In the day and age of Big Data, gathering data and information is not difficult anymore. In fact, experts will tell you that data has become the new currency for businesses. However, data analysis is as important 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 so that they can 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 requirement of the industry, people with varied skillsets are considered for such positions. A data analytics career can hence offer lucrative and fulfilling jobs to people from varied 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. 

Common Mistakes to Avoid at the Entry Level of Your Data Analytics Career  

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 the theoretical concepts of this field. However, gaining practical experience is equally essential. Practising on sample data sets, understanding patterns and deriving your own conclusions will help you get a better understanding of concepts and also fare well in interviews.  

    To get more practical experience, apply for courses that offer a mix of theoretical and practical knowledge, and focus on practising 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 visualisation skills.
  • Not networking with professionals in the field: Networking is very essential – it can help you get quick and reliable access to industry insights and other updates.  

    To network better, socialise 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 important data analytics projects that you have worked on, in your resume. Also, add other skills that you would have learnt 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 jobs titles might not contain the word ‘analyst’ although the job description would be similar to that of a data analyst. For example, roles like 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 be able to present data and insights in a comprehensive manner and communicate things in a simple way. This is because the people you would be presenting your findings to might not be well versed with 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 practise 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 business and their major 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, their 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 skills like critical thinking. Our blog on much needed data analytics skills can help you identify the skills you should focus on. You can also practise 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 very 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 open to new opportunities and will put in your effort to achieve the organisation’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 easily, as a mentor will be able to 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 the developments in data analytics as it is an evolving field. When you research well, you identify opportunities in terms of job roles and industries that you may not have considered before.

    Research online, refer to the projects that certain companies are taking up and network actively. You can also refer to portals like dataconomy 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 so that you can 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 interesting data analytics jobs available on Indeed as well, 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 background in marketing, you can apply for the position of a market researcher, after completing your data analyst training. If you have technical proficiency in data analysis, big data analyst can be an interesting role for you as in this profile you can put your technical knowledge to good use. Likewise, in an intermediate data analyst role, you can work as an analyst while also focusing on business, and get proper experience in both business and technology. After you have explored and developed 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 that 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 of your mentor, networking community or fellow students in your learning program if you face difficulties in this process.   

Springboard’s 1:1 mentor-led, project-driven data analytics career track program can help you transition smoothly into this field. At Springboard, you can find an industry SME as a mentor who will guide you throughout your learning journey while helping you improve your skills through project-based learning. This program also comes with a job guarantee upon completion of the program. Check out the program now to get a step closer to your dream career.