| Presenter(s): | Piet Daas & Marco Puts, Statistics Netherlands |
| e-mail(s): | pjh.daas@cbs.nl, m.puts@cbs.nl |
| Date: | 21 March 2018 |
| EMOS learning outcome addressed | Statistical methods |
| Webinar aims | The webinar aims to show statisticians how to deal with big data in real world statistical applications. |
| Webinar learning outcomes | To be aware of the need for a paradigm shift when using big data. To be familiar with methods that enable extraction of information from big data in a reliable way. To understand the importance of the need for good quality data and well thought of checks and controls. |
Webinar content | In the webinar, the current state of art of using big data for official statistics is discussed. These are illustrated by walking through a big data based production process. The observations are generalised to other big data based applications. |
| Difficulty level | Advanced |
| Prerequisites for the webinar | The webinar will build on the content presented in: 2017 EMOS Webinars: Big Data I and II |
| Further readings and resources | Daas, P.J.H., Puts, M.J.H. (2014). Big data as a Source of Statistical Information. The Survey Statistician 69, 22-31. Singh, D., Reddy, C.K. (2014). A survey on platforms for big data analytics. Journal of Big Data, 1-8. Daas, P.J.H., Puts, M.J., Buelens, B., van den Hurk, P.A.M. (2015). Big Data and Official Statistics. Journal of Official Statistics 31(2), 249-262. Daas, P.J.H., Burger, J., Quan, L., ten Bosch, O., Puts, M. (2016). Profiling of Twitter Users: a big data selectivity study. Discussion paper 201606, Statistics Netherlands, The Hague/Heerlen, The Netherlands. Puts, M., Daas, P., de Waal, T. (2017). Finding Errors in Big Data. In: The Best Writing on Mathematics 2016, Princeton, USA. (Pitici, M., ed.), pp. 291-299, Princeton University Press, USA. |
| Presentation material | EMOSWebinar06_Big_data |
| Recording of the webinar | EMOSWebinar06-Recording |