Data analysts perform a variety of tasks related to collecting, organizing, and interpreting statistical information. The precise nature of the job varies somewhat from profession to profession, as an analyst working for a hospital would necessarily focus on different things than would someone working for a department store or a supermarket chain. In any capacity, though, people with this job look for ways of assigning numerical values to different business functions, and are responsible for identifying efficiencies, problem areas, and possible improvements.
One of the most important things any data analyst does is collect, sort, and study different sets of information. This can look really different in different settings, but is usually related to nailing down a fixed value to some process or function so that it can be assessed and compared over time. A grocery store might want an analyst to collect all the hours that certain employees work along with profit margins for certain days, weeks, or even hours, for instance; an Internet business might want to see hard numbers on where customers are coming from, how much they are spend on purchases, and whether deals like free shipping have any bearing on overall profits.
There are several different strategies people can use to compile data, but there are typically three universal goals. The data must be regulated, normalized, and calibrated such that it could be taken out of context, used alone, or put in conjunction with other figures and still maintain its integrity. Analysts typically use computer systems and complex calculation applications to get their numbers nailed down, but there is still a lot of intellectual know-how that goes into making these systems work.
Extrapolation and Interpretation
Once the information has been collected, analysts are usually responsible for coming up with some conclusions about what it means, as well as educating business executives on how to use it. Getting hard numbers on sales figures for a given holiday season, for example, is somewhat useful in and of itself, but is usually most valuable when stacked against numbers from previous years or other seasons as a point of comparison. These professionals may also be called on to help business owners and leaders understand what differences in numbers mean when looked at from year to year or across various departments. They usually have the expertise to not only assign statistical values to things, but also to explain what they mean.
Projections and Advisory Responsibilities
In some companies, analysts are charged with actually advising project managers and leaders about how certain data points can be changed or improved over time. They are often the ones with the best sense of why the numbers are the way they are, which can make them a good resource when thinking about making changes. A health clinic that wants to improve patient wait time might ask an analyst to identify the main reasons for delays, for example, just as an advertising firm might look for statistical feedback on prior campaigns as a way to design and plan future slogans.
Research and Writing Tasks
Advisory responsibilities often go hand in hand with writing and research. Most analysts are comfortable preparing written summaries to accompany graphs and charts, but the position often calls for additional writing tasks, too, such as drafting company memorandum, press releases, and formal reports. Analysts typically also collaborate with database programmers and administrators to write system modification recommendations or in-house instruction and training materials.
System Expertise and Troubleshooting
Most of the work analysts do is completed with the help of computers and digitized statistical software programs, which means that professionals need a certain degree of technical expertise as a matter of course. Making the systems work is the first and most important part, but the job usually also requires program troubleshooting and system security measures, as well as an ability to adapt to changing technology and keeping updates current and useful across multiple platforms.
Types of Work Settings
Almost every industry imaginable has a need for data analysis, at least at some level. Just the same, the fields of sales, marketing, and healthcare tend to have the most jobs available for these professionals at any given time. Most professionals work on teams to tackle specific projects or problems as needed. A lot of the work is done on the computer, and much of it can be done from home or from a remote office though this sometimes depends on the type of data being gathered. Professionals can typically expect to work standard hours, though important projects or looming deadlines can and often do require some overtime and weekend work.
A university education is almost always essential for this sort of work. Most employers require data analysts to hold at least a bachelor’s degree, preferably in statistics, computer science, or business administration, though there are times when other coursework may be acceptable if the candidate can also demonstrate substantial experience working in a related field. Many of the best paid and most successful analysts hold master’s degrees or doctorates, which gives them more expertise and usually also guarantees higher pay.