1.3.1.Data Science in Business - sj50179/IBM-Data-Science-Professional-Certificate GitHub Wiki

How Data Science is saving lives

Using Data Science techniques to understand and analyze the large data sets available today has a huge impact on human lives. It can provide targeted information to help healthcare professionals give the best treatment to patients, or help predict natural disasters so that people can prepare early, and much more besides.

Data science tools enable organizations to analyse vast quantities of data from widely different sources, and present that information in a way that allows data scientists to gain new knowledge, in some cases, saving hundreds of lives.


How Should Companies Get Started in Data Science?

First thing first, start capturing data. Once you have data, then you can apply algorithms and analytics to it. So the first thing to do would be to capture data. If you're not capturing it, start capturing it. If you're capturing it, archive it. Do not overwrite on your old data thinking you don't need it anymore. Data never gets old. Data is always relevant, even if it's 100 years old, 200 years old. It is relevant to you and and your firm and your success. So keep data, capture it, archive it, make sure nothing goes to waste. Make sure there's a consistency. So someone 20 years later trying to understand, that data should be able to do so, so have proper documentation. Do it now. Put the best practices for data archiving in place the moment you start a business. And if you're already in business and you haven't done it, do it now.


Lesson Summary

In this lesson, I have learned:

  • Data Science helps physicians provide the best treatment for their patients, and helps meteorologists predict the extent of local weather events, and can even help predict natural disasters like earthquakes and tornadoes. 데이터 μ‚¬μ΄μ–ΈμŠ€λŠ” μ˜μ‚¬λ“€μ΄ ν™˜μžμ—κ²Œ μ΅œμƒμ˜ 치료λ₯Ό μ œκ³΅ν•  수 μžˆλ„λ‘ 돕고 κΈ°μƒν•™μžλ“€μ΄ 지역 기상 ν˜„μƒμ˜ 정도λ₯Ό μ˜ˆμΈ‘ν•  수 μžˆλ„λ‘ 도와주며, μ§€μ§„μ΄λ‚˜ 토넀이도와 같은 μžμ—°μž¬ν•΄λ₯Ό μ˜ˆμΈ‘ν•˜λŠ” 데도 도움을 쀄 수 μžˆλ‹€.

  • That companies can start on their data science journey by capturing data. Once they have data, they can begin analysing it. 기업은 데이터λ₯Ό μΊ‘μ²˜ν•¨μœΌλ‘œμ¨ 데이터 κ³Όν•™ 여정을 μ‹œμž‘ν•  수 μžˆλ‹€. 일단 데이터가 있으면 뢄석을 μ‹œμž‘ν•  수 μžˆλ‹€.

  • Some ways that data is generated by consumers. How businesses like Netflix, Amazon, UPs, Google, and Apple use the data generated by their consumers and employees. μ†ŒλΉ„μžκ°€ 데이터λ₯Ό μƒμ„±ν•˜λŠ” λͺ‡ 가지 방법이 μžˆλ‹€. Netflix, Amazon, UPs, Google 및 Appleκ³Ό 같은 기업이 μ†ŒλΉ„μžμ™€ 직원이 μƒμ„±ν•œ 데이터λ₯Ό μ‚¬μš©ν•˜λŠ” 방법

  • The purpose of the final deliverable of a Data Science project is to communicate new information and insights from the data analysis to key decision-makers. 데이터 μ‚¬μ΄μ–ΈμŠ€ ν”„λ‘œμ νŠΈμ˜ μ΅œμ’… 결과물의 λͺ©μ μ€ 데이터 λΆ„μ„μ˜ μƒˆλ‘œμš΄ 정보와 톡찰λ ₯을 μ£Όμš” μ˜μ‚¬ κ²°μ •μžμ—κ²Œ μ „λ‹¬ν•˜λŠ” 것이닀.


Quiz

Reading:The Final Deliverable