Data Science Vs. Data Analytics Vs.
Machine Learning: Expert Talk
Data & Analytics go hand in hand when it comes to
enterprise activities. These are essential in driving
business growth of companies because both data & its
analysis gives crucial insights into various business
advancements, people can get
emerging technologies like AI, Machine Learning,
Blockchain & data analysis techniques like big data,
data analytics & data science.
If your company is planning to become a data-driven
organization in the future, then you need to have a clear
understanding of tools & technologies that can seamlessly give
you actionable insights. So, if you invest the right amount of time
& resources to understand such techniques & technology, then
your enterprise can have a competitive edge over others.
Naturally, questions will arise when you research various
What is Data Science & How can it help my organization?
What is Machine Learning? Can it help me to get critical data
Is Data Science different from Data Analytics?
What is Structured & Unstructured Data?
So, let’s have a brief understanding of Data Science & Data
Analytics, its core differences, Machine Learning & its usage in
Is Data Science & Data Analytics
Data Science & Data Analytics are not new terms. In fact,
Data Analysis techniques came to the fore in 1962. The term
“Data Science” was first used by Peter Naur in 1974 & In 1992,
the broad definition & core principles of Data Science were laid &
Similarly, the processes that are now called Data Analytics has its
origins in the late 1960s.
Superficially, both the terms might look the same. However, they
have some core differences. Let’s know a little bit about Data
Science & Data Analytics
What is Data Science?
Data Science is an extensive multidisciplinary field. Its primary focus is
to help companies find unseen connections (pertaining t