Throughout the past few years, the field of data science has continued to grow and is becoming more popular. However, it is important to mention that becoming a data scientist is not easy and it is not a quick process. But if you are smart, willing to learn, and you are committed you to have what it takes.
What Is Data Science
People are often curious as to what data science is. It is best described as a role that is a combination of applied science and a data engineer. Many people that move into this role are ones of developers, statisticians, analysts as well as IT professionals. These roles are able to smoothly transition into a data science role. There are many different roles that can transfer easily into the data science position.
As a Java developer, these professionals are already familiar with software that use engineering principles. They also work on software systems that perform tasks that are very complex. Data science consists is building data products known as software systems that are all based on data and algorithms.
As a Python developer, you should already be familiar with the development of software as well as scripting. A python developer uses libraries that store data science such as NumPy and SciPy. Through Python, there are also great support systems for data science applications. Libraries such as NumPy/Scipy, Pandas, Scikitlearn are all perfect libraries to fall back on for help. There are also libraries for exploratory analysis and visualizations such as IPython and Matplotlib. There are also systems that work well with large data sets. The most popular library of this type would be Hadoop. There is much to learn when working as a Python developer but it is definitely an interesting field to work in.
Statistician And Applied Science
Data science can also be involved when working with statisticians and applied science information. If you have already been working within a position that works with statistics you have probably already been exposed to the programs you need such as Matlab or SAS. These are the tools that are used when exploring data and developing models. Much experience is needed in this background when starting out.
A business analyst can also go far in the world of data science. This is when you take the knowledge you have gained over the years and use it to fully understand how to use the data to gain insights into the business world. There are also databases and computer software that can help you as an analyst to figure this out also.
The world of science is not an easy one to work in. You need to be a person with patience, many disciplines knows the languages of programming and be able to gain the experience needed from the real world. Being able to do this takes more time than people realize and it will also take a personal investment by you. However, if you are dedicated to this position you will find that the data science field can be a very rewarding field to work in.
To find out more about how to get started in this field there are many resources that you might find to be helpful. There are books, both in-person and online classes as well as presentations. These will all be helpful to you in the beginning and give you the insight that is needed to become successful. As with any position in the real world, it is important that you stick with it and you will learn the ins and outs and be the best data scientist you can be.