Wolfgang Hümmer

XCube: XML for data warehouses

Data warehouse systems are nowadays a well known and widely spread approach for supporting management decisions. In several companies or even across companies the idea of integrating several data warehouses into a virtual or federated data warehouse is of growing interest. But the technical and semantic problems are very demanding. An essential part for solving this problem is a standardized, vendor independent format for describing multidimensional data. This paper introduces XCube, a family of XML based document templates to exchange data warehouse data, i. e. data cubes, over any kind of network. XCube is organized in a modular fashion, so the multidimensional schema, the descriptions of the single dimensions and the fact data itself can be transmitted in separate steps. In addition to the describing formats XCube also offers two kinds of dynamic document types that can be used to explore the (multidimensional) content of another warehouse in a vendor independent way. They are primarily meant to reduce the amount of data transferred over the network.

An Alternative Relational OLAP Modeling Approach

Schema design is one of the fundamentals in database theory and practice as well. In this paper, we discuss the problem of locally valid dimensional attributes in a classification hierarchy of a typical OLAP scenario. In a first step, we show that the traditional star and snowflake schema approach is not feasible in this very natural case of a hierarchy. Therefore, we sketch two alternative modeling approaches resulting in practical solutions and a seamless extension of the traditional star and snowflake schema approach: In a pure relational approach, we replace each dimension table of a star / snowflake schema by a set of views directly reflecting the classification hierarchy. The second approach takes advantage of the object-relational extensions. Using object-relational techniques in the context for the relational representation of a multidimensional OLAP scenario is a novel approach and promises a clean and smooth schema design.

A Decathlon in Multidimensional Modeling: Open Issues and Some Solutions

The concept of multidimensional modeling has proven extremely successful in the area of Online Analytical Processing (OLAP) as one of many applications running on top of a data warehouse installation. Although many different modeling techniques expressed in extended multidimensional data models were proposed in the recent past, we feel that many hot issues are not properly reflected. In this paper we address ten common problems reaching from defects within dimensional structures over multidimensional structures to new analytical requirements and more.

Data logistics as a means of integration in healthcare applications

Information integration is still a crucial issue in healthcare applications. Most clinical applications are determined by a huge variety of heterogeneous and independent work places, most of them equipped with specialized clinical hardware. Due to this it is almost impossible -- at least not feasible -- to run a common database system storing all relevant data of a clinical application. Nevertheless these clinical applications have to share their data. Our solution to this integration problem is to facilitate so called Process based Data Logistics. This approach is based on the integration capabilities of process management; however it does not coordinate the staff working in the healthcare domain in a restricting sense, but coordinates data sources and data sinks of these applications.

Query optimization by using derivability in a data warehouse environment

Materialized summary tables and cached query results are frequently used for the optimization of aggregate queries in a data warehouse. Query rewriting techniques are incorporated into database systems to use those materialized views and thus avoid the access of the possibly huge raw data. A rewriting is only possible if the query is derivable from these views. Several approaches can be found in the literature to check the derivability and find query rewritings. The specific application scenario of a data warehouse with its multidimensional perspective allows the consideration of much more semantic information, e.g. structural dependencies within the dimension hierarchies and different characteristics of measures. The motivation of this article is to use this information to present conditions for derivability in a large number of relevant cases which go beyond previous approaches.

Contracting in the days of eBusiness

Putting electronic business on a sound foundation --- model theoretically as well as technologically --- has to be seen as a central challenge for research as well as for commercial development. This paper concentrates on the discovery and the negotiation phase of concluding an agreement based on a contract. We present a methodology how to come seamlessly from a many-to-many relationship in the discovery phase to a one-to-one relationship in the contract negotiation phase. Making the content of the contracts persistent is achieved by reconstructing contract templates by means of mereologic (logic of the whole-part relation). Possibly nested sub-structures of the contract template are taken as a basis for negotiation in a dialogical way. For the negotiation itself the contract templates are extended by implications (logical) and sequences (topical).

Processing reporting function views in a data warehouse environment

Reporting functions reflect a novel technique to formulate sequence-oriented queries in SQL. They extend the classical way of grouping and applying aggregation functions by additionally providing a column-based ordering, partitioning, and windowing mechanism. The application area of reporting functions ranges from simple ranking queries (TOP(n)-analyses) over cumulative (Year-To-Date-analyses) to sliding window queries. We discuss the problem of deriving reporting function queries from materialized reporting function views, which is one of the most important issues in efficiently processing queries in a data warehouse environment. Two different derivation algorithms, including their relational mappings are introduced and compared in a test scenario.

Adaptive Präaggregation in multidimensionalen Datenbanksystemen

Das Konzept des ‘Online Analytical Processing’ umfast die interaktive Analyse multidimensionaler Daten. Die dabei zu verarbeitenden Datenmengen sind in der Regel sehr gros. Deshalb mussen geeignete Optimierungsverfahren fur die Gewahrleistung der Interaktivitat eingesetzt werden. Das durch die multidimensionalen Datenstrukturen gefuhrte Benutzerverhalten im Anwendungsfeld OLAP bildet die Grundlage fur das in diesem Beitrag vorgestellte redundanzbasierte Optimierungsverfahren. Die Grundidee dieses adaptiven Verfahrens besteht darin, bereits berechnete Ergebnisse und Teilergebnisse in einem reservierten Speicherbereich fester Grose zu puffem, um neue Anfrageergebnisse daraus abzuleiten. Notwendig fur einen solchen multidimensionalen Aggregatpuffer ist zum einen ein Algorithmus, um konstruktiv die Ableitbarkeit eines Aggregates aus einer Menge anderer Aggregate zu bestimmen. Zum anderen wird eine geeignete Verdrangungsstrategie benotigt, welche die Informationen uber das multidimensionale Schema und uber das Zugriffsverhalten moglichst gut ausnutzt. Der Beitrag erlautert die verwendeten Techniken und zeigt das Potential des Ansatzes anhand von Simulationsstudien auf.

Nutzung von Datenbankdiensten in Data-Warehouse-Anwendungen (Connecting Data Warehouse Applications with Database Services)

Zusammenfassung Zentral für eine effiziente Analyse der in Data-Warehouse-Systemen gespeicherten Daten ist das Zusammenspiel zwischen Anwendung und Datenbanksystem. Der vorliegende Artikel klassifiziert und diskutiert unterschiedliche Wege, Data-Warehouse-Anwendungen mit dem Datenbanksystem zu koppeln, um komplexe OLAP-Szenarien zur Berechnung dem Datenbankdienst zu überlassen. Dabei werden vier unterschiedliche Kategorien, die Spracherweiterung (SQL), die anwendungsspezifische Sprachneuentwicklung (MDX), die Nutzung spezifischer Objektmodelle (JOLAP) und schließlich der Rückgriff auf XML-basierte WebServices (XCube) im einzelnen diskutiert und vergleichend gegenübergestellt.

On the problem of generating common predecessors

Using common subexpressions to speed up a set of queries is a well known and long studied problem. However, due to the isolation requirement, operating a database in the classic transactional way does not offer many applications to exploit the benefits of simultaneously computing a set of queries. In the opposite, many applications can be identified in the context of data warehousing, e. g. optimizing the incremental maintenance process of multiple dependent materialized views or the generation of application specific data marts. In the paper we discuss the problem whether it is always advisable to generate the most complete common predecessor for a given set of queries or to restrict a predecessor to a subset of all possible base tables. As we will see, this question cannot be answered without having knowledge about the cardinality of queries after aggregation. However, if we can rely on this information, we can come up with an optimal predecessor for a common set of queries.