Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and Visualization

Abstract

Huge amounts of useful data are easily generated and gathered currently at a rapid rate from a broad range of rich data sources in numerous applications and services in the real world. Data science applies database techniques, scientific and engineering methods, mathematical and statistical models, data mining algorithms, and/or machine learning tools to manage data, extract the useful information and discover the new knowledge from these big data. This explains why data science for big data applications and services has become a fundamental technology in providing novel solutions in various areas in business, engineering, health, humanities, natural sciences, social sciences, etc. (e.g., healthcare, manufacturing, social life). Usually, data science focuses on big data management, analytics and visualization. Once big data are managed (i.e., captured, curated, managed and processed), big data are analyzed with an aim to discover interesting knowledge and information, which is usually presented in text or table form. Consistent with a proverb that “a picture is worth a thousand words”, big data visualization as well as visual analytics helps to reveal and explain the discovered interesting knowledge and information. In this paper, we present (a) big data management with focus on information fusion and the data lake; (b) big data analytics and mining, with focus on frequent patterns; as well as (c) big data visualization with focus on a few visual analytic systems for visualizing big data and mined frequent patterns. For illustration, we discuss these three aspects of data science on coronavirus disease 2019 (COVID-19) data. This highlights some important aspects of data science for big data analyses, services, and smart data.