If you are interested in working with big data and…
A data analyst is an individual or a professional who has to work with data to provide insights. This is one of the most common and easy-to-understand definitions of data analyst available on internet. These individuals have to translate numbers into plain English. First, they take raw/unstructured data and then come up with an analysis which then produces digestible results. These results are then used by executives and other relevant personnel to make decisions.
We are living in a high technology business world where data analysts are mostly involved in many diverse projects. At one time, they might be working with Hadoop clusters, and then the other second they have to deal with cloud services. Similarly, data analysts also have to use traditional query languages or object-oriented systems for getting access to the required data. Nowadays, they even have to use smart tools and conduct data workflows. Follow here for a comprehensive career guide to get in-depth details about any career just like data analyst, data scientist, DevOps, IT Support Sepcialist etc.
Thus this shows that data analysts are becoming popular as they serve a variety of business purposes and today’s economy demands data analysts more than anyone.
Generally, a Data Analyst has to;
Data visualization is an individual’s ability to present data findings in the form of graphics or illustrations. The main reason behind making data visualizations is quite simple that is; to facilitate a better understanding of data-driven insights. Having this skill would be a plus point for a data analyst.
Data cleaning is also an important skill to possess why because when you have a cleaned dataset, which would lead to algorithms generating remarkable insights. Contrary, if you have un-cleaned data then this can make misleading patterns which can then lead a business towards mistaken conclusions. Therefore, this skill is also a necessity.
Even though it is not a required skill but taking into consideration its wide-reaching applications and usefulness, if you manage to gain a working understanding of this environment then it can boost your credibility to a great extent.
Learning Python has to be the top priority for a data analyst. Python is a high-level general purpose programming language that landed the number one spot in IEEE’s spectrum 2019 survey. It offers so many features which pertain specifically to AI. Therefore, learning this skill is also a plus point.
Just as we mentioned earlier, earning a Data Analyst certification can also help you set a great career for yourself. So we have listed down some of the worth considering certifications for you.
We believe if you pursue a career in data analysis then for sure you have a long future of steady job growth ahead.
If you are that person who wishes to work at your ease and pace, having flexible work hours and even work from home option then working as a freelancer is the best option here. Once you are done building up a client base for yourself and gain some experience (2 to 3 years at least), companies may likely start to hire you as a consultant. And know that consultants enjoy maximum work flexibility along with hefty salaries.
This is another option you can choose only if you prefer the structure and stability of working as an employee with a fixed salary. In this case, you can probably go to the post of a manager from an entry-level analyst.
The average annual salary that a data analyst can make working in the US is around $68,768.
United Kingdom:
Working as a data analyst in the UK can help you make an average annual salary of £35,834.
India:
If you are working as a data analyst in India then you can expect to make an average annual salary of ₹725,002.
Note: Reference salary data is taken from glassdoor.