The 21st century has ushered in the age of big data and data economy, in which data DNA,
which carries important knowledge, insights, and potential, has become an intrinsic …

The main purpose of data mining and analytics is to find novel, potentially useful patterns
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …

CRISP-DM (CRoss-Industry Standard Process for Data Mining) has its origins in the second
half of the nineties and is thus about two decades old. According to many surveys and user …

Metalearning attracted considerable interest in the machine learning community in the last
years. Yet, some disagreement remains on what does or what does not constitute a …

The use of end-to-end data mining methodologies such as CRISP-DM, KDD process, and
SEMMA has grown substantially over the past decade. However, little is known as to how …

As the need to analyze big data sets grows dramatically, the role that classification
algorithms play in data mining techniques also increases. Big data analysis requires more of …

An increasing number of publications concerning data mining in the subject of human
resource management (HRM) indicate the presence of a prospering new research field. The …

The unprecedented and overwhelming SARS-CoV-2 virus and COVID-19 disease
significantly challenged our way of life, society and the economy. Many questions emerge, a …

The coronavirus pandemic has been globally impacting the health and prosperity of people.
A persistent increase in the number of positive cases has boost the stress among …

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Go to cart Search SpringerLink Search Book cover Data Science Thinking pp 59–90Cite as …