How to become a data analyst with no experience?

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As the field of data science is growing day by day so is the demand for data scientists and data analysts increasing. Many individuals from students to professionals are keen on entering data science in some way or the other. Lucrative salaries topped with immense hike are the factors which students consider before shortlisting a course for them. Getting a certification before working as a data analyst would help in providing theoretical as well as practical knowledge needed for the job.

What does a data analyst do?

Data is collected by companies on every business activity from operational costs to inventory and supply data. But in order to get useful insights from this data, they need to hire a data analyst. The work of a data analyst is to analyze data related to products, customer interactions and performance and get valuable information from it.

The important duties of a data analyst are:

  • Collection of data through surveys, tracking of web analytics and buying datasets
  • Identification of data errors and correction of those errors. Ensuring consistency in maintaining accuracy interpretations.
  • To design database structures and then determine how to store and compare data categories.
  • To look for trends and patterns and then converting to valuable insights.
  • Finding connections with the interpreted data in relation to a business and how it will prove of benefit to the company.
  • The presentation of data to stakeholders, clients and colleagues.

Qualifications for a data analyst

Most of the data analysts pursue professional degree or certification for getting more knowledge about the role. It also helps in better job opportunities. A student can either pursue a Bachelor’s degree in math, computer science, statistics, business or science. Or they can also opt for a professional certificate program which provides the flexibility to choose their routine.

However, it is not necessary for a data analyst to have a professional degree or certification. It is the technical skills that they have and the ability to solve problems is what matters.

Skills required by a data analyst

The work of a data analyst is crucial to any business. The valuable insights provided by them from raw data helps businesses in taking better decisions. Listed below are the skills that a good data analyst should possess:

  1. Data Analysts make use of programming languages to analyzing and interpreting the data.
  2. Various software tools like Google sheets and excel are a must for data analysts. SQL is a more advanced tool that will further help and make their job easier.
  3. It is the job of data analyst to make complex data legible. Therefore, good communication skills are a must for this role.
  4. To have extensive understanding of math and statistics.

How to Become a Data Analyst with No Experience?

Even if you are not keen on taking up a certification or degree but still want to make a career as a data analyst, here is what you can do:

  • Learn data analysis through self-study

    : If you have that discipline and determination, it is not at all difficult to study a course online. With everything from videos to theoretical knowledge available on the internet, learning has become a lot easier. Some of the skills that you need to study thoroughly include Python, R, data visualization, Statistics, and SQL.

  • Work on data analytics projects:

    Once you are done with the all the technical skills, it is important for you to take up hands on projects. A data analyst certification will help you for the same. Ensure that the certification course allows you to design different data projects and present your findings.

  • Create a portfolio:

    After getting experience on practical skills as well as theoretical knowledge, you should consider making an impressive portfolio. It is with the help of your portfolio that employers will get to know about your abilities and that you are capable enough to take up the job of data analyst.

  • Apply for entry level data analyst jobs:

    Update your resume and include everything in your portfolio to apply for internships and jobs. Reach out to network that you have built while working on your projects, self-study and courses.

Becoming a data analyst and how much time it takes for getting a job depends entirely on you and your commitment.

Is the job of a data analyst lucrative enough?

Yes for sure, the job of a data analyst offers good growth prospects. And it is not necessary to have a certification or a degree for this role. All you need are the right technical skills and practical application of the knowledge that you have. The salary of a data analyst varies from $65,000 – $86,000 in the US. The job opportunity for data analyst is likely to grow by over 20% in coming years.

Right from entry level to senior level, the requirement of data analyst is increasing. With competitive salaries on offer many individuals are attracted on pursuing a career in this field. Expertise in programming, machine learning and data visualization are the deciding factors of average salary of a data analyst. A potential data analyst candidate will have experience over tools like Python, R, SAAS, Excel and Tableau.

No matter what job you may take up, every opportunity has its set of tasks and problems. If you are smart enough to acquire all the necessary skills and show them to your prospective employer, there is nothing to stop you from making a successful career in that field. Have confidence in yourself, do some research and look for ways in acquiring the skills to help in your job. Be positive and take that first step towards your data analytics journey. You need to invest time in understanding the organization’s data needs and then make use of various tools in the market to give out the data which would help the business. Choose to take a structured route by opting for a degree or go ahead with self-study and hone your skills.

If you like more information on data science topics like DATA SCIENCE CERTIFICATION AND ITS BENEFITS read the link and Developing a data-driven hiring strategy

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