Data Science
Data Science (DS) aims to extract valuable information, insights and knowledge from large-scale data. It is a multidisciplinary approach that combines the principles and practices of mathematics, statistics, artificial intelligence and computer engineering to analyze large amounts of data. These analyses can help data scientists ask and answer questions such as what happened, why it happened, what will happen and what can be done with the results.
History of Data Science
While the term data science is not new, its meaning and connotations have changed over time. The term first appeared in the 60s as an alternative name for statistics. It was not until the late 90s that computer science experts formalized the term and recognized it as an independent field that includes three aspects: data design, data collection, and data analysis. It took another decade before the term data science became used outside of academia.
The Future of Data Science
Innovations in artificial intelligence (AI) and machine learning (ML) are making data processing faster and more efficient. Industry demand has spawned an ecosystem of courses, degrees, and jobs in the field of data science. Data science is a trend that is expected to continue to grow strongly in the coming decades due to the need for cross-functional skills and experience. While many parts of data science fall outside the scope of HPC, many others rely on the powerful computing power of HPC to complete a variety of different data analysis tasks. This can be either MPI or highly parallel, depending on the workload in data science being examined.