Why is IoT analysis relying on centralised reporting when there are better alternatives?

When it comes to enterprise software, operational efficiency trumps bells and whistles every time. Why then, when it comes to optimising those applications, particularly for the Internet of Things (IoT) are enterprises trying to boil the ocean? A recent GlobalData survey of 1,000 IoT professionals revealed a heavy reliance on hardcore business intelligence software. Forty percent of those surveyed ranked business intelligence platforms well above all other means of analysing data. More broadly throughout companies, major do-it-all business intelligence software platforms have already given way to numerous smaller, more discrete ways of deriving value from enterprise data, be that a direct SQL query, a predictive data modeller, an auto-generated data discovery visualisation, or a live, interactive executive dashboard. The reasons for this are simple: business intelligence software is reactionary and static. Its users rely heavily upon basic reporting mechanisms that, in turn, rely heavily upon laborious queries and reports – a very costly venture to both build and maintain. This reluctance to follow the broader market away from business intelligence platforms within IoT is concerning, given a subtle shift noted in the same survey concerning when, during its lifecycle, an IoT deployment fails. In 2016, no failures were noted post…


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