wehub-resource-sync
27 lines
1.3 KiB
Markdown
27 lines
1.3 KiB
Markdown
# What is the Definition of Data Science?
|
||
|
||
That's a tricky question. It's particularly challenging because there is no "definition." Unfortunately, this rather novel term has been used ambiguously, and there are many subjective definitions. Anyway, I think the field of Data Science is highly interdisciplinary and influenced by many many other fields ...
|
||
|
||
Okay, before I start, I’d say data science is mainly about extracting knowledge from data (and I think that the terms “data mining” or “Knowledge Discovery in Databases” are highly related). So, data science can be about analyzing trends, building predictive models, … etc.
|
||
|
||
It’s say data science is an agglomerate of data collection, data modeling and analysis, decision making, and everything you need to know to accomplish your goals with respect to the aforementioned sub-tasks. Eventually, it boils down to the following fields/skills:
|
||
|
||
There’s computer science:
|
||
|
||
- algorithms
|
||
- programming (patterns, languages etc.),
|
||
- understanding hardware & operating systems
|
||
- high-performance computing'
|
||
|
||
And the mathematical aspects:
|
||
|
||
- linear algebra
|
||
- differential equations for optimization problems
|
||
- statistics
|
||
|
||
Plus others:
|
||
|
||
- machine learning of course (somewhere between the technical and mathematical skills)
|
||
- domain knowledge
|
||
- and very important: the data visualization & communication skills
|