Data analytics in a changing environment


New challenges (such as the General Data Protection Regulation) and opportunities (such as the third Data Package) are entering the data analytics scene. Further initiatives are also appearing on the horizon.

At this daWos session, we will discuss how to position data analytics in this changing environment.

Questions that could be addressed include

  • Are data analytics products sufficiently mature to warrant an investment by the NSIs?
  • What will be the impact of algorithmic decision-making and how will NSIs be communicating about it, e.g. to comply with the requirement for transparency, accountability and traceability? How to ensure humans are still involved in the decision-making process?
  • What is the impact of the General Data Protection Regulation[1] and the third Data Package[2] on the availability of data for statistical and research purposes? For instance, is there a risk of unintended consequences of the third Data Package, because greater availability of other data will increase the disclosure risk of statistical microdata, which may make the data owners ask for additional protection?
  • What is the impact of the third Data Package on computational models and processing approaches? In particular, what are the challenges foreseen when handling non accessible data from private owners? 
  • Beyond the question of the data themselves, are there any ethical/legal issues actually preventing the adoption of data analytics in production? Should/could the ESS, or Eurostat, facilitate the actual adoption?
  • Big data, smart statistics, smart cities, internet of things: how do the buzzwords further come into the picture?
  • In acknowledging the potential of data analytics, what are the transformations needed for statistical institutes to adopt new roles/capabilities: where are we now ("as-is") and where would we like to go (to-be)?
  • Any other foreseen future trends/developments on a mid-longer term, and how they might affect other systems?