Water companies want insight into the possibilities of big data
Big data: experiments and research
Digital data collection in today’s society has grown spectacularly to become big data. The art is to transform big data into big information, and to convert all the still-undiscovered connections into practical, usable information.
For today’s world to become an intelligent world, which can be governed on the basis of effective, connected, real-time information, two important developments are necessary: data integration, so as to effectively link data from various systems, and real-time data analysis, so that new information can immediately be put to use. It is uncertain whether either of these developments will proceed. These two uncertainties alone already create four possible future scenarios.
big data + integration + real-time analysis = intelligent data
When investing in the future, we occasionally have to make choices now about how we want to deal with big data, even in a context great uncertainty. This also applies to water companies, whose production and distribution processes, for example, themselves generate large quantities of big data. KWR assists the companies in preparing for such choices via the water sector’s joint research programme (BTO). Thus, one of the ten trend alerts that KWR issues every year as part of the BTO Trends research, addresses how water companies can put themselves in the best possible starting position for every possible development in the future scenarios. For these companies, it is worth taking a wait-and-see attitude when it comes to making large capital investments in big data. But experimenting and staying up to date on trends is crucial, as is exploring possible alliances with other parties both within and outside the water sector. It would not be wise for water companies to leave big data exclusively in the hands of outside ICT parties; it is important that they themselves maintain a broad overview of the ICT field and thus preserve the connection with their substantive water knowledge. Experimenting with making (non-sensitive) data publicly available can shed light on the benefits of drawing on collective thinking and on the disadvantages resulting from the loss of control over data, once they are made public.
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