We’ve all heard of data science. You know, it’s that field that makes the most out of scientific methods, algorithms and systems to cite knowledge and details from data in many forms. It’s quite similar to data mining. It is used to understand and analyze some actual phenomena by using data.
We’ve compiled a list of skills you need to have in order to become a Data Scientist. There are five of them and they are crucial in this field.
About 88% of the data scientists have at least a Master’s degree, and 46% have a Ph.D. A strong educational background is required for you to become a data scientist.
In order for you to pursue your dream and become a data scientist, you can earn a Bachelor’s degree in Social sciences, Computer science, Statistics or Physical sciences. The most common out of these ones is Statistics, with 32%, Computer science, with 19% and Engineering, with 16%. But sometimes it’s still not enough.
As said earlier, most of them have a Master’s degree or a Ph.D. and they also take online training to learn some of the skills. But the skills you acquire during your degree program should be enough for you to make the transition to this field, to data science.
You need to know some of the analytical tools, and for data science, R is the one, as it was specifically designed for data science. This program is what can solve any problem in this field.. About 43% of the people use R to solve statistical issues.
The thing with R programming is that it’s hard to learn, especially if you’re mastering a programming language. However, you can start learning it online. It will take some time, but it’s worth it.
The most common coding language used is Python and it’s usually required in data science, together with Perl, Java and C/C++.
Data sciences have specific processes, and almost all of the steps use Python. It may take some formats of data and you could import SQL tables into your code.
We must say, it’s not really a requirement, but it won’t ruin anything. Also, experience with Pig or Hive is good. Cloud tools, like Amazon S3 is also something that comes right on time. Hadoop turned out to be the second most important skill that a data scientist should possess.
When you’re a data scientist, you can come to situations like those when the amount of data you have actually exceeded the memory of your system. In this cases, you might need to send the data to a different server, and this is how we meet Hadoop. Hadoop is often used to carry data to different points on a system. It’s also used for summarization, data filtration and exploration, as well as data sampling.
NoSQL and Hadoop are now the most popular ones in data science, but it’s still required for the people to know how to work in SQL (which is short for structured query language). This one is a programming language that works with operations such as adding, deleting and extracting data from a certain database. It also works with analytical functions and it transforms database structures.
SQL was designed specifically to help you work on data. It offers you important details when it comes to questioning a database. Its commands are concise and can help you in saving time. By learning SQL, you’ll get to understand databases better and you’ll get important experience as a data scientist.
Laura grew up in a small town in northern Quebec. She studied chemistry in college, graduated, and married her husband one month later. They were then blessed with two baby boys within the first four years of marriage. Having babies gave their family a desire to return to the old paths – to nourish their family with traditional, homegrown foods; rid their home of toxic chemicals and petroleum products; and give their boys a chance to know a simple, sustainable way of life. They are currently building a homestead from scratch on two little acres in central Texas. There’s a lot to be done to become somewhat self-sufficient, but they are debt-free and get to spend their days living this simple, good life together with their five young children. Laura is an advocate for people with disabilities.