Faceted Search in Business Intelligence on the Cloud

Faceted search is a new concept in search engines for implementing a feature of direct search queries using guided navigation among the search results. In this concept, the search results are grouped and ranked under facets that guide a user on the dimensions through which the search results can be viewed. It has been implemented on web based query systems by integrating with semantic search engines (like Google, Yahoo and Bing). However, there is a significant opportunity of implementing faceted search in business intelligence (BI) frameworks to include direct searching features through BI dashboards and custom reporting interfaces. In this paper, a technology positioning map for implementing faceted search in BI framework on cloud computing has been presented. BI on the cloud is based on massively parallel processing of hardware and database resources and an XML based service oriented architecture in which the data warehouses and OLAP cubes are formed using XML data files. The architecture has been expanded to include a DOM parser and a DTD mapping system that will parse the 2D XML views (pulled from cubes formed by many-to-many XML files) and extract the database fields to be stored in a facet repository as per pre-established metadata rules. Whenever an OLAP query is invoked by a user (using a decision map), a query coordinator will fetch the relevant 2D OLAP views and group them under facets fetched from the facet repository taking the services of a metadata coordinator. The user can make use of the facets to create direct queries, generate the targeted dashboards, and hence reduce searching time.