Data Scientist: What Is It and How to Become One?
Recently companies have started to gather data in large volumes in order to understand their product development, public response and optimize their marketing strategies. Here the role of a data scientist comes into play. They are the people who actually deal with these huge sets of data and analyze them in order to understand the trends of the market.
This article is to shed some light on what is data science and how to become a data scientist.
What Is Data Science and What Does A Data Scientist Do?
Data science is the field of studying and analyzing data to find out the different trends or patterns in them.
The people who deal with the data are called data scientists. They are supposed to come up with optimum solutions to the company after recognizing the data trends and how it is affecting the business or the company. A data scientist is also supposed to develop algorithms for a better analysis of the data.
A data scientist is supposed to be good in mathematics, statistics, computer science, and programming, along with it he or she also needs to have a better understanding of the business, great communication skills and a good grip in pattern recognition.
What Are the Skills You Need, To Become A Data Scientist?
Here are some of the skills that you need to master in order to become a good data scientist.
Have Proper Database Knowledge
A data scientist needs to know all about database management which also constitutes analyzing tools like Oracle, Microsoft, MySQL, etc.
Need to Be Good in Statistics, Math, And Programming
As mentioned above, in order to become a good data scientist, one needs to have a proper understanding of the subjects like statistics, mathematics, and mathematical analysis. Only if you have a master's degree or a Ph.D. degree in these subjects then only you can properly understand the nature of the data and its trends.
Also, proper knowledge in different or at least one programming language is a must in the sector of data science
Data Wrangling
You need to learn data wrangling in this field. Data wrangling basically deals with the cleaning, manipulation, and organization of the data. Flume, scoop, R, Python are some of the tools used for data wrangling.
Machine Learning
One needs to be very much acquainted with the algorithms of machine learning. Machine learning is a new concept but a very powerful one used in data science where the programs or systems are made capable of automatically learning from experienced data sets.
Big Data Tools
A data scientist needs to have proper working knowledge in big data tools like Hadoop, Talend, Apache-spark, etc. These big data tools are necessary for handling huge and complicated data sets that can’t be dealt with the traditional data processing software.
Need to Visualize Results
Data visualization is a must requirement for any data scientist. It is very critical in order to understand the trends in the data sets.
Conclusion!