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This process of adaptation and migration can involve an investment of time that, in some cases, is around weeks or months. Therefore, many companies resort to combining cloud and on-premises solutions in a hybrid model .

Thus, they use the cloud to store and work dynamically and use local platforms for stable workloads.

Augmented analytics
In addition to analyzing data that benefits business development, augmented analytics combines the study of information with machine learning algorithms and natural language processing (NLP) to make your work much more productive.

In this way, it is possible to manage and understand the data and interact with them, as well as detect anomalous trends. In addition, machine learning algorithms, fundamental in the evolution of big data , facilitate the predictions and preventive strategies that your company may need.

This technology combines different branches of artificial intelligence such as machine learning with the aim of optimizing the interpretation of data and the possibility of developing and sharing it more quickly.

Edge Computing It is based on one objective: to optimize the use of bandwidth and response times in data transfer . This is achieved because the data is processed in a physical space as close as possible to its destination.


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