WHAT IS DATA SCIENCE?
At first, there was data and with time, it grew to big data. Big data is nothing but a large quantity of data. Although data was increasing,
there was no technology to store that much amount of data. This lead to the development of Hadoop and other framework to handle big data. Now, the main problem was,
what to do with this data? How it can be useful? So, the focus shifted to processing of data. At this stage, data science came into picture.
WHAT IS THE NEED OF DATA SCIENCE?
Traditionally, the data was structured and small in size. This data was easy to analyze using simple Buisness Intelligence algorithms. Now a days, most of the data is in unstructured form and hard to find patterns using BI algorithms.
So, Data Science was necessary to find patterns in the unstructured data.
Let's look at some domains where data science is being used.
If you want are developing a system that predicts the requirements of customer based on customer's activity in the past.
This data was also present before but no one was using it and it was just a weight on the databases.
There are ample situations where data science can be helpful. May be detecting some disease based on previously stored data or prediction of natural calamities. The choices are infinite.
WHAT IS THE DIFFERENCE BETWEEN DATA ANALYST AND DATA SCIENTIST?
Now, masses get confused between data analyst and data scientist.
DATA ANALYST
The main difference is that, a data analyst does the buisness administration and perform exploratory data analysis.
Although the data is being explored by data analyst , the information was not being used anywhere.
DATA SCIENTIST
On the other hand, the responsibilites of a data scientist includes exploratory data analysis , machine learning and advanced algorithms and data product engineering.
HOW TO BECOME A DATA SCIENTIST?
CHECK OUT OUR HOW TO START TO BECOME A DATA SCIENTIST AND OTHER POPULAR PAGES