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How cloud computing will reform data science

Cloud computing is definitely on the rise. The most up-to-date companies now use the cloud as a technical solution for organizing and storing their files. With these trends, the cloud is becoming a resource for innovation once again. Many universities, vendors, institutes and government organizations are investing in research around the topic of cloud computing nowadays.

Cloud is the foundation of data science, as accessing the data for research is a crucial part of proper data science methods. With proper handling, the cloud can bring unstructured data to life, as it can be designed for data scientists to combine their data with services that customize and develop solutions for special industries and challenges.

Easily accessible and structured data often provides relatively little value. The information that can give the most insight is usually owned by the customer and is quite impossible to extract and analyze. But data science teams with special cognitive analytics and data cataloging capabilities in the cloud can pull out intelligence from this pile of unstructured data. Analysing customer transaction patterns, testing different marketing offers have therefore never been easier.

With the rise of companies offering services through online chatbots, the volume of unstructured information has grown significantly once again. The ability to store and quickly recall volumes of specific pieces of data becomes critical for turning a simple messaging assistant into a quick and informative customer experience.

The growth of data sources across the globe are on the rise. Programming, data mining and analyzing, communication, tailored customer experiences and offers are being developed thanks to the work of data scientists and the help of the cloud.

This huge source of information is the greatest potential possible for many industries, and data scientists need to have access to the right resources and technology to evaluate it. Remember, nowadays, it’s not enough to have data. Companies need a group of people and machines to manage it and draw insights from it.


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