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.

The post How to Speak Data Science appeared first on The DataCamp Blog .