UZH-Logo

Maintenance Infos

SODA: Generating SQL for business users


Blunschi, Lukas; Jossen, Claudio; Kossmann, Donald; Mori, Magdalini; Stockinger, Kurt (2012). SODA: Generating SQL for business users. Proceedings of the VLDB Endowment, 5(10):932-943.

Abstract

The purpose of data warehouses is to enable business analysts tomake better decisions. Over the years the technology has maturedand data warehouses have become extremely successful. Asa consequence, more and more data has been added to the datawarehouses and their schemas have become increasingly complex.These systems still work great in order to generate pre-canned reports.However, with their current complexity, they tend to be apoor match for non tech-savvy business analysts who need answersto ad-hoc queries that were not anticipated.This paper describes the design, implementation, and experienceof the SODA system (Search over DAta Warehouse). SODAbridges the gap between the business needs of analysts and thetechnical complexity of current data warehouses. SODA enables aGoogle-like search experience for data warehouses by taking keywordqueries of business users and automatically generating executableSQL. The key idea is to use a graph pattern matching algorithmthat uses the metadata model of the data warehouse. Ourresults with real data from a global player in the financial servicesindustry show that SODA produces queries with high precision andrecall, and makes it much easier for business users to interactivelyexplore highly-complex data warehouses.

The purpose of data warehouses is to enable business analysts tomake better decisions. Over the years the technology has maturedand data warehouses have become extremely successful. Asa consequence, more and more data has been added to the datawarehouses and their schemas have become increasingly complex.These systems still work great in order to generate pre-canned reports.However, with their current complexity, they tend to be apoor match for non tech-savvy business analysts who need answersto ad-hoc queries that were not anticipated.This paper describes the design, implementation, and experienceof the SODA system (Search over DAta Warehouse). SODAbridges the gap between the business needs of analysts and thetechnical complexity of current data warehouses. SODA enables aGoogle-like search experience for data warehouses by taking keywordqueries of business users and automatically generating executableSQL. The key idea is to use a graph pattern matching algorithmthat uses the metadata model of the data warehouse. Ourresults with real data from a global player in the financial servicesindustry show that SODA produces queries with high precision andrecall, and makes it much easier for business users to interactivelyexplore highly-complex data warehouses.

Citations

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:2012
Deposited On:24 Jan 2013 13:31
Last Modified:05 Apr 2016 16:22
Publisher:Association for Computing Machinery
ISSN:2150-8097
Related URLs:http://www.vldb.org/pvldb/vol5.html
Other Identification Number:merlin-id:7863

Download

Full text not available from this repository.

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations