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How To Become a Research Data Analyst – A Detailed Guide

You might have come across many videos and posts on your social media feeds about this hot topic of data analyst vacancies and salaries being paid for such roles. Well, most of them speak of hypothetical data but what if I also tell you that the professional networking platform LinkedIn reported vacancies of whooping 1.09 lakhs on their platform? The numbers are really promising but let’s dig down to know the details of the Research Data Analyst you have come looking for. You might be having a lot of questions going on in your mind -How to become a Research Data Analyst? What is the ideal way to get started? Don’t worry you will have the answer to all your questions. 

 

A guide to how to become a research data analyst

 

Who is a Data Analyst?

To explain in layman’s terms, a research analyst is the one who cleans up the mess and helps in communicating with the complicated machines in the language (data) they understand. Like, a business analyst analyzes the business and helps in making the decision. As a data analyst, you will be analyzing the data to put it to good use.

 

The Job Typically Includes:

  • Gathering the data 
  • Analyzing the data – removing the clutter 
  • Present data and put it to good use

 

In the past few years, the world is moving slowly away from certification to skill-based jobs. It wouldn’t be surprising if you have been asked to produce your work on the skill you possess rather than your educational certifications. We will discuss both the parameters of how to take the role of a data analyst with or without having a professional degree. 

 

If you are looking to take up the role without the degree, we would request you drop here and continue reading from the second part. 

 

How to Become a Research Data Analyst? A Step-by-step Guide

As a data analyst, you can be a part of various industries as it is in high demand now. If you are looking to get your first job or trying to shift your career path, here are a few steps that could help you get started. 

  • Understand if it suits you
  • Start building the basic skills
  • Work as a freelancer to get better exposure
  • Create your portfolio 
  • Practice, Practice, and Practice
  • Get yourself started with an internship/full-time job
  • Certification 

 

Let’s discuss them in detail! You are with me, right? 

 

1. Understand if It Suits You

Most of the time we tend to make our career decisions based on the content we have consumed on the Internet or have known someone doing great in their particular fields. This seems to be easy to decide without having to risk trying your own hands rather than depending on someone’s suggestions who has already done it. Trust me! You may not end up making the right decision every time.

Hence, it becomes very important to understand what suits you better and what makes you happy. So, research more about the tasks you will be involved in day-to-day life, speak/connect with people on the professional network sites who have already taken up this career, and most importantly consider your present life situation. 

 

2. Start Building the Basic Skills

One of the most important things to do while finding a new job or changing your career path is to list the tools that are required. The tools here are the technical skills you need to gather.

  • Python 
  • SQL 
  • Statistics
  • Data Preparation 

 

Start accumulating knowledge about the above-mentioned skills. Most of them are available for free cost on the Internet. If you are a professional who doesn’t have much time to read through yourself, take up live classes on weekends (this will help you stay committed to the timeline and finish the required-on time rather than watching a recorded video which can lead to procrastination).

Python is a simple and beautifully designed language that is easy to understand and anyone with Zero knowledge or exposure can easily understand it. SQL on the other hand is similar to the way python is and doesn’t consume much of your time. 

 

3. Work as a Freelancer to Get Better Exposure

Once you gather a sufficient amount of knowledge on the skills we have discussed, it is always better to test your knowledge or skills by putting them to work. If you haven’t started your professional career, it is highly recommended to take any internship programs (paid/non-paid) to understand your flaws and groom yourself to be better.

If you are a working professional and do not have time to join an internship, you can test your skills by freelancing or answering technical questions on the platforms like GitHub.

 

Also Read,

 

4. Create Your Portfolio 

While a resume will have the details of your skills, the portfolio acts as proof. Hence, building a portfolio becomes most important as it showcases your work and helps the employer with the good details about your skills when they are looking for the right fit. 

 

How to Build the Portfolio?

Choose a platform to showcase your work. There are many free platforms that will help to host your portfolio. 

 

LinkedIn:

This is a great platform for all professionals. Whether you are starting your career or having a thriving career, this platform can be leveraged to show up your skills. Write a detailed explanation of the things you worked on or like working on. Also, have someone recommend you from within your network which can be a great help. 

 

GitHub:

This is an open-source community with almost 56 million developers and is another well-liked choice where you can host your portfolio for no cost. You can begin contributing data projects to a public repository after creating an account, where you can display components like your code and Jupyter Notebooks.

 

Kaggle:

The adaptable cloud platform for Jupyter Notebooks known as Kaggle can also be used as a free online portfolio for your work. You can present any data sets you’ve produced or any code you’ve developed here, as well as the outcomes of any Kaggle data science competitions in which you participate.

 

5. Practice, Practice, and Practice 

Let’s admit this, we human beings tend to forget the things that we learn or read. The only way we can keep the bar high is by practicing what we learn. Taking up a course is just 20% of the job and the rest 80% depends on how well you enhance the skills. The only way you can sharpen your skills is to practice what you have learned regularly. Take up small tasks and work on them. Test yourself to do better every day. This is the only way you can master it. 

 

6. Get Yourself Started with an Internship/full-Time Job

Since we have discussed the things required in great detail, we are at the final and most important part of finding yourself a career as a Data Analyst. According to one of the job-finding portals, here are the top companies that are looking for you:

  • Accenture
  • TCS (Tata Consultancy services)
  • Cognizant 
  • Amazon
  • Capgemini
  • Infosys
  • EY
  • Wipro and many more

 

As we are done with learning the skills, enhancing the skills and building the portfolio, it is time for the world to see what you have in your kitty. Create your profile on the job-finding portals. Most of them today are freely available.

 

7. Certification

Though the world is slowly moving away from certificates to skills. The trust factor is still attached to this small piece of paper. Hence, having a valid certificate will add great value. Also, not every employer may consider your skills without having a certificate that proves that you exhibit a skill. 

It is important to choose the best institutes or colleges that offer the course. This is one most important things out of all the steps we have discussed till now. We have curated a few best picks for you to help you reduce your research time. 

 

How to Become a Research Data Analyst? Here is the Complete Road Map

Since we have looked at the basic details of data analysis, it’s time to go through the steps of becoming a data analyst. And we will try to find an answer to the most asked question: How to become a Research Data Analyst? We will look at the details in 3 different parts which will include the prerequisites, different kinds of roles available, and job opportunities (Salary as per the industry standards). 

 

Prerequisites

Before choosing any industry, it becomes important to understand the details about the requirement that the industry might need from you as an individual. This will include the skills you need to acquire, any specific degree, or any soft skills that will add weight to your resume.

 

Mathematics and Statistics 

To start your journey as a data analyst, you need to be good at Mathematics and Statistics. If you are someone who doesn’t like numbers and hates the complications of math formulas, you will not enjoy doing your job. If you don’t have any prior exposure to these subjects, it is highly recommended to start learning these skills and acquire them which could be done in just a month. 

Most organizations/companies prefer someone who has a bachelor’s degree in the above subject. This isn’t a compulsion rather will be an advantage over the competition. 

 

Tools and Programming Languages 

You might need to learn a few new skills to race ahead of everyone and the tools or programming languages we are going to discuss might be different for each company. For example, banking-related firms can choose to pick someone better at SAS than python. Confused? Need not worry, the article further will guide you.

 

Excel:

We are in the 21st century now and we have got robots doing most of our jobs and making decisions. Technology has evolved to a great extent, but this beautiful tool remains one of the best inventions of mankind. Needless to say, you need to master excel skills to make your job easier, along with the basic skills you might have to learn the below skills to enhance the knowledge

 

  • Functions 
  • VLookUP
  • Macros & VBA
  • Charts
  • Pivot Table 

 

SQL (Structured Query Language):

A relational database’s structured query language (SQL) is a programming language used to store and process data. To store, update, remove, search for, and retrieve data from the database, utilize SQL statements. SQL can also be used to optimize and maintain database performance. A few of the important skills that you need to develop in SQL are: 

  • Aggregator functions 
  • Joins
  • Views
  • Query optimization
  • Triggers transactions

 

Programming Languages:

To become a data analyst, you need compulsorily to know the programming languages but given the cutthroat competition and bias, you need to make sure you stand out. As discussed earlier, few companies can particularly choose to pick someone based on their operational requirement. A few of the well-known programming languages you need in your kit are:

 

  • Python: Out of all the programming languages, python will be preferable for anyone who wishes to learn to program. Due to its built-in library and ease of understanding, this programming language has made its way to various applications across the industry. It is easy to learn, and you can finish the curriculum in a matter of 3 months.

 

  • R language: R might be a good fit for you if you’re passionate about the statistical computation and data visualization aspects of data analysis. 

 

  • SAS: If you are looking to start your career in a banking-related company, SAS (statistical software suite) is a language that needs to be on your list. Most banking companies like Citi bank prefer SAS over any other language as this has proven to be effective for banking transactions. 

 

Visualization Tools: 

As a data analyst, you will be dealing with a lot of data, and explaining the data over the tool using charts will be easier and more understandable. Imagine explaining the population of the countries in the world with just numbers and putting the same on the charts. Which one would be easier to understand? You are right, the charts are an easier way to analyze the data. Needless to say, to need to be an expert at using these visualization tools, to name a few:

 

  • Tableau: One of the leading visualization tools which are used for data analysis and has been named as one of the most used tools in this segment. 

 

  • Power Bi: Microsoft’s Power BI is a cloud-based business analytics tool that anybody can use to quickly and effectively view and analyze data. 

 

Hope you have added all these to your checklist. All the details we have discussed aren’t a compulsion and you need to also ensure that you will not be able to master everything. Hence, choose the one based on your requirement and comfort. 

 

Soft Skills 

When you become a data analyst along with data you will be dealing with the top hierarchy of the organization. Since you are involved in making the decision, you are expected to be a notch up in your soft skills. Needless to say, this will be a great help in clearing your interview and negotiating your salary. 

Even after having heavy baggage of skills, marketing companies may not consider someone with average soft skills. YouTube is the best source to learn soft skills free of cost. Now that we have discussed how to become a research data analyst in a detailed manner. We will move on to discuss resume building. 

 

Resume Building 

We have discussed all the technical aspects. But the most important thing to do is to show the world what skill you possess and grab the opportunity. While this is a really important thing which most of the freshers ignore or try to inflate the details which are not correct. 

As discussed earlier, there could be cases in the company could require a different set of skills they need for their operation. Hence, it becomes most important to tweak your resume when required. The cutthroat competition in the industry needs to stand apart from the crowd. 

 

Job Description and Keywords 

While applying for any job, go through the job description in great detail and try to find the keywords that are matching with your skills. For example, if you have learned the Python language, you will be mentioning the projects you have worked on and the papers you have published. Try to highlight these things which will seek the attention of the employer. 

 

Projects 

Most organizations prefer to choose folks who have practical knowledge about any subject. And any practical knowledge can only be acquired by working on the skills. Ensure you have at least two of the projects you have worked on or if you don’t have anything to put on this set of resumes, it is highly recommended to take up any projects with the help of Kaggle. 

 

Certifications 

Though we are moving away from the certifications. It is always recommended to get some certifications to rank yourself higher. LinkedIn and Google certifications are the best tools to make use of. This will be a booster to your ranking. 

 

Work Experience 

If you have already worked as a data analyst earlier, clearly mention the work experience and the technology you have worked on. For someone fresher, you can mention the internship that you have undergone.

 

Read,

 

How Do I Find a Job?

We are almost at the end of the discussion. We have discussed how to become a research data analyst. Now, we will discuss how to find yourself a job and companies which prefer a data analyst. 

 

Create Your Account on Job Portals

Create a profile of yours on any well-known job portals like LinkedIn, Shine, Monster, Naukri etc. Most of them offer free services, you can use them to apply for jobs. 

 

Referrals

If you have decided on joining any particular company you like, you can contact any of the employees who are already working in these organizations and ask them to refer you. You can contact employees through LinkedIn or any social media. 

List the Companies 

Not all companies will be looking for a data analyst. Hence, you need to ensure you are aware of the companies that are looking for you. Here are a few well-known names:

  • Mc Kinsey 
  • Bain
  • BCG
  • Deloitte
  • Accenture

 

Now that we have discussed How to become a Research Data Analyst? Let’s dive into a few of the most frequently asked questions. 

 

FAQs

 

Q1. What does a data analyst typically earn?

An annual salary of Rs. 10–12 lakh is typical for data analysts. Experiential learning makes things better. You’ll find rich possibilities fairly early in your career if you have the talent.

 

Q2. I’m an engineer; can I take a data analytics course?

Anyone from any field can take this course; there are no prerequisites. Being an engineer would be advantageous because you have studied mathematics, which forms the core of the data analytics course. Anyone, whether or not they have a degree, can take this course because the majority of them are beginner-friendly. It is advised to examine the qualifying requirements from the institute in question if you have a specific one in mind.

 

Q3. After completing the online data analytics course, what career profiles should I consider?

Data analysts have become a significant position in the current business environment. Business analysts, research analysts, project managers, and data analysts are just a few of the positions that professionals can apply for. The retail, banking, healthcare, telecommunications, e-commerce, financial, and sales sectors are the main areas that employ data analyst experts.

 

Q4. What are the ideal abilities of data analysts?

Data analysis is a process that involves analyzing and interpreting data using a variety of tools and approaches. Listed below are a few technical and soft skills needed to succeed as a data analyst.

Visualization of data.

Cleaning data

NoSQL and SQL.

Computer learning.

Algebra II and Calculus

 

Q5. How to become a Research Data Analyst with a full-time job?

Given the world is moving into digital space, this question doesn’t need to be answered specifically. Since the skill can be developed digitally, you just need to ensure that your time is being utilized effectively. 

 

Q6. How to become a Research Data Analyst as a homemaker?

Getting a few basics stronger and regular practice will ensure that you will learn efficiently. 

 

Q7.  How to become a Research Data Analyst as a student?

As a student, you might have a little hard time learning any new skills. Start your journey with a few free youtube videos and enroll yourself for suitable courses.

 

Q8. How to become a Research Data Analyst, if I don’t have any technical background?

If you don’t have a technical background, you will have to learn a few basic languages (not completely) like C, and HTML for basic understanding. Later, you can plan for full-time skill building.

 

Q9. How to become a Research Data Analyst, if I belong to a finance background?

If you want to shift your career to tech, it is always better to get the basic essentials first. Taking up the research data analyst skill isn’t recommended unless the basics are in place. 

 

Q10. How to become a Research Data Analyst, if I belong to a medical background?

If you want to shift your career to tech, it is always better to get the basic essentials first. Taking up the research data analyst skill isn’t recommended unless the basics are in place. 

 

Conclusion: 

The discipline of data analysis is expanding every day. Data analysis is being used by all firms, which is why this position is paying quite well. This field has enormous potential because it requires significantly fewer workers than there are now on the market. One can open the door to a prosperous and bright future by enrolling in an online data analysis course. The course is also becoming more and more popular among working people because it can be completed online and helps their careers. 

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