We all remember the good old days at the beginning of the 2000’s. Myspace was created. Social media began to piggyback off of that platform to give us Facebook and several other. Youtube even followed shortly after. It was then that a term was coined that is more important now than ever from a business perspective and it gets a pretty misunderstood life. Data Science. So what is it really? Let’s find out.

First off we have to go back to the beginning. The “birth” of data science in a way. Data science in a simplified nutshell is the combination of computer science and data mining. It wasn’t very popular before social media. However, when the digital footprint of the collective human race began to stretch beyond that of the basic email and into social media, the world saw a mass of data.

This big mass of data from the ever flowing digital footprints had massive value to companies. It opened a world of possibilities in which decisions could be made by using this data. But those simple questions for those decisions were almost always met with varying degrees of difficulty in regards to the data. Companies began hiring people for those roles. Analyzing large amounts of data, data mining, programming and more to gain knowledge with those numbers. Data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.

So what’s the process or in this case cycle for data science? 

Good question! The cycle is a 5 step process in which companies capture, maintain, process, analyze, and communicate data. And this process is circular so it constantly happens over and over. 

Capture involves data acquisition, data entry, signal reception and data extraction. 

Maintain involves data warehousing, data cleansing, data staging, data processing and data architecture.

Process involves data mining, clustering/classification, data modeling and data summarization.

Analyze involves exploratory/confirmatory, predictive analysis, regression, text mining, and qualitative analysis.

Communicate involves data reporting, data visualization, business intelligence and decision making.

As you can see there are many different things that involve data science. As increasing amounts of data become more accessible, large companies are no longer the only ones in need of data scientists. There is an ever growing demand for data science professionals across all industries. And if you are looking into data science or wanting to hire one after seeing all that they can do, head on over to creativeteam.io. Where we can help you find the answers you seek with your data. Becomes sometimes… this is not the data you are looking for.