In the day and age of Big Data, gathering data and information is not difficult anymore. Experts will tell you that data has become the new currency for businesses. However, data analysis is as critical as data collection, and that’s why companies are always on the lookout for qualified data analysts . Companies need data analysts to help them derive insights from the data sets collected to improve productivity and profits and resolve underlying issues. A data analyst is responsible for identifying drawbacks in business operations and devising solutions to improve efficiency. This job role is valuable for a company, and depending on the industry’s requirements, people with varied skill sets are considered for such positions. A data analytics career can hence offer lucrative and fulfilling jobs to people from various backgrounds.
Given the significance of the job role, applicants making a career transition to data analytics should consider some critical aspects to be successful. These include:
● Gauging the level of seniority to apply for.
● Identifying the level of technicality one can handle.
● Avoiding the common mistakes people make while switching over to data analytics.
As a fresher in the field of data analytics, you must be cautious. Here are some of the common oversights you should avoid:
● Not applying concepts while solving sample problems: While starting a career in data analytics, you need to have a clear understanding of this field’s theoretical ideas. However, gaining practical experience is equally essential. Practicing sample data sets, learning patterns, and deriving your conclusions will help you better understand concepts and farewell in interviews.
To get more practical experience, apply for courses that offer a mix of theoretical and practical knowledge, and focus on practicing SQL-based problems. You can also work with tools such as Microsoft Excel, or BI (business intelligence) tools like PowerBI, FineReport, and Tableau. Also, regularly working with programming languages like Python and R, can sharpen your critical thinking and data visualization skills.
● Not networking with professionals in the field: Networking is essential – it can help you get quick and reliable access to industry insights and other updates.
To network better, socialize with the other students in your learning program or refer to websites such as LinkedIn and join communities consisting of people from your field. You can also look for a mentor who could guide you through the process of becoming a successful data analyst.
● Focusing too much on technical jargon in your resume: Data analysis process requires problem-solving skills and managerial expertise, apart from the technical skills. This is because a business can face varied problems, and it would be the job of a data analyst to identify them. Recruiters do, therefore, look for such skills and experience in an applicant’s resume.
Mention only the most essential data analytics projects that you have worked on, in your resume. Also, add other skills that you would have learned in your previous work experience/s – that will give you an edge. The right kind of resume is critical for getting the right data analytics job.
● Not researching for the right job role: People often don’t research thoroughly and go by job titles only. Many job titles might not contain the word ‘analyst’ although the job description would be similar to that of a data analyst. For example, roles like a market researcher, database administrator, or technical support associate require data analysis skills but do not specify it in the designation.
Therefore, go through the detailed job descriptions before you decide on any profile. Be familiar with the responsibilities of a data analyst and the industries which frequently employ data analysts so that you can identify the job role that is perfect for you. Thorough research can certainly point you in the right direction on your data analytics career path.
● Not improving your communication and presentation skills: Communication and presentation skills are as important as the technical aspect of a data analyst’s job. You should comprehensively present data and insights and simply communicate things. This is because the people you would be showing your findings might not be well-versed in the technical terms.
To learn or sharpen your presentation and communication skills, you can talk to your mentors, learn Microsoft PowerPoint or other such presentation software, and practice presenting sample projects with them. Moreover, participate in discussions on websites like LinkedIn as it will help widen your horizons.
Common Mistakes that Seasoned Professionals Make and How to Avoid Them
Experienced professionals should avoid making these mistakes while career transitioning in data analytics:
● Ignoring the business aspect: You should understand that a data analyst is responsible for identifying the inefficiencies of a business and their primary job role is to suggest relevant solutions. Therefore, you must have a clear understanding of your prospective employer and the industry they operate in.
To gain a deeper understanding of a company, research well – check out past and recent projects, goals, and key areas of work. If possible, get in touch with the focus company’s employees and ask for assistance.
● Not focusing enough on foundational skills: Building the right foundation for a data analytics career is essential to sustain it. Polish your primary skills and revisit your basics. This will make your understanding of the theoretical and practical concepts stronger.
To improve your basics, you can start by gaining expertise in programming languages like Python and improving critical thinking skills. Our blog on much-needed data analytics skills can help you identify the skills you should focus on. You can also practice working on data analytics tools or BI (business intelligence) tools, and refer to the notable projects in this field to get an idea of the skills and concepts used there.
● Not trying to upskill: Learning to upskill can be a crucial part of a data analyst’s career as it helps you stay abreast with the new developments in the industry. Hence, you must be open to learning and upskilling. Along with perfecting your skillsets, it will show your employer that you are free to new opportunities and put in your effort to achieve the organization’s goals.
For professionals making a career transition from a non-technical field, taking up a mentor-led program is highly recommended. It will help you transition into a data analytics career smoothly. A mentor will clarify the basics of data analytics in detail for you and resolve your queries with practical examples.
● Not keeping up-to-date with recent developments: You should always focus on researching and staying updated with data analytics developments as it is an evolving field. When you analyze well, you identify opportunities in job roles and industries you may not have considered before.
Research online, refer to the projects that individual companies are taking up, and network actively. You can also refer to portals like data economy that provide news and updates related to technology. Make it a habit to read and research as it will help you stay relevant and increase your knowledge to have a successful data analytics career.
How to Find the Right Job Role?
To start your career in data analytics, first, understand the job role you want. You can get an entry-level job or a senior-level job (mid or supervisory level) depending on your experience and qualifications. If you have just graduated or are working as an associate in some other field, you should consider starting your data analytics career path with an entry-level job. Once you gain some experience, plan for career progression.
Moreover, different job roles require different levels of technical knowledge. You can apply for a job that requires you to manage clients or answer customer queries about products, based on data. If you want to opt for something more technical, look for profiles like risk analyst and security program analyst. There are several exciting data analytics jobs available on Indeed, which shows that the demand for reliable professionals in the field is increasing. So, you can select a role best suited to your skills and interest areas.
For instance, if you have a marketing background, you can apply for a market researcher’s position after completing your data analyst training. Suppose you have technical proficiency in data analysis. In that case, the prominent data analyst can be an exciting role for you as in this profile; you can put your technical knowledge to fair use. Likewise, in an intermediate data analyst role, you can work as an analyst while also focusing on business, and get good experience in both business and technology. After exploring and developing an understanding of your strengths and interests, you can move on to technical or strategic roles.
Once you have researched thoroughly and are ready to make a career transition, apply for a training or learning program in data analytics. Also, start networking with others from the field and keep yourself updated with the latest advancements. To make your career transition smooth, keep an eye out for the mistakes people make and try to avoid them.
Now that you are aware of the common mistakes people make in their data analytics career transition, try to avoid them using the tips mentioned above. Revisiting your basics regularly, understanding the business goals, and staying updated on your industry’s developments will ensure that you make consistent progress in your career transition. Moreover, do not hesitate to take help from your mentor, networking community, or fellow students in your learning program if