholders in the data warehouse environment 
(which are not necessarily research topics, though). 
In a nutshell, these issues involve: 
- Methodologies for DW design and data 
integration 
- Project documentation 
- Metadata standards 
- Data quality assessment 
- DW evolution 
Stefano proceeded in presenting some results in the 
fields of DW evolution and project documentation 
and concluded with three promising research 
problems: 
- Federations of XML warehouses under P2P 
environments. 
- Optimization and processing for complex nested 
aggregation queries. 
- Maintenance in highly dynamical environments. 
Following the talk, a discussion took place, mainly 
SIGMOD Record, Vol. 32, No. 4, December 2003                                                                           115
 
on the future of data warehousing research. Apart 
from the topics raised by Stefano, other areas of 
research were also suggested, like data warehousing 
for multimedia content and real-time data 
warehousing (where the back-stage cannot afford the 
luxury of daily refreshment and has to sustain 
refreshment rates in terms of minutes or hours). The 
agonizing question on whether data warehousing as a 
research area has any future at all was also raised and 
there was a rather wide agreement that without any 
drastic breakthrough the area will eventually freeze, 
even if the practical problems are not yet solved. 
 
6 Summary 
It would not be unrealistic to say that this year’s 
DMDW closes a cycle of five years of interesting 
data warehousing research. After five years, DW 
design is the only topic that consistently remains in 
the issues of the workshop; on the other hand, 
traditional topics like materialized view selection, 
indexing, aggregate query processing, metadata 
management and conceptual modeling seem to 
disappear, not only from the final program but also 
from the submissions too. However, this does not 
mean that these problems have found satisfactory 
solutions in practice. The delay between taking over 
proposed (in part even standardized) solutions by the 
DW technology vendors seems to be rather 
increasing. 
While it is clear that the field of data warehousing 
as a research area is going through a crisis, seeking 
for new topics, we cannot summarize without a tone 
of optimism: indeed, novel research areas can be 
identified, including: 
- the handling of non-traditional content, like 
spatial or multimedia information;  
- the need of addressing real-time requirements, 
i.e., moving the focus from pure DW’s for 
decision support to general purpose (integrated) 
Operational Data Stores, where many aspects are 
similar but additional technology must be 
provided; 
- advanced data warehouse architectures like P2P 
data warehousing, and  
- the management of the dynamically evolving 
nature of DW’s.  
Of course, traditional areas like data integration 
and query processing and optimization will possibly 
continue to offer research topics from the viewpoint 
of data warehousing. Naturally, it is up to the 
research community, whether to embark on these 
challenges or follow different directions. 
 
7 Acknowledgments 
On behalf of the Program Committee we would like 
to thank all the authors of submitted papers and all 
the referees for their careful work. The support of 
Freie Universität Berlin, Oracle Deutschland GmbH 
and Sunsite Central Europe (CEUR) is also gratefully 
acknowledged. We would like to express our 
gratitude to the members of the Organizing 
Committee of VLDB’03 for their support in 
organizing this workshop. Finally, we would also 
like to thank Avigdor Gal for detailed comments over 
a previous version of this report. 
 
116                                                                               SIGMOD Record, Vol. 32, No. 4, December 2003


Report on the 5 th International Workshop on the Design and Management of Data Warehouses (DMDW&apos;03)

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