Information technology

Data science and business intelligence – Definitions

Data science, business intelligence and big data. The definitions in vocabulary.

It’s easy to spot these hype terms like data science, big data in LinkedIn or exhibition posters. I summarized the definitions of most frequently used buzz words. The definitions are not official if there even exists official versions and some of them overlap with each other. Anyway the definitions will be useful for sure when you next time meet people in a cocktail party and want to discuss little deeply.

Definitions of data related terms

Data scientist

A data scientist should manage computer science and statistics but also have a good insight in business to make vice decisions. The keyword here is problem solving.

Data engineer

Data engineer is more like, well, engineer that plans the software infrastructure. So maybe data scientist will use the platform that data engineer has developed.

Data analyst

In an article a data analyst was described as inexperienced data scientist who does not necessarily deal well with statistics and algorithms. It fits well to my idea about this title.

Business analyst

Something similar to data analyst but this guy fight more with real life business problems. Data is just one tool in the box as sometimes you get the answer with other methods suc as by asking question.

Business intelligence

I could almost say that this is a fancy term for reporting. Business intelligence is about doing reports, analyzing them and making human decisions based on historical data. Many of the BI tools and concepts are beginning to be well established in the industry.

Data warehouse

Somewhat well defined concept to store data so that business intelligence people can use it for reporting.

Big data

So large amount of data that it’s difficult or impossible to process with traditional methods. For example relational databases are not capable in some situations anymore.


Internet of Things means sensors and measuring equipment that are attached to physical objects. The sensors then send the data to some kind of data storage. Most often data is very high frequeny and that’s why IOT is a friend of big data.


Finally you should remember that enterprises themselves cannot define this terms accurately. With this vocabulary you can however specify little bit better what exactly do you mean when you are talking about data.

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