Portable In-Browser Data Cube Exploration

نویسندگان

  • Kareem El Gebaly
  • Lukasz Golab
  • Jimmy Lin
چکیده

Data cubes, which summarize data across multiple dimensions, have been a staple of On Line Analytical Processing (OLAP) for well over a decade. While users typically access data cubes through data warehouse systems or business intelligence tools, we demonstrate that data cubes can be explored effectively and efficiently inside a browser. We provide an overview of the two recent technologies that enable our portable data cube exploration approach: 1) Afterburner, an in-browser relational database management system, and 2) explanation tables, an information-theoretic technique for guided data cube exploration.

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تاریخ انتشار 2017