Hello, 

These are the three steps to launching a data analyst career
Step 1: Earn a bachelor’s degree in information technology, computer science, or statistics
Minor or study applied statistics or data analysis. Also take computer science classes that emphasize project management and database management. Find an advisor or career counselor that is familiar with a data analyst career path.
Step 2: Gain data analyst experience
It is difficult to gain employment as a data analyst if you do not have any experience. Interning while in school is a good way to gain valuable experience and will help with insights about additional skill development and training. Even still, most people in technical careers start at entry level positions in this case including positions such as a statistical assistant or technician. These jobs will provide valuable on-the-job training and experience. Take as many in-house training classes as possible, especially ones about analytical software programs and big data management. Experience, knowledge, and willingness to learn will help you rise to the level you desire.
Step 3: Advancing your career – consider a master’s degree or certificate program
An advanced degree will offer more job opportunities and ways to advance your career. Employers want candidates to have an array of knowledge and be familiar with the latest technologies and tools. Consider a master’s degree in data science, data analytics or big data management. These programs will generally provide exposure to the newest software programs from experts in field. Many universities partner with corporations to create team assignments, internships, and capstone projects: which will gain invaluable real world experience while earning an advanced degree.

This is what a Data analyst does in simple terms:

• Figure out what questions are being asked and figure out if those questions can be answered by data.
• Determine technical issues with collecting and analyzing data, and design reports.
• Identify new sources of data and methods to improve data collection, analysis, and reporting.
• Collect, analyze, and report data to meet business needs.
• Distinguish trends and patterns.
• Report data in a comprehensive and repeatable way.

Hope this helps.....