Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. … A Data Scientist will look at the data from many angles, sometimes angles not known earlier
This data is generated from different sources like financial logs, text files, multimedia forms, sensors, and instruments. Simple BI tools are not capable of processing this huge volume and variety of data. This is why we need more complex and advanced analytical tools and algorithms for processing, analyzing and drawing meaningful insights out of it.
Use of the term Data Science is increasingly common, but what does it exactly mean What skills do you need to become Data Scientist What is the difference between BI and Data Science How are decisions and predictions made in Data Science These are some of the questions that will be answered further.
First, let s see what is Data Science. Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. How is this different from what statisticians have been doing for years
As you can see from the above image, a Data Analyst usually explains what is going on by processing history of the data. On the other hand, Data Scientist not only does the exploratory analysis to discover insights from it, but also uses various advanced machine learning algorithms to identify the occurrence of a particular event in the future. A Data Scientist will look at the data from many angles, sometimes angles not known earlier.
So, Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning.