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Data Industry is on boom today and it seems no shortage of intelligent opinions about the job responsibilities and roles accelerating the data industry. Most of the people are usually confused between the role of a Data Scientist and the Data Analyst. Even if both of them deal with Data only still there are plenty of significant differences that make them suitable for different job positions.
Here, we will discuss how to differentiate Data Scientist from Data Analyst, and their job roles too. Before we switch on the actual topic, let us have a quick look at history, how Data science became so popular in a short time only and how it can help some organization growing exponentially through a quick decision-making process.
Business analytics, concept is in existence around us for more than 32 years with the launch of Microsoft Excel Software in 1985. Before the invention of the Software, business analytics was a manual exercise and highly annoying too. We should give special thanks to Microsoft Excel Software that has been accelerated business analytics wave.
Two major factors contributed immensely to the success of Data Science Phenomenon. First is technology advancement in different phases and another contributing factor is the Internet that helps in large Data collection from reputed web sources. This results ina collection of voluminous data that was not possible to collect a few years back. Companies now have a platform that can be used for quick and effective decision making.
As we have discussed already, voluminous data seems really effective for businesses when used efficiently. You can make quick decisions and act accordingly. To make this data more meaningful, we need a person with skills set like Data visualization, Data interpretation, Maths, Statistics, Machine learning skills, business insights and much more.
This was the reason the role of Data scientists and Data analysts came into existence. They are not only responsible for meaningful business insights, but accelerate business decisions too for exponential growth. Within a few years, Data analysts or Data scientists become the most glamorized profession in the world with attractive salary options and celebrated career choices too.
There are plenty of similar definitions revolving around the Internet, but not all of them are accurate. The reason for the difference is job roles defined by the Companies are usually confusing and they are not clear by the HR manager. Many of the people think that Data Scientist is just a fancy word for Data Analysts. But this is not true as each of them has different job roles and responsibilities.
Today, both have become hot career choices in the big data world. Now let us come on the actual topic how Data Scientists and Data Analysts are different from each other. Based on our discussion, you would not only be able to determine the differences, but you can quickly decide on your best career choice too.
The skills for both Data scientists and Data analysts do overlap but there are significant differences to help you in getting the idea more precisely. Both of them should have basic knowledge of Mathematics and Algorithms, software engineering, and good communication skills too.
How are they different from each other in the matter of skills? Data analysts are master of SQL and use regular expressions frequently to solve any database query. A data scientist, on the other hand, possesses strong skills in statistical modeling, business acumen, business analytics, and computer science. Data scientists find out best possible ways that help some organization in meeting tough business challenges. This is the reason why Data Scientists ate taken superior in every prospect as compared to Data analysts.
Data Scientists and Data analysts are further divided into four categories based on their job roles and responsibilities
Based on the job role, Data Scientists usually enjoy the higher salary experience when compared to Data Analysts. Here, we have given the idea on median salary based on global survey. Regardless the differences between two, one is incomplete without the other. This is the right time to master Data Science skills in the year 2017-2018. Get started with certified project-based data science training with JanBask Training now!
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