Data wrangling for big data
Speakers: Renée Miller (University of Toronto, USA); Divyakant Agarawal (University of California, USA); Chris Williams (University of Edinburgh and The Alan Turing Institute, UK); Leonid Libkin (University of Edinburgh, UK); Nikolaos Konstantinou (The University of Manchester, UK); Tim Furche and Giorgio Orsi (Meltwater, UK)
Date: 14 September 2017
Time: 12:30 – 18:00
Venue: The Alan Turing Institute
View the agenda here.
Registration is now closed.
Data wrangling is the process by which data is extracted, integrated and cleaned that enables it to be analysed.
It is often estimated that data scientists spend over half their time on data wrangling, so the development of systematic and cost-effective techniques to support wrangling seems to be a pressing need.
This workshop will include presentations, demonstrations and posters on work that relates to data wrangling, with a view to sharing best practice and emerging techniques.
The workshop is supported by the EPSRC VADA Programme Grant on Value Added Data Systems and is suitable for data scientists and computer scientists who are interested in emerging techniques for data integration and cleaning.
Open call for posters and demonstrations: if you would like to submit a poster or demonstration, please email email@example.com.