Whether you are a newly graduated student from the university or a white-collar who has been active in business for 5 years, there is a question. The question is: "Will the profession I have chosen satisfy me after a while?".
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Career Choice
If you take into account both the money you will earn and the feeling of professional satisfaction when choosing a profession, you are likely to ask yourself this question. Professions are also rapidly taking shape in the rapidly developing and changing world economic system. Of course, the expectations and job descriptions in the sector are also affected by these changes.
Career Choice
If you take into account both the money you will earn and the feeling of professional satisfaction when choosing a profession, you are likely to ask yourself this question. Professions are also rapidly taking shape in the rapidly developing and changing world economic system. Of course, the expectations and job descriptions in the sector are also affected by these changes.
Especially in the
last 10 years; trends such as machine learning, artificial intelligence,
digital marketing, consultancy and big data are the locomotives of this
process.
So how did these
trends develop so quickly?
My personal
observation is that there is a 'data processing mechanism' at the basis of all
this. Regardless of which of these trends the company you work with earns
material income, it has to classify and make sense of the data it obtains. Of
course, in the end, to turn it into an algorithm or a comment...
The Big Data
Trend in the World
Although summing it up in two sentences as I did may sound easy, this does not change the fact that the process is very complex. It is a really long and tedious process for a company to access, classify, interpret and interpret data. However, companies doing this correctly can make really good profits from this business.
If we can predict
how much data is produced worldwide, we can understand how big a market this
is.
According to 2018
figures, the total number of data created so far on the internet is 18
zettabytes. By 2025, this figure is expected to increase ten times and reach
175 zettabytes. Because there is a rapidly increasing use of data. The industry
is growing very quickly.
1 zettabyte is
1.000.000.000 terabytes.
If we wanted to
store 175 zettabytes on DVD, we would have to create a DVD set that can travel
around the Earth 222 times!
When you begin to
specialize in Data Science, you see that it is an immense field. Acquisition,
storage, use and protection of data, etc. It includes dozens of different
specialist processes, including before and after data processing. When you
begin to specialize in one of these processes, you may have the opportunity to
learn other processes, albeit partial. In this respect there is a similarity
with coding, so changing expertise is simpler.
After some experience in independent auditing at PwC and KPMG companies,
the Excel, Power BI and Tableau programs that I learned compulsorily enabled me
to be actively involved in the process of meaning and visualization of data.
Although I am working in a field operating in the financial sector, my job is
essentially a data processing business.
For those who do
not know about Independent Audit, it is useful to define it in the simplest
way. It is a business process where we take the data that is useful to us from
the customer, make the necessary deductions from them and report in the IFRS
accounting language. Of course, as with any job, it has hundreds of details,
but they are not the subject of this article.
Especially in the
last 2 years, I worked in PwC, I got interested in the coding area. I wanted to
acquire the front-end developer infrastructure and further develop myself. I am
currently learning JavaScript, CSS and HTML. I bought myself a nice laptop and
started my education. Within a year, I want to go a level in these areas and
switch to programming languages. The programming language I am most interested
in is Python and Julia. Python is the simplest language you can learn, and
Julia is an alternative program that is expected to replace Python in the
future... Getting the infrastructure to learn these excites me.
Of course, not
everyone does this. You must have a passion for a good progression in your
skill. I am talking about trying to learn them while working an average of 14
hours a day between January and July. A separate dimension of passion.
As I said, once
you enter the data science, you can go all the way to artificial intelligence
or coding if you have time and curiosity. It is entirely up to you.
Data Science
has been a field that influenced me a lot while shaping my career. I hope that
I have caused you to be interested in this field, which is seen as the sector
of today and the future.
If you are interested in online money making, career, personal development, investment and entrepreneurship and want to make more money, stay tuned.
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