The digital revolution is built on data and is well underway: terms such as big data, cloud, internet of things, internet of everything, fourth industrial revolution, smart cities and data economy are no longer just words on everyone's lips, but concepts that are changing the habits of consumers and businesses. This digital transformation started with the first wave of digitalisation: the technical digitalisation of converting analogue contents and services into digital ones; resulting in the (big) data revolution. However, big data are a data management infrastructure with underlying hardware, software and architecture and should not be "taken for museum purposes" only. As such, a second wave of digitalisation is needed to enable learning from (big) data and to generate value from this (big) data revolution for businesses and society as a whole. As such, analytics - the science of "learning from data" or of "making sense out of data" - becomes the engine of the digital transformation. The biggest challenge therein is the veracity of the "data pedigree", i.e. the trustworthiness of the data, including the reliability, capability, validity and the related quality of the data. This presentation demystifies and explains these concepts and terms, illustrates the connection between data science and statistics, i.e. between the two approaches of analytics, and highlights some challenges, opportunities and principles needed to (hopefully) succeed in the digital transformation. 

Slides

Time: 15:00 - 15:30
Track:

Track 5
organised by SSS


Speaker: Diego Kuonen