As one journeys through his/her career in analytics, some truths start becoming evident over time. And while none of them are ground-shattering, they often surprise novices in the field. So, it’s worthwhile to know 11 absolute facts of data science.
If you think academia has problem with unreproducible research, you should work in private sector consulting for some time.
If you can use data science to make your customers to do random walk in the space of doing their business and they reverse the negative changes after some time, it shows in the bottom line after a while.
While I found this list to be quite good is it a common thing to write an article based on "facts" pulled from reddit? (see note at the bottom of the article)
12. Statisticians who have been working successfully in this area for decades will now need to re-brand themselves as "data scientists", because "statistics" isn't a sexy enough word.
On a side note, 9 of those statements apply equally to any technical field. The only two that don't (deep learning and big data) can be substituted with the appropriate term du jour in the field.
For example, I'd argue they apply very well seismic interpretation in a business setting. The connotations change a bit, but the overall sentiment is identical.
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[ 2.6 ms ] story [ 24.9 ms ] thread7. No one cares how you did it
9. Presentation is key
If you think academia has problem with unreproducible research, you should work in private sector consulting for some time.
If you can use data science to make your customers to do random walk in the space of doing their business and they reverse the negative changes after some time, it shows in the bottom line after a while.
For example, I'd argue they apply very well seismic interpretation in a business setting. The connotations change a bit, but the overall sentiment is identical.