Break into One of Today’s Most Popular Professions: Data Analytics

How to make a career change into the world of big data, business intelligence and analytics.

Dreaming of a career in data analytics? Or are you already in the role but looking to progress? Your goal isn’t out of reach if you arm yourself with knowledge and focus on your strengths and interests. The following steps and explanations can help.

1. Understand the terminology

Analytics is not synonymous with “business intelligence” or ” big data.” To clarify, business intelligence shows how a business system is operating today, while analytics focuses on how to improve that system for tomorrow. Business intelligence covers all aspects of a user’s interaction with a system—from collecting data to accessing it. That data is then tapped into via reports and graphical dashboards. Typical tools used are data solutions such as Teradata, Hadoop and Oracle.

Analytics professionals process data derived from business intelligence, and deliver insights that help drive business decisions. This can improve revenue, streamline operations or help identify other opportunities to enhance the system’s performance. The tools used for analytics include SAS, R and Excel.

“Big data,” however, is another story. Ever-increasing volumes, variety and velocity of data (the “three Vs”) create issues for data storage and visualization that destabilize traditional business intelligence systems. Therefore, big data is a business intelligence issue, not a data analytics issue.

As you formulate your career plan, it’s important to scrutinize job titles and descriptions to better understand whether you are pursuing the path right for you. Remember: A big data job is not an analytics job.

2. Assess your interests and aptitude

Analytics jobs may pique your interest, but it’s critical that you seek the position best suited for your skillset. Ensure your compatibility with a career in this field by assessing your own analytics aptitude.

Do some research on job sites like Ladders, using keywords such as ” Analyst,” “Analytics,” and “Data Scientist,” and carefully read each job description. An analyst job that doesn’t explicitly mention analyzing data in the job description isn’t a data analytics position.


The graphic here helps you zero in on the positions that match your objectives. Common analytics job titles are divided into which category they generally fall under: Business analytics, predictive analytics, and data analysis.

Let’s look at Marketing Analyst jobs in the chart. Most marketing analyst positions fall in the Business Analytics Professional job category, but some require advanced analytics skills, which makes them fall under the Predictive Analytics Professional category. “Data scientist,” on the other hand, is a title used broadly, and these jobs can fall under all three categories.

The categories themselves—Data Analyst, Business Analytics Professional and Predictive Analytics Professional—require different analytics skillsets. The table below identifies typical skills needed for each category.


3. Target your dream jobs

It is easier to transition into a data analyst position if you have prior experience in data structure, informational management, data architecture, or other engineering areas. If you have business background (product management, project management, MBAs) consider a business analytics job. If you have experience in statistics, operations research, computer science or algorithms, a predictive analytics job may suit you.


Review job descriptions online, and note the skills and tools required for each position. Check the tables above to identify the job categories that position falls under. Given your background, interests and industry experience, identify your dream analytics job title from within the job categories appropriate for you.

4. Seek out tools to help you achieve your objectives

Working toward your dream job doesn’t mean going it alone – there are many resources you can use to break into the field. For example, tools like SQL and R can be learned for FREE or fairly inexpensively at Coursera, Udacity or SQLCourse. For the data-to-decisions mindset, we highly recommend taking Aryng’s Analytics Career Transition packages. These include an assessment, complete hands-on business analytics and testing training, experience with a real-time project, mentoring sessions and optional career coaching to help you find and secure your analytics dream job. You can also learn more about our fundamental approaches to analytics or about our “Data to Decisions” framework by downloading one of Aryng’s analytics whitepapers.

Good luck with your job search. You’re already taking the hardest step—understanding the analytics landscape and identifying which jobs are right for you.