The recent buzzword in the tech world is Data Science. What is data science?
Let’s take the example of Amazon, they have an enormous amount of raw information in their storage framework. What people are buying, how frequently they are shopping, what they are searching, what their preferences are and even how they are paying for their purchases. Every type of raw data combined together to form big data. But just keeping these data stored will not be of any help.
One needs to simplify and analyze this data. Because these data can be helpful in taking strategic business decisions.
WHY DATA SCIENCE?
When you have a large amount of raw and unsorted data, the first thing that one needs to do is sorting. Sorting will simplify and group the data into manageable portions which can be worked with. Data science is all about getting a data product at the end, like your Amazon homepage.
Big data is input which is processed using several algorithms and data tools, which in turn gives data product. Data product’s usage is for finding technical solutions to business problems.
Data science helps in various sectors and fields in daily work and life. From eCommerce, law, defense, health, entertainment to finance and investments each and every business concern need to use the data for its growth.
WHO ARE DATA SCIENTISTS?
Professionals who turn the big data into a meaningful insight are data scientists. But of course, it's not that simple. To be a data scientist one should have a background in mathematics and technology. But that's just preliminary; the most important part is to have strategic acumen. Without a strategic outlook, data product will be of no use. Business acumen helps in understanding the problem and find a workable solution to it. Whether to attract or retain customers or to optimize the processes of the business like supply chain and stock holding.
Other than just technical knowledge one also should have the mindset to be a data scientist. That is to have an intellectual curiosity to ask new questions and make new discoveries. One should be able to uncover the truth hidden beneath high stacks of raw data.
HOW TO BE A DATA SCIENTIST?
Demand for data scientists is exponential today. It's the up and coming career choice for many tech students and professionals. Higher demand means a higher number of opportunities, but that also leads to higher competition. So to succeed in such competition, one should be trained properly and in the right direction.
Having hundreds and thousands of certification courses to choose from, it might get really confusing. So one should have their priorities set like what they want to learn, how much they want to invest and what their expectations are in the long run. Usually, certification courses teach R programming, tableau training, data mining, Python, machine learning, etc.
Select a course, and work hard on it, and gain real-world experience because that's the most important facet of any training.
RESOURCE BOX:
You think you have the acuity and perseverance needed to become a data scientist and work on predicting the future. If so, then choose the best to reach your goal. Here data science certification in Mumbai gets an idea of the vast and prolific options one can have.
Let’s take the example of Amazon, they have an enormous amount of raw information in their storage framework. What people are buying, how frequently they are shopping, what they are searching, what their preferences are and even how they are paying for their purchases. Every type of raw data combined together to form big data. But just keeping these data stored will not be of any help.
One needs to simplify and analyze this data. Because these data can be helpful in taking strategic business decisions.
WHY DATA SCIENCE?
When you have a large amount of raw and unsorted data, the first thing that one needs to do is sorting. Sorting will simplify and group the data into manageable portions which can be worked with. Data science is all about getting a data product at the end, like your Amazon homepage.
Big data is input which is processed using several algorithms and data tools, which in turn gives data product. Data product’s usage is for finding technical solutions to business problems.
Data science helps in various sectors and fields in daily work and life. From eCommerce, law, defense, health, entertainment to finance and investments each and every business concern need to use the data for its growth.
WHO ARE DATA SCIENTISTS?
Professionals who turn the big data into a meaningful insight are data scientists. But of course, it's not that simple. To be a data scientist one should have a background in mathematics and technology. But that's just preliminary; the most important part is to have strategic acumen. Without a strategic outlook, data product will be of no use. Business acumen helps in understanding the problem and find a workable solution to it. Whether to attract or retain customers or to optimize the processes of the business like supply chain and stock holding.
Other than just technical knowledge one also should have the mindset to be a data scientist. That is to have an intellectual curiosity to ask new questions and make new discoveries. One should be able to uncover the truth hidden beneath high stacks of raw data.
HOW TO BE A DATA SCIENTIST?
Demand for data scientists is exponential today. It's the up and coming career choice for many tech students and professionals. Higher demand means a higher number of opportunities, but that also leads to higher competition. So to succeed in such competition, one should be trained properly and in the right direction.
Having hundreds and thousands of certification courses to choose from, it might get really confusing. So one should have their priorities set like what they want to learn, how much they want to invest and what their expectations are in the long run. Usually, certification courses teach R programming, tableau training, data mining, Python, machine learning, etc.
Select a course, and work hard on it, and gain real-world experience because that's the most important facet of any training.
RESOURCE BOX:
You think you have the acuity and perseverance needed to become a data scientist and work on predicting the future. If so, then choose the best to reach your goal. Here data science certification in Mumbai gets an idea of the vast and prolific options one can have.
No comments:
Post a Comment