When it comes to intellectually stimulating jobs that require copious amounts of brainpower, few can match that of a data analyst.
At a time where data extrapolation has become the cornerstone for success among businesses, data analysts can’t be happier.
After all, not only do they get to do what they love, it’s also encouraging that their services are in demand.
Needless to say, since businesses depend heavily on their services to inform their corporate strategy, they tend to compensate data analysts well.
However, tendencies are generalizations that do not reflect the case-by-case reality of data analysts.
The truth is that while there is a standard data analyst salary, several factors play a role in determining how much more or less you can expect this someone with this professional profile to bid for.
That’s exactly what I’m going to discuss in this article.
Dive into the world of a data analyst to learn more about what they do as well as how their compensation packages are influenced by experience, rank, and even geographic location.
Let’s get right into it.
Data Analyst Average Salary
Based on data shared by PayScale, on average, Data Analysts rack in just north of $60,000 annually, their hourly rate corresponding to $21.13.
While the median salary stands at roughly $61,000, 90% of salaries used in Payscale’s report exceed the mean with only 10% falling below the average salary.
On the other hand, data analyst salary estimations offered by Indeed are much more optimistic, ranking them in the mid $70K annually.
That said, while annual salaries may differ, the estimated cash bonus of roughly $4000 indicated by Payscale can be considered a relatively fair trade-off in the long run when compared to the stats offered by Indeed.
How Experience Affects A Data Analyst’s Salary
In as much as the average base salary stands within the 61K-75K threshold, experience plays a significant role in how much more a data analyst can rack.
Let’s examine how that pans out in a real context utilizing estimates provided by PayScale.
According to PayScale, entry-level data analysts bring in an estimated $60K.
However, (and as occurs in the world of work), the more experience a data analyst has, the higher their compensation will be.
Based on the graph, it is estimated that data analysts begin to command more compensation after five years of experience, with punctual bonuses expected every five or so years following their last bonus.
How Location Affects Data Analyst Salary
In addition to experience, the location where a data analyst is stationed to work also plays a significant role in how much compensation they receive.
As highlighted on PayScale, within the United States, salary expectations for data analysts rise based on the State or area in which the analyst resides.
In Los Angeles, California, data analysts can expect to reel in roughly 7% more than the median salary.
As is evidenced in the graph, data analysts in San Francisco, on the other hand, can command as much as a 23% increase over the median annual salary.
To paint a more inclusive picture, let’s take a brief look at how national average salaries differ based on the country in which a data analyst lives.
In comparison to average data analyst salary rates in the United States, a data analyst who resides and declares taxes in Spain can expect a much median lower salary totalling roughly $33,000 annually.
Needless to say, the nearly $40,000 difference in salary expectations is quite a telling factor in determining where a data analyst should like to pursue a career.
Data Analyst Salary Key Takeaways
Whenever a job opening comes up for a Data Analyst, the natural question that comes to a candidate’s mind will always be centered on salary expectations.
While there is no strict or fixed rule with regard to the salary that a full-time data analyst can request, experience, skills, and geographic location always play a significant role in refining the salary offer.
If you are currently working in data mining or are considering a career in it, then here’s a bit of advice to help guide you align your skills with the salary you’re looking for:
- Be clear on all the technical, analytical, and soft skills that contribute to your competitiveness as a professional.
- Find out whether there are skills that are in more demand than others and, consequently, how much more compensation companies are willing to pay for data analysts who master them.
- Leverage Glassdoor, PayScale, and any relevant salary sites you find on Google to help give you an idea of your market value.
- Search for companies that are putting out advertisements for job titles within data analytics. Be sure to pay attention to the salary and benefits package being offered. Obviously, there will be discrepancies. For example, a job advertisement for a data analyst for Microsoft, IBM, or Google will logically pay more than a less known business.
- Apply for the best one that suits your needs. Obviously, there will be discrepancies
In short, do your research and plan accordingly so you can secure the best career path for your skillset and experience.
Data Analyst Salary FAQ
What Does The Data Analyst Role Entail?
A data analyst is a person who gathers, organizes, and scrutinizes a set of data in order to make inferences and conclusions that are based on a logical methodology.
In a nutshell, data analysts take complex or complicated company data, break it down into a simple, understandable format which they then present to a board of directors, company executives, stakeholders, or any interested parties.
Someone who works in data analytics may apply one of four types of processes to achieve the results which stem from the services that they offer:
- Descriptive Analytics: In the context of business analytics, this consists of reporting solely the underlying agents or elements that provoked a particular action to take place.
- Diagnostic Analytics: This type of analytics differs from descriptive analytics in the sense that here, a data analyst isn’t seeking a global description of a series of actions that provoked a result. Rather, it centers the discussion on identifying and analyzing the catalysts behind a particular action in order to understand why something took place.
- Predictive Analytics: As the name suggests, predictive analytics examines trends, tendencies, and patterns in a set of data in order to foresee what may happen in the future.
- Prescriptive Analytics: Lastly, prescriptive analytics concentrates its effort on identifying a solution to a given problem or to take advantage of an anomaly.
It is easy to confuse a data analyst with two similar profiles: data scientists and business analysts.
Unlike a data scientist which goes through company data to identify opportunities or weaknesses that are of interest or concern to a business, or like a business/financial analyst who proposes strategic decisions to a business, the role of a data analyst does not encompass these responsibilities.
Instead, they take care of complex data analysis and presentation without the added need or expectation for strategic decision making or company directional proposals.
What Responsibilities Does A Data Analyst Assume?
Doubling down on the specific responsibilities that data analysts are expected to accomplish can be a challenging feat.
In a nutshell, a data analyst’s role and tasks are entirely dependent on the needs of the business for whom they work.
Consequently, there will be discrepancies between individual roles and expectations.
That said, universally speaking, there are common responsibilities that data analysts share.
- Generation of reports: As part of their professional profile, it is incumbent upon data analysts to compile the conclusions they have drawn from their data analysis in a presentable format. That way, they can communicate their results to the interested parties. The chief way to do so is via a report in which they string together conclusions stemming from big data analysis, supporting each one with the necessary facts that they extracted from their analysis.
- Spot patterns in data: In conjunction with report generation, data analysts are expected to notice any trends or patterns that are present in data. Granted, the level to which they dive into this pattern recognition is entirely dependent on the type of data analysis that they’re conducting.
- Logical data storage and retrieval: It is also a data analyst’s job to determine where and how the data they access should be stored. This is the most technical area of data analysis that usually involves a unique skill set to leverage tools such as databases, Microsoft Excel, Python/Machine Learning software, to promote accurate data visualization and accessibility.
Granted, as alluded to previously, the responsibilities of a data analyst vary greatly based on each company’s respective needs and, as you will discover, the experience and qualifications of the hired expert.
What Requirements Are Needed To Become A Data Analyst?
There is no steadfast guide regarding the exact requirements that a data analyst needs in order to be hired by a business.
However, as usual, on average, there are general expectations that are ascribed to them based on the responsibilities that they need to complete.
Generally speaking, data analysts need to have a solid balance of technical and analytical skills.
That includes the need to correctly scrutinize and evaluate a batch of data in order to extract the results and conclusions that they need.
Additionally, they need to be able to correctly handle software applications that permit the storage, collection, and analysis of data.
Those two skills would fall under analytical and technical skills respectively.
Usually, a data analyst has a prominent academic background that is research-oriented.
Since the crux of their focus on research-based, any investigative-based Bachelor's degree, Master’s degree program or higher is valued in data analyst jobs.
As is expected, candidates who have a profile in Data Science, Computer Science, Statistical Analysis, or Mathematics are at a natural advantage due to their field of study.