Karen Corral

Seven key interventions for data warehouse success

The success of data warehouses depends on the interaction of technology and social context. We present new insights into the implementation process and interventions that can lead to success.

Comparing the understandability of alternative data warehouse schemas: An empirical study

An easily understood data warehouse model enables users to better identify and retrieve its data. It also makes it easier for users to suggest changes to its structure and content. Through an exploratory, empirical study, we compared the understandability of the star and traditional relational schemas. The results of our experiment contradict previous findings and show schema type did not lead to significant performance differences for a content identification task. Further, the relational schema actually led to slightly better results for a schema augmentation task. We discuss the implications of these findings for data warehouse design and future research.

Database Schema Design for a Web Services Supply Chain Manager: Requirements and Proposed Infrastructure

Web services enable the commoditization of computer code components for distributed system execution in cross-organizational platforms via the Internet. At any point in time, the state of a set of composite applications and the web services they are consuming constitutes an instance of a new type of dynamic software supply chain. Proper management of what we refer to as this “web services supply chain” requires seamlessly integrated and automated B2B relationships with responsibilities for procurement, performance monitoring, benchmarking, cost allocation and ongoing relationship maintenance requiring new hybrid organizational infrastructure constructs. To cope with the increased complexity of managing this dynamic supply chain, we elaborate requirements and propose an exemplar database schema design with web-scripts as a means for pre-specifying and monitoring organizationally approved patterns of web service invocations. The database research challenges associated with long-running transactions are discussed in our schema design, including reflections of the realities associated with web-script failure, variable quality-of-service (QoS) levels, the share-ability of web-scripts between organizational business processes, the need for continuous updating of web-scripts by agents (human or automated), and the scalability of designs to accommodate evolutionary change.

Strategies for Document Management

Keyword search has failed to adequately meet the needs of enterprise users. This is largely due to the size of document stores, the distribution of word frequencies, and the indeterminate nature of languages. The authors argue a different approach needs to be taken, and draw on the successes of dimensional data modeling and subject indexing to propose a solution. They test our solution by performing search queries on a large research database. By incorporating readily available subject indexes into the search process, they obtain order of magnitude improvements in the performance of search queries. Their performance measure is the ratio of the number of documents returned without using subject indexes to the number of documents returned when subject indexes are used. The authors explain why the observed tenfold improvement in search performance on our research database can be expected to occur for searches on a wide variety of enterprise document stores.

Architecting a Dimensional Document Warehouse

This paper examines how the concepts of dimensional data warehouses can be applied to document retrieval and storage. It then shows how the specifics of dimensional document warehouses differ from dimensional data warehouse and how these differences make it impractical to use existing engines for building and analyzing data cubes (such as SQL servers analysis manager) in order to build and analyze a document warehouse. The paper further shows that readily available software can be used to build an engine to analyze a dimensional document mart. All of the steps required to design, build, and analyze a dimensional document mart are described and illustrated. Design features are suggested for improving the recall and precision of searches from dimensional document marts

Enabling self-service BI: A methodology and a case study for a model management warehouse

The promise of Self-Service Business Intelligence (BI) is its ability to give business users access to selection, analysis, and reporting tools without requiring intervention from IT. This is essential if BI is to maximize its contribution by radically transforming how people make decisions. However, while some progress has been made through tools such as SAS Enterprise Miner, IBM SPSS Modeler, and RapidMiner, analytical modeling remains firmly in the domain of IT departments and data scientists. The development of tools that mitigate the need for modeling expertise remains the “missing link” in self-service BI, but prior attempts at developing modeling languages for non-technical audiences have not been widely implemented. By introducing a structured methodology for model formulation specifically designed for practitioners, this paper fills the unmet need to bring model-building to a mainstream business audience. The paper also shows how to build a dimensional Model Management Warehouse that supports the proposed methodology, and demonstrates the viability of this approach by applying it to a problem faced by the Division of Fiscal and Actuarial Services of the US Department of Labor. The paper concludes by outlining several areas for future research.

The benefits and costs of using metadata to improve enterprise document search

The literature shows that there are many problems with enterprise document search. Studies reveal that typical knowledge workers spend between 10% and 20% of their time searching for documents they never find. While many argue that metadata can improve enterprise document search, in reality few organizations use metadata. This represents a missed opportunity. This article describes the results of two experiments that use simulation to evaluate the actual impact of metadata on the costs and benefits of enterprise search. The first study provides quantitative evidence of the increase in recall and precision that stems from the use of metadata-enhanced document searches. The second study demonstrates that simple metadata structures can be nearly as effective as complex ones, implying that the cost of creating and maintaining metadata is likely to be lower than generally thought. This is the first study to provide explicit quantitative evidence of the gains that can be achieved from the use of metadata, and one of only a handful of studies that examines the cost of creating and maintaining metadata