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Data Science

This article dives deeper into what data science is and how it can be described.
© Luleå University of Technology

Data science continues to evolve as one of the most promising areas to analyze data and support organizations in their digitalization journey. It combines advanced analytics techniques such as artificial intelligence (AI), algorithms, and machine learning with data to uncover actionable insights hidden in an organization’s data. These insights support data-driven decision-making.

The sheer amount of big data has made data science one of the fast-growing fields. Organizations are increasingly relying on data science in order to extract hidden patterns and knowledge from their data assets and provide actionable insights to improve business outcomes. More and more companies are coming to realize the importance of data science, AI, and machine learning. Regardless of the industry, organizations that wish to remain competitive in the big data era, need to efficiently develop and implement data science capabilities.

Put in other terms, data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. The data used for analysis can come from many different sources and be presented in various formats.

Climate change is an unrelenting contemporary concern, for which data science facilitates data-driven decisions offering an innovative, yet comprehensive, approach to address its complexity and challenges.

An interesting example of how data science is serving to make the world a better place to live is by addressing some of these current climate change challenges. A recent study by NASA provides an in-depth look at how massive amounts of data can be leveraged and analyzed to generate viable solutions to combat climate change. In this study, it is argued that climate science represents a data science domain that is undergoing extraordinary growth. The report stipulates that there is a need to provide effective means for publishing scientific datasets and performing advanced analytics based on big data efficiently.

© Luleå University of Technology
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Data Science for Climate Change

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