|
|
Method: "Data Science" Node Cluster View Page
| ATTRIBUTE NAME |
ATTRIBUTE TYPE |
ATTRIBUTE VALUE |
| Title |
String |
Data Science |
| Abbreviation |
Acronym |
DS |
| Similar Method |
Method |
Data Engineering |
| Description |
String |
Data Science is the methodology or practice of exploring and working with data to discover and calculate new data or data that is not normally achievable through human labor. In addition to all forms of data processing, common sub-areas of Data Science include but are not limited to practices such Data Analytics, Informatics, Predictive Analysis, Machine Learning, Reporting, Data Visualizing, Info-Graphing, Semantic Data Analysis and Processing, and Natural Language Processing (NLP).
Like most scientific areas of practice, Data Science often includes a tremendous amount of trial and error, much of it which may not lead to usable outcomes. For those outcomes that are usable, it is common to work with Data Engineers to commoditize them and apply them to broader and more resuable problem domains. |
| Read More |
HTML Link |
https://scholar.google.com/scholar?q=%22Data+Science%22&btnG=&hl=en&as_sdt=0%2C31 |
| End of Data |
|
