Data analysis in business development
Digitalization will proliferate throughout all societal structures in the near future. The industrial internet, the internet of things and similar trends are becoming commonplace. Companies are faced with a new situation where competitors, partners and customers are already benefitting from the available data the digitalized world provides, or are moving towards doing so.
The amount of data available is far greater than what can be handled with traditional methods. The acquisition, analysis and processing of measurement data into user-friendly formats has become crucial in achieving efficiency, cost savings and competitive advantages. .
In the energy and industrial sectors data analysis has been employed, in particular, by large global companies, which have built vast systems to gather and benefit from data in their businesses. Developments in information systems, the increased availability of applications and significant decreases in the price levels of sensors, however, have markedly eased data collection for a wider range of companies. In itself, this is not sufficient. The right tools as well as technical and financial expertise are also required. It is crucial for companies to find those factors, among the vast amounts of data, that can improve cost efficiency and develop their business.
It is also vitally important to have thorough knowledge of the target’s processes. Without expertise, essential information cannot be identified. At the end of the day, you require a human expert and support activities to back up data analysis and information acquisition systems. This is often the most significant challenge for companies. Data is available, but to comprehensively benefit from it requires a big effort, which relates to the company’s resources and organization.
Elomatic’s FORMIOT service enables flexible data analysis implementation from individual device inspections all the way up to plant level systems. The comprehensive service includes data acquisition, analysis, and visualization. We place emphasis on cost efficiently implementing issues identified in data analysis such as energy savings, production efficiency measures and investments.
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