|Presenter(s):||Piet Daas & Marco Puts, Statistics Netherlands|
|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.
|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.|
|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.
|Recording of the webinar||EMOSWebinar06-Recording|