The words like Big Data (BD), Machine
Learning (ML), Data Mining (DM), Cognitive Applications (CA), Artificial
Intelligence (AI) etc. keep coming up in many discussions or conversations
these days but what exactly they are and how are they interrelated? Here is the
explanation of some of these terms in a very simple manner. Let’s start with
Big Data.
1. What is Big Data? When exactly
the data is termed as “Big Data”? Is it the size of elephant or dinosaur?
A: Actually there is no particular
limit defined for data after which it becomes big data. The data is big or
small in reference to the application in which we are using it. When the
particular application is not able to handle or respond to data then that data
becomes big for that particular application. For example same amount of data
can be termed as Big Data for Excel but not for SAS or SPSS. Hence, the term
Big Data in itself is not appropriate and it is better to refer such data as
Large Data.
2. What is the difference between
Data Analysis & Data Science?
A: Data Analysis is simply
analyzing data. From ages, data has been analyzed for various techniques like MIS
Reporting, Six Sigma, Lean etc. However, Data Science is little different from
Data Analysis. Data Science is also data analysis but here we analyze large
data sets with the help of Machine learning and/or Data Mining techniques. Data
Analysis can be done with tools like Excel, however for Data Science tools like
SAS, SPSS, Python, R etc. are required. A Data Scientist needs to have statistical
knowledge along with programming skills.
