Introduction
The branch of science which deals with the
study of data is known as data science. Well, if you dig a little deeper, it
does not only mean the study of data, but also its manipulation and processing.
Data science typically involves-
1. Identifying and determining the correct
data.
2. Collecting large amount of both
structured as well as unstructured data.
3. Cleaning, validating, devising and
applying algorithms.
4. Analyzing and interpreting the data.
5. Finalizing the data.
Use of Data Science
Now, a question should be arising in your
mind that what is the use of data science. Well, the answer lies in the fact
that not all data is structured. Today, data is mostly either unstructured or
semi structured, and for dealing with this type of data, we need data science,
but this is not the only reason for having data science, if you dig deeper, you'll
find many more reasons for the existence of data science.
Data Science Training
Data science training is nothing else but
the process of becoming a data scientist. It requires both tools and machine
learning. Data science training involves a lot of time in gathering data,
cleaning data and munging data as data is never clean.
All this requires persistence, statistics
and skills. Altogether, becoming a data scientist is not at all an easy job. A
data scientist applies machine algorithms to text, numbers, images, audio,
video and many more to manufacture artificial intelligence (AI) systems. In
other words, a data scientist has to analyze data and provide enough meaningful
data for organizations to make a well-informed decision.
More generally, a person having the
knowledge of how to extract meaning from interpreted data is termed a data
scientist.
Data Science VS Business Intelligence
Many of you may confuse data science with
business intelligence which shouldn't happen as the two are very different concepts.
Business intelligence analyses previous data and finds insight to explain the
ongoing business trends whereas data science is a more advanced approach. It
can explain what and how events occur by analyzing the past or current data.
All You Need to Become A Data Scientist
After reading the above article and digging
deeper in the field of data science, many of you will be interested in becoming
a data scientist, and you'll eagerly want to know the qualifications and skills
required for becoming a data scientist. The first and foremost thing required
is education as data scientists are highly educated intellectuals and secondly,
you require programming skills. R programming is generally preferred for learning
by a data scientist as it is specially designed for the same. Some technical
and non-technical skills required are - python coding, SQL database/coding,
apache spark, machine learning and AI, data visualization, intellectual
curiosity, business acumen, communication skills and teamwork.
The Conclusion
Now that we know what data science means
and how it functions, we can conclude that maybe it is a complex thing to
understand but once implemented will surely benefit the organization. It is
beneficial in the long run.
To become a data scientist, you would need datascience training. ExcelR offers a variety of courses and training to clear
your concepts.
https://www.excelr.com/data-science-course-training-in-bangalore/
