Top Five skills that you Need to become a Data Scientist
Following are the five skills that are needed to become a data scientist.
1. Analysis of data (Analytical skills)
2. Programming skills
3. Business skills
4. Communication skills
5. Visualization skills
1. Analysis of Data: It plays a crucial part for data scientists. In order to analyse this, larger part of data is to be broken in to smaller parts.
Figure: Flow chart for data analysis
The ability to understand the data is based on knowledge, clear thinking and logic. Primarily, education is the major part of the data scientist. Usually, very strong depth knowledge is required for data scientists. So, one who wants to become a data scientist must and should be well educated. This education may be the study of mathematics, statistics, computers and various engineering. The analytical tools like R and SAS are preferred for data science. Thus, they should be learned.
Data analysts follow following factors:
Data analysis includes cleaning data, creating models, applying statics on data, validating models.
2. Programming Skills
There are various programming skills a data scientist should get in to it.
Coding of Python: It is the one of the most important coding language besides JAVA, C, C++, DOT NET, ORACLE, COBAL etc, in data sciences.
SQL: In order to execute complex quires in data sciences SQL is required.
Unstructured Data: Sometimes, data scientist has to work with unstructured data. So, they should have knowledge on social media, blogs, videos, audios, etc.
Some other programming skills relevant to industry i.e., familiar with HTML or CSS in the case of web industry.
Data analysis platform like R, SASM, SPSS, and MATLAB are specialized in these programming skills.
In many cases, Hadoop platform is largely preferred. Tool like Amazon S3 is an advantage in this platform.
Figure: Programming languages representation in Venn diagram
3. Business Skills: It falls under the category of non-technical skills. The one who want to become a data scientist should have a depth knowledge on the industry in which, they are working and should know the problems of the company. If once they came to know about the problems, then they should think of resolving it. The data scientist must be familiar with waterfall or the agile framework. They always should have an eye for other business skills. The business analyst should have basic knowledge and future expectation of the industry.
Figure: Steps for business skills
4. Communication Skills
Now-a-days communication skill has become a hot button topic in any field. Especially, this skill has an enormous part for data scientist. Most commonly, any company looks for one who speaks clearly and fluently. As they need to translate their technical data to non-technical. Soft skills are as important as technical skills.
A person who wants to be a data scientist should be good in storytelling, listening skills, writing reports etc. Additional skills are also needed as per industries.
5. Visualization: It is incredibly important. Generally, this includes statistical graphics, web based data, Venn diagrams etc. A data scientist should be able to design a simple and meaningful visualization. Following is the visualisation of high level determination of skills needed.
In visualisation point of view, the data visualization tools like ggplot and d3.js are helpful.
In addition to above five skills there are other skills that required in data sciences. They are as follows:
Commitment, creativity, business savvy and presentation, end programming, front end programming, Product learning, Problem solving skills, Curiosity, Technology, Machine learning, algorithms proactive, collaboration etc,.