=Paper= {{Paper |id=Vol-2105/10000002 |storemode=property |title=None |pdfUrl=https://ceur-ws.org/Vol-2105/10000002.pdf |volume=Vol-2105 }} ==None== https://ceur-ws.org/Vol-2105/10000002.pdf
       Unlocking Value from Ubiquitous Data

                               Rajendra Akerkar
            1
                Western Norway Research Institute, Sogndal, Norway
                            rak@vestforsk.no



Abstract. Data is growing at an alarming rate. This growth is spurred by varied
array of sources, such as embedded sensors, social media sites, video cameras,
the quantified-self and the internet-of-things. This is changing our reliance on
data for making decisions, or data analytics, from being mostly carried out by
an individual and in limited settings to taking place while on-the-move and in
the field of action. Unlocking value from data directs that it must be assessed
from multiple dimensions. Data's value can be primarily classified as “informa-
tion,” “knowledge” or “wisdom”. Data analytics addresses such matters as what
and why, as well as what will and what should be done. In recent days, data
analytics is moving from being reserved for domain experts to becoming neces-
sary for the end-user. However, data availability is both a pertinent issue and a
great opportunity for global businesses. In effect, data ubiquity is helping manu-
facturers, retailers, mobility sector and logistics firms, for example, foster an in-
tegrated decision-making environment supporting real-time, information-based
business networks. New IT architectures enabled by big data, internet-of-things,
cloud computing, and other technologies are helping optimize a business envi-
ronment with common real-time data, workflow, and alerting capabilities.
Business success will be centered around the timely and effective analysis of
the large-scale data sets generated by business and sensor networks and the
ways in which organizational insights are used to assess and affect potential
impacts and risks to their business. This talk will present recent examples from
work in our research team on ubiquitous data analytics and open up to a discus-
sion on key questions relating methodologies, tools and frameworks to improve
ubiquitous data team effectiveness as well as the potential goals for a ubiquitous
data process methodology. Finally, we give an outlook on the future of data
analytics, suggesting a few research topics, applications, opportunities and chal-
lenges.

Keywords: Big data, analytics, ubiquitous, internet-of-things, supply chain,
business, mobility sector.