Skip to main content

How to Speak Data Science

Data Science has its own language. This is a great list of often-heard data science terminology and quotes by Datacamp.
Mar 2015  · 3 min read

Data Science has its own language. So, if you want to have at least a slight chance of surviving in the enterprise world of tomorrow -with its obsessive focus on collecting and analyzing data- you better have started yesterday with learning this terminology.

Luckily, and inspired by the “How to Speak Startup” article on TechCrunch, the online data science school DataCamp is here to help you with a great list of often-heard data science terminology and quotes:

(Note: This is an attempt to be funny. Whether this is a successful attempt is an opinion and open for debate. That it shouldn’t be taken serious nor offensive is a fact.)

  • Data scientist - Average programmer looking for a job that pays as much as what a top programmer would get. Sometimes also goes by the name "data analyst". Click To Tweet.
  • Statistician - Mathematician who can’t program. Click To Tweet
  • "Our company is big data ready" - My software vendor has done a great up-sell. Click To Tweet
  • "We measure everything" - We have absolutely no clue what to measure. Click To Tweet
  • Data savvy manager - Title used by managers active in marketing, sales or HR whom put pie charts in their powerpoint presentation. Click To Tweet
  • "Correlation does not imply causation" - We looked at the wrong data set and can’t draw any conclusions from it. Often represented in a graph to create the illusion of adding value. Click To Tweet
  • Machine Learning - Statistical technique used by the sales and marketing department of big data vendors to secure their yearly bonus. (also see "Our company is big data ready") Click To Tweet
  • Chief Data Scientist (CDS) - Former CTO (also see data scientist) Click To Tweet
  • Hadoop - Open-source software used for distributed computing. Data Scientists seem to have a quota to drop the name every two sentences when talking big data, but most only know the logo is a yellow elephant. Click To Tweet
  • “Being a data scientist is the sexiest job in the 21st century" - Although a quote often used in the data science industry, statistical underpinned proof remains missing. Click To Tweet
  • Data science bootcamp - Headhunting firm marketing itself as a school. Click To Tweet
  • “We booked these results with a small sample" - Our financial budget wasn’t large enough to perform a statistical significant data analysis. Click To Tweet
  • “We implemented a data-driven decision making process” - In the past we didn’t have a clue what we were doing. Click To Tweet
  • "We use cutting edge predictive modeling techniques to forecast our results” - We run a linear regression model and then ignore the result. Click To Tweet
  • "There is a significant effect but ..." - Sentence-start used by data scientists or statisticians when they’ve put weeks of work into their analysis, the results look fishy and not as expected, and there is no time to redo the analysis. Click To Tweet

Hope this was helpful! Good Luck.

Spatial Statistics in R

Beginner
4 hours
9,386
Learn how to make sense of spatial data and deal with various classes of statistical problems associated with it.
See DetailsRight Arrow
Start Course

Introduction to Data Science in Python

Beginner
4 hours
396,225
Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

Machine Learning for Business

Beginner
2 hours
18,487
Understand the fundamentals of Machine Learning and how it's applied in the business world.
See all coursesRight Arrow
Related
Data Science Concept Vector Image

How to Become a Data Scientist in 8 Steps

Find out everything you need to know about becoming a data scientist, and find out whether it’s the right career for you!
Jose Jorge Rodriguez Salgado's photo

Jose Jorge Rodriguez Salgado

12 min

YOLO Object Detection Explained

Understand YOLO object detection, its benefits, how it has evolved over the last couple of years and some real-life applications.
Zoumana Keita 's photo

Zoumana Keita

5 Ways to Use Data Science in Marketing

Discover five ways you can use data science in marketing. Get ahead of the game, improve your data skills, and work on a data science marketing project.
Natassha Selvaraj's photo

Natassha Selvaraj

DC Data in Soccer Infographic.png

How Data Science is Changing Soccer

With the Fifa 2022 World Cup upon us, learn about the most widely used data science use-cases in soccer.
Richie Cotton's photo

Richie Cotton

_Quote.png

The Deep Learning Revolution in Space Science

Justin Fletcher joins the show to talk about how the US Space Force is using deep learning with telescope data to monitor satellites, potentially lethal space debris, and identify and prevent catastrophic collisions. 

Richie Cotton's photo

Richie Cotton

53 min

Regular Expressions Cheat Sheet

Regular expressions (regex or regexp) are a pattern of characters that describe an amount of text. Regular expressions are one of the most widely used tools in natural language processing and allow you to supercharge common text data manipulation tasks. Use this cheat sheet as a handy reminder when working with regular expressions.
DataCamp Team's photo

DataCamp Team

See MoreSee More