Ever wondered how Google, Yahoo, and other search engines pull out information from the millions of websites online? How advertising companies always know what’s on your shopping list and target you with the perfect ads that will sway make you click? Or how websites that let you compare prices of products or hotels so that you can get the best deals, get all the information? The answer is quite simple, data analysis.
What is data analysis?
Data science is an umbrella term for research, collection, sorting and presenting data in a pleasing and more understandable manner. Algorithms search for defined patterns within given parameters and provide available data in a more relevant and understandable form. This data is later compiled and structured into a simpler form that suits research. As we move into a digital era where numbers are necessary to prove one’s point, the necessity of data science has been increasing.
What does a data scientist do?
A data scientist is tasked with the job of filtering through piles of information by utilizing algorithms more sorted for usage. Patterns are found within this data to provide a correlation for easier representation. They can sometimes be essential to trap and verify errors in the information that they have acquired while figuring out algorithms that help in storage of this information along with big data. They are required to be adept with software, statistics and need to have the trait of persistence. Their final step is to present all the data, with the help of the patterns found, in a more meaningful manner to make sense to the layman.
What do you need to be a data scientist?
Apart from your technical knowledge, a data scientist must be curious and thirsty to know more. There is so much data that a data scientist had to go through that it often helps if they are the kind of individual who wants to know more.
They need to have great organizational skills that would help them in sorting and arranging data for further use.
Scavenging for data and patterns that may make sense in any way can be tiresome and an exhausting job. Being a bit stubborn might do the trick and help through the stage of boredom, that may later lead to the final wonderful moment.
How to become a data scientist?
As the importance of the job increases, so does the complexity. A data scientist requires adept knowledge in maths, statistics, business and software. Few essential languages are SQL and python. Renowned training institutes that teach data science and the essentials like math, stats and coding are springing up everywhere. They also assist in placements with firms post the training period. Institutes provide adequate education in the field while keeping the classes open minded and free for enquiry.
What are the job opportunities?
Post your course, you can apply for the post of statistician, business intelligence reporting, data analysis, data mining or a big data engineer, program or a project manager. Some prospects may lead you to other countries with salaries as big as 110,000 USD a year.