DrillBeyond: enabling business analysts to explore the web of open data

  • Authors:
  • Julian Eberius;Maik Thiele;Katrin Braunschweig;Wolfgang Lehner

  • Affiliations:
  • Technische Universität Dresden, Dresden, Germany;Technische Universität Dresden, Dresden, Germany;Technische Universität Dresden, Dresden, Germany;Technische Universität Dresden, Dresden, Germany

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2012

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Abstract

Following the Open Data trend, governments and public agencies have started making their data available on the Web and established platforms such as data.gov or data.un.org. These Open Data platforms provide a huge amount of data for various topics such as demographics, transport, finance or health in various data formats. One typical usage scenario for this kind of data is their integration into a database or data warehouse in order to apply data analytics. However, in today's business intelligence tools there is an evident lack of support for so-called situational or ad-hoc data integration. In this demonstration we will therefore present DrillBeyond, a novel database and information retrieval engine which allows users to query a local database as well as the Web of Open Data in a seamless and integrated way with standard SQL. The audience will be able to pose queries to our DrillBeyond system which will be answered partly from local data in the database and partly from datasets that originate from the Web of Data. We will show how such queries are divided into known and unknown parts and how missing attributes are mapped to open datasets. We will demonstrate the integration of the open datasets back into the DBMS in order to apply its analytical features.