It is specific information about facts, elements, etc., which allows them to be studied and analyzed, so their collection, knowledge and study allow informed decisions to be made regarding many aspects of the business, thus increasing the efficiency of economic activity . Interesting, isn't it?
Data governance
This operation consists of the capacity to organize and exploit the founder email lists information that is collected about economic activity . For example, a drone manufacturing company collects information about the evolution of the needs of its clients, but also about the efficiency of its production chain and its workers. Knowing all this data favors decision-making regarding changes in the technology used or in the workforce.
An innovative and very relevant contribution that has been incorporated into data governance is privacy by design . This contribution consists of establishing data protection already incorporated in the design of technological programs. This new tool can be used thanks to the analysis of collected data. The processing of this information helps to ensure that data protection is preventive, proactive and provides comprehensive security, from the beginning and from end to end, unlike the current type of protection, which is rather corrective and reactive. This new addition helps data governance to be not only more automated, but also more secure and respectful of privacy.
Data in the energy sector
In the case of the energy sector, being one of the sectors of the future par excellence, much is expected of its evolution and it is hoped that it will establish itself as one of the pioneering sectors in innovation and sustainability. To achieve these goals, the collection, administration and use of information will be key when it comes to directing this improvement.
The objective of data governance in this case is to ensure that all functions related to information management are carried out in the most efficient way, complying with what is planned. Data governance, therefore, encompasses the entire data processing process, from beginning to end, and, in short, tries to ensure that the data meets the demands of the sector.. This activity can also automatically detect faults in energy networks, which would take much longer to be detected if the analysis of possible defects were carried out completely manually.
