There is an assumption that certain college degrees are more helpful than others when it comes to preparing for, learning, or succeeding at information technology (IT) careers.
If you believe this to be true then you may also be of the mindset that a Computer Science (BSc.) degree is more valuable than a Liberal Arts (BA) degree!
Surprisingly, there may be some evidence supporting this assumption. For example, it has been noted recently that engineering and computer science college graduates are more employable and better paid than liberal arts college graduates.
With the ever-increasing focus on setting up an online presence or the increasing competitiveness of online businesses, there is a need for web data analysts who can help web-based business succeed or thrive online.
A web data analyst researches the activities of users as they interact with a website, identifies the measures critical to the survival of the web business and recommends actions in the form of web analytics reports for web managers, online marketing teams or business owners.
Data Analysts have the opportunity to work in several different domains or sectors, for example as banking data analysts, retail data analysts, telecommunications data analysts and as marketing data analysts.
The marketing data analyst role is one of the more common ones and a marketing analyst may be found analyzing databases of prospects, leads and customers for the marketing department.
In this post, we will take a peak into the day of a marketing data analyst…
The data analyst career is one of the popular Information Technology (IT) career tracks available today.
The term data analyst is loosely associated with business data analysts, systems analysts, database analysts, reporting specialists, data researchers, statistical data analysts or marketing data analysts!
However, in this article, I will explain who a data analyst really is and provide a career roadmap or plan for becoming a data analyst.
Who Is A Data Analyst?
The term data analyst refers to someone who works with data or makes sense of the information buried in raw data or draws inferences and conclusions from it.