Data analytics is a branch of science that analyzes & processes raw data to gain insight for informed decision making. Most techniques used in data analytics have been automated into algorithms that process data for human consumption.

With the surge in data and its correlated fields, the job of a Data Scientist has become the most sought-after job. Data Science is predicted to grow over the next decade. It is a staggering fact that over 90% of the data in the world was generated in just 2 years.

More and more industries are becoming data hungry, and they need data to hold specialized data scientists who can craft products for the customers. About 11.5 million jobs will be created by 2026 according to U.S. Bureau of Labor Statistics.

Data Analytics is a career with great potential; organizations are turning into data analysts to examine their vast produced digital raw data.

It is projected that there will be 2.7 million more job openings in data analytics by 2020. Further research by Robert Half’s 2019 Technology Salary Guide indicates that data analytics expert have very competitive salaries; the annual pay ranges from $77,000 to $219,500. You are, therefore, safe if you are thinking of transitioning into a career in data analytics.

According to Forbes, to prepare students for the jobs in 2030, “Inject data analytics training into students’ course of study to help students master the use of data generated by AI”.  Learning data analytics can help you advance in your current profession or explore a growing field. Accelerate Change, transform business and Prepare for the Next Disruption. 

Anyone can transition into data analytics either from a technical or non-technical background since analytics skills is required in mostly all industries and job functions. Multiple jobs are mapped into analytics job category which simply means there is a role for you.

The main question is, what should you do to jumpstart your career in data analytics?

1. Understand what data analytics entails

Data analytics is a diverse field. Ensure that you learn and understand what data analytics all is about, what it entails, and the required skill set for each specialization. Also, research how data analytics is applied and implemented in diverse fields.

2. Know the must have skills

In data analytics field, the skills are divided into two categories: the hard skills and soft skills.

Hard Skills: these are considered technical skills and you should have great knowledge in leveraging the tools listed below in executing any data analytics project.

• SQL
• Advanced Excel
• Business Intelligence tool (mostly used are Tableau, power & Qlik)
• Basic Programming (Python or R)

Soft Skills: these are behavioral or personality skills

• Communication
• Presentation
• Data Storytelling
• Business Domain Knowledge
• Problem solving

3. Pick a business domain area of specialization

After being conversant with what data analytics entails, choose a domain area of specialization that interests you, and develop domain knowledge in the field you have picked. Some of the areas that you can focus on include healthcare, marketing, finance, HR, business, analytic fields.

4. Start learning to hone your skills and acquire knowledge

Decide the type of learning path you would like to follow; self-learning, instructor led, face to face bootcamp learning. You can pick any learning path that soothes your schedule, but you must stay consistent and motivate yourself towards accomplishing your goal of becoming a data analytics professional. There are a lot of free resources online to help you get started, click HERE to access some of them.

5. Work on real-world projects to hone your skills

Now that you have gained knowledge and skills in data analytics field of specialization, try to put these skills into practice. You should think of building a portfolio for yourself by working on real-world projects. You can find many great datasets to work with on Kaggle.com. You can also join local analytics meetups, connect with other analytics professional on LinkedIn and seek the help of a mentor to guide you towards advancing in your new career. Practical training enables you to sharpen your expertise. Internship is another great way to hone your skills so you can put that into consideration.

6. Apply for a real data analytics job

After completing data analytics projects or internships, you are confident that you are ready to apply for jobs. It’s time to update your resume with your skills and start applying for your dream job.

In conclusion, data analytics field has great growth opportunities & you can always switch industries, job functions, or even delve deeper into advance analytics (data science, Machine Learning, Artificial Intelligence, Deep Learning, and others).

Transitioning to a career in data analytics is not a one-night process; neither is it a lifetime process, it takes dedication and interest to achieve it. Whereas self-education in data analytics is achievable, it’s highly advisable to enroll in a training course or seek a mentor to guide you on best practices.