Data analysis is one of the revolutionary technique that has been the base for further lot technologies and industries. It is important and is structured in a disciplinary manner in order to produce essential results. Concept includes static algorithms and particular set of work methods but the result is always dynamic.  

1. Learning Data Analytics

2. • Data analysis is one of the revolutionary technique that has been the base for
further lot technologies and industries. It is important and is structured in a
disciplinary manner in order to produce essential results. Concept includes static
algorithms and particular set of work methods but the result is always dynamic.
• In further simpler words, set of data( practically abundance of data) will be
analysed and filtered to reach to the results which represents almost of the people
in the world. Such results are used in every known fields like clothing, medical,
fashion, health care, cosmetics, appliances, household materials, furnitures and
everything. In other words, the result will ultimately change the products of big
industries of world. You ask, how? Well the result that I am referring to the result
of interest, expectations, values, perspectives, of the people. These result has been
resulting in biggest milestone of technology and it will continue to do better in
upcoming days.

4. But how possibly could normal peoples lifestyle
change the technology? Is the foremost
question that prick the mind. So allow me to
explain it to you:

5. 1. Filtering lifestyle
• You can surely see an audacious transformation in lifestyle from past few
decades to contemporary. Recapture the infamous materials back in there,
they were dependent on what people needed and expected at that
decade. Look upon the materials we now consist, it depends on what and
why we need them. As lifestyle changes the materials around us also
changes but the the technology is a few steps ahead, rather going in flow
with changing lifestyle, it is priorly collecting what the future might be like,
and what would people need in there. This is collected by analysing the
data of every individual, the data will be sensitively observed, then the
result will be created.
• Doesn't it sound all pre planned and set of intellectual manner of work? It
ofcourse does, because it is so.

6. 2. Education qualification
• Now this is very important, the process of data collection( that happens
every millisecond) it is way more easier to precisely count how much
amount of people on earth are literates, illiterates, graduates, under
graduates, post graduates, PhD holders and else others. This calculation of
data is very much important for data science( which includes data analysis)
upon the calculation, data scientists can precisely count how many more
data scientists could possibly be produced based upon their qualification.
The number of data scientists are being increasing produced every day
from the corners of the world but yet the need is still more. Since data
science concludes various concepts, it will be easier for a person to learn
atleast one respective aspect of data science and could serve as data
scientist. So there is no worry in being a data scientist for non-technical
people.

8. 3. Programmers are on high demand:
• Being a programmer is an individual interest, could ace being
one by self study. There are lot of freelancing programmers
who aren't certified by an university but they still crack
reliable codes merely by practice and putting effort of
dedication upon it. Data science is desperately in need of
programmers who are not certified but are much better
programmers than the certified ones. Through data analysis it
is much more easier to count such techies, and through
marketing they can easily reach to such people and invite
them to be a data scientist.

9. 4. Lets look upon present byproducts of data
analysis:
• 1. Software applications:
• we might ignore how much space the applications has engulfed in our lives
for. For example, we now have medical apps in Google play and Apple
store which delivers medicine, the production of this applications is
analysed with the help of data analysis, of in which area this facility is most
needed, what type of medicines are generally needed, how much it will
grow among which society is calculated, upon this calculation, the plan will
be set.
•
• 2. Psychological support:
• It is now available of mental support of service in online through lot of
mental health related websites.

10. • 3. Business and loans:
• Again upon the analysis of how many people would be benefited by a business
maintaining and advising apps, the creators will produce them.
•
• 4. Social media apps:
• This would be familiar to everyone because the usage of social media is in stature
and unlimited. These are clear examples of byproducts of data analysis.
•
• 5. Online education:
• There are several number of websites that provide online education which has
made education handy and easy.
•

12. • There are still many consequences of data analysis which are
tremendous, the best part is there will be fewer experience of loss
because it will be entirely upon what is really needed and how
much is it needed. What would realistically go flop if it is with a
clear target and organised scheme. Another best part is, anyone
who is determined to be part of data science can really ace it
through by attending classes and learning the concept.
• Learnbay is a Bangalore based Data science and Data Analytics
training center which provides essential concepts of specified tools
in the course structure. By teaming up with IBM, Learnbay is helping
aspirants to learn the next big field like Data Science with proper
tools of education.

13. Thank you
For More Details:
www.learnbay.com