Career Opportunities in Data Analysis

• If the business side of things excite you more, you could similarly explore the skills required for making. A lateral move into business analytics or business intelligence Analytics.

• if you're starting off as a junior data analyst and really like working with data lakes and big data repository's, you can acquire further expertise in these technologies and evolve your career into becoming a big data engineer.

Viewpoints: Get into Data Profession

• I was actually working on my PhD in Economics at University of Illinois, Urbana-Champaign, when a colleague of mine suggested that a master's in statistics would also be an excellent value add. That's how I got into the statistics program as well in Illinois. But once I started that, I was pretty hooked and there was no going back, so to speak. In other words, my original goal of becoming an economist actually evolved into a career filled with data, modeling, analytics, insight gathering, communication, visualization, and of course, underlying all of that data-driven problem-solving.

Viewpoints: What do Employers look for in a Data Analyst?

• I want to make sure that the information is right. Missing a deadline isn't as detrimental as a company making a multi-million dollar decision on wrong information, or someone losing their job because it wasn't pulled or it wasn't reported correctly

• I think that skill is really sought after. I think another thing that companies obviously look for when they look for a Data Analyst is fluency with numbers, ability to understand complex analysis, ability to understand AB tests and what the results of AB tests are saying, and the implication of those results

• Meaning, if there is a problem presented to a Data Analyst, they should be able to know how to tackle that problem using data in whatever format it may be sitting in, and being able to analyze it and present the insights that will then solve the problem.

The Many Paths to Data Analysis

• As you gather more work experience, you can keep advancing your knowledge and skills in specific areas, for example, Statistics, Spreadsheets, SQL, Python, Data Visualization, Problem-Solving, Storytelling, or making impactful presentations.

• You begin with the advantage of industry experience and skill yourself in other areas such as Statistics and programming, for example. If you’re currently working in a technical role, you have the ability to quickly pick up the tools and software you need for the data analyst role

• Data Analysis is a fast-moving field. If you’re curious, open to learning new things, and excited about the field, you will be able to forge a path forward, regardless of the formal qualifications you think you may be missing.

In this lesson, you have learned the following information:

Data Analyst roles are sought after in every industry, be it Banking and Finance, Insurance, Healthcare, Retail, or Information Technology.

Currently, the demand for skilled data analysts far outweighs the supply, which means companies are willing to pay a premium to hire skilled data analysts.

Data Analyst job roles can be broadly classified as follows:

Data Analyst Specialist roles - On this path, you start as a Junior Data Analyst and move up to the level of a Principal Analyst by continually advancing your technical, statistical, and analytical skills from a foundational level to an expert level.

Domain Specialist roles - These roles are for you if you have acquired specialization in a specific domain and want to work your way up to be seen as an authority in your domain.

Analytics-enabled job roles - These roles include jobs where having analytic skills can up-level your performance and differentiate you from your peers.

Other Data Professions - There are several other roles in a modern data ecosystem, such as Data Engineer, Big Data Engineer, Data Scientist, Business Analyst, or Business Intelligence Analyst. If you upskill yourself based on the required skills, you can transition into these roles.

There are several paths you can consider in order to gain entry into the Data Analyst field. These include:

An academic degree in Data Analytics or disciplines such as Statistics and Computer Science.

Online multi-course specializations offered by learning platforms such as Coursera, edX, and Udacity.

Mid-career transition into Data Analysis by upskilling yourself. If you have a technical background, for example, you can focus on developing the technical skills specific to Data Analysis. If you do not have a technical background, you can plan to skill your self in some basic technologies and then work your way up from an entry-level position.