Things You Should Know For A Career In Data Analysis

This article is sponsored by Simplilearn.


Did you know that there are 60,000 searches on Google every second? Right now, every human on the Earth is generating 1.7 megabytes of data every second! With such an upsurge in data, the demand for data analysts, data scientists, and other data professionals is growing day by day. Every industry and sector requires data analysts and data scientists to make sense of all this data. Be it the healthcare sector or the automobile industry, every organization wants to use this data to improve decisions and increase profitability.

If you are someone who is looking forward to starting their career in data science and analytics, there are a couple of things that you should know – 

  1. You should know how to code

If you want to become a data analyst, you should have a thorough knowledge of programming languages such as SQL, R, and Python, tools like Excel, Tableau, Hadoop, and Microsoft Power BI. Keep in mind that data analytics is a different discipline than computer science. You do not need to be a pro in computer science to become a data analyst. Pursuing Data Analytics courses online wherein you can learn these skills, as well as work on real projects, can help you enhance your skills and your portfolio.

  1. You should love numbers

Data analytics is all about numbers. A data analyst should like and be good at working with numbers. The most important job that a data analyst does is to use statistical techniques on data and then present those insights in the form of a simple story to the decision-makers. If you do not love numbers or work with numbers, then data analysis is not the right career path for you.

  1. Communication skills are also important

Apart from technical skills, it is also important to possess communication skills. A data analyst should be able to visually communicate their findings from the analysis in the form of charts, reports, and graphs. If you are comfortable working with datasets, collecting valuable insights from them, using statistical techniques and models, and presenting them in a manner that would help people from a non-quantitative or a non-technical background understand these findings, then you would be perfect for this career path.

  1. Importance of Projects

You may be overestimating the value of your degrees and certifications. To apply the theoretical data analytics concepts that you have learned in your degree or certification program, you should build your portfolio by working on real projects. You can opt to work on online tutorials and premade projects to apply those theoretical concepts without investing too much money.

  1. Data analytics is not similar to the “IT” or “Computer science” industry 

You may be an IT professional with work experience in the information technology or computer science industry, but in the field of data analytics, you might just be a fresher. The best way to not start right at the bottom and leverage the experience that you already have is by getting hands-on experience through projects, contests, or hackathons. This shows that you have worked on real data sets and not showcase you as a newbie to the field of analytics.

  1. Data analytics is here to stay

With every new trend or technology, it so happens that there is a rise before there is a fall, but that will not be the case with data analytics. This field is not just a trend; it is the future. Data is like the “oil” of the 21st century. In fact, data analysis has been around since long before it became the buzzword of the century. Data is being collected and utilized from everywhere – even the smallest of things like a cab ride.

  1. Data analytics is important for each industry

As data is rising, the need for businesses to become data-driven and data-dependent is also rising. Hence the demand for data analytics professionals is also growing immensely. Having a background in analytics can help your career, whether you work in the commerce, business, or engineering industry.

  1. Different domains require different kinds of data analysis

Analytics is all about combining analytical skills with the skills of each different domain. For example, if the domain is human resources, then data analytics in this domain would be human resource analytics. Thus, you should upskill yourself in analytics pertaining to the domain you want to work in.

  1. Understanding the job market

Before you decide the domain or industry that you want to work in, you need to understand the job market thoroughly. With proper research done in advance, you will have an advantage over others to land your desired job role. You need to be aware of the latest market trends since data analytics is a constantly evolving field.

  1. Learn to swim before you dive

This is a very famous saying. With respect to data analytics, individuals who are thinking of making a switch in the field or thinking about starting their career in data analytics often think that they will change the future and be geniuses that build robotic technologies. Before you reach that level, it is important to master data analytics fundamentals and be completely well-versed with the field.

  1. Big data is a subset of data analytics

It might seem like big data is a technology of its own, but actually, it is a subsection of analytics. When huge data sets, which are much bigger as compared to the conventional data sets, are being considered, big data analytics comes into play. Since the volume of data is so big, the techniques of data handling, management, storage, and analysis change in this scenario, but the core concepts remain the same.

  1. Average salary of an entry-level data analyst

An entry-level data analyst can expect to earn somewhere between Rs. 1,72,794 and Rs. 7,16,015.

Once you know all these factors, you can make an informed decision about entering the field of data analytics and fulfil all the prerequisites.

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