Business Intelligence consists of reporting tasks aimed at the interactive and dynamic presentation of complex company data. We offer this highly sophisticated service, both via the products offered by leaders in the market that offer the most robust and dynamic platforms equipped with data integration and forecasting tools, and in concert with the most relevant development languages that allow us to create fully customized and / or open source products. Our detailed range of BI solutions allow you to use descriptive statistics techniques to impart absolute and intrinsic value from extrapolated data, through powerful indicators and dashboards, to support the entire decision-making process that drive growth.
The new frontiers of Data Science have the aim of calibrating forecasting models that are able to anticipate the behaviour of various corporate assets. Given their intrinsic purpose, Predictive Analytics techniques are highly applicable in virtually every area relating to operational activity. They allow you to extract an array of information-rich patterns and relationships from your company’s data-borne assets, not only in the field of clustering and segmentation, but also in the development of predictive models that make it possible to forecast an array of plausible outcomes of certain phenomena, in both the short and long term.
The technologies of the Big Data world have been developed to effectively address an array of issues for which the classic tools of Data Management, data analysis and model development, are not seemingly appropriate. These powerful and contemporary tools have been therefore developed to manage manifold data, both in the form of absolute quantity and in the accentuating the speed of the flow, as in the case of streaming analytics. This operating framework, for example, presents some difficulty, both from the point of view of storage, due to high costs and data ingestion, as it requires the use of ad hoc architectures, but above all it poses stimulating challenges in the development of efficacious and robust models that can be utilised on a host of non-static, but dynamic data.
Internet of Things (IoT) represents the field in which engineering meets Data Science. Through the technologies of IoT, it is possible to build networks of machines that communicate and interact with each other in real time. The collection of telemetry data, together with the analysis and development of models based on them, pose new and extensive challenges, both on the design of physical architectures and distribution of computation (Edge Analytics) and from an algorithmic point of view. All these issues find space for expression in Industry 4.0, through the component(s) of IoT.
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