On Firehoses, Windows, and Business Rules: Towards a Successful Fast Data Organisation

Due to the enormous growth of data and the increasing speed at which organisations are required to respond to it, Fast data is the latest trend in data science. In this study, we set out to answer the question what Fast data is and how organisations can deal with it in a successful way. We define Fast data as: the ability to gain insights from (near) real-time data streams and derive value from these insights. We argue that successful Fast data organisations are built on four pillars: (i) technology, (ii) strategy, (iii) culture, and (iv) skills & experience. We conclude with a critical discussion of our results, for instance touching upon whether Fast data is really ‘new’

Formal Modelling of Complex Event Processing and its Application to a Manufacturing Line

Identifying the significant and most needed information in huge enterprises at the right time not only helps in decision making, but also plays an important role in overall performance and profit making of enterprises. Complex Event Processing (CEP) is a developing method of processing different events from multiple sources and filtering them to produce complex events. This thesis provides a methodology to model CEP using Timed Net Condition Event System (TNCES), a Petri Nets derived formalism. Petri Nets is a graphical, mathematical modelling language used to analyze and describe discrete-event dynamic systems. The biggest advantage of representing CEP in TNCES is that it opens paths to the validation of the events filtering and decision making in different level of enterprise. /Kir1