A data analyst can work in almost any industry in today’s data-driven world. From business to healthcare to criminal justice, there are mountains of data to be mined, sorted, and deciphered on a daily basis.
A data analyst collects, cleans, studies, and interprets data in order to solve problems and answer questions. For example, determining what demographic is most likely to visit a given resort, or what age group is most susceptible to a certain illness. They can even spot trends in data to make insightful predictions about the future.
Data analysts may work quietly in the background of an organization, but they are invaluable to the modern workforce, where data is king. Their presence is crucial to the successful operation of a large number of industries, including government, science, and finance. Read on to learn more about what a data analyst is, what a data analyst does, and how you can become one.
What Is Data Analysis?
Data analysis is the process of gathering insights from data to more accurately and efficiently inform business decisions and dealings. A data analyst is responsible for gathering, cleaning, interpreting, and converting raw data into information that’s useful and simple to understand. While job descriptions may vary, there is an overarching sameness to the work of any data analyst.
What Does a Data Analyst Do?
The work of a data analyst can best be understood by understanding their process, which goes as follows:
Identify the Problem
Data analysts start by identifying the data they need to analyze in order to answer a question or solve a problem. This involves defining their objectives, establishing their metrics, determining which data to measure, and how to measure it.
Ask the Right Question
The true value of a data analyst is the ability to look at a problem or desired outcome and figure out how to get from point A to point B. In other words, taking everything you do know in order to get to something you don’t know. This entails asking succinct questions that are also quantifiable and measurable.
Choose the Right Method
Once a data analyst has defined the problem they want to solve, they’ll then pick the best method for answering it. An analyst will typically consult the four data analysis methods and pick the most fitting for their task: descriptive analysis (“What happened?”), diagnostic analysis (“Why did it happen?”), predictive analysis (“What might happen?”), or prescriptive analysis (“What should we do about it?”).
Collect the Data
Now it’s time to collect the necessary data using whatever data collection method is most appropriate. Depending on the analyst’s work environment and the problem they’re working on, gathering the data may already be done for them. If not, the analyst may have to access databases to retrieve whatever information they need. For instance, sifting through government records might yield the data that’s needed to answer the question at hand. Other ways of retrieving data may include going to stakeholders, using programming language to create a program that will mine specific data, or searching online for market information to use as inputs in the analysis.
Clean the Data
After enough data has been collected, the analyst must clean it in preparation for analysis. This means performing tasks like reconciling inconsistencies, purging duplicate and incongruous data, and arranging data structure and format. This is oftentimes the most time-consuming part of the data analysis process.
Process the Data
Now it’s time to actually analyze the data. Processing is where an analyst examines data and finds patterns in it, with the desired end result of eventually interpreting the data. This often requires more programming and a series of tools and platforms that are either purchased or created by developers within their organization. By maneuvering the data using data analysis approaches and tools, the data analyst can suss out trends, parallels, outliers, and disparities that tell a story. During this phase, one might use data mining to find patterns in databases or data visualization software to help convert data into an easily-understood graphical layout.
Interpret the Results
Finally, the analyst interprets the results of the analysis. How well does the data answer the primary question? What recommendations can be made based on the data, and what stipulations are there to the conclusions drawn?
Share Your Findings
The last step of the entire process is the presentation of the concluding data. This comes in many forms, but communicating the results of a data analyst’s findings is an essential component of the job. Presentations are most commonly a combination of visualizations like charts and graphs, writing reports, and/or presenting information to interested parties.
How To Become a Data Analyst
The path to becoming a data analyst isn’t a fixed one. Many candidates have a bachelor’s or master’s degree in computer science, statistics, economics, or applied mathematics, but a conventional degree isn’t necessarily the best way to get there. Instead, many data analysts opt for a data analytics bootcamp, which can get you job ready in less than a year.
Our Recommended Bootcamp
The Online Data Analytics Bootcamp from the University of Maryland Global Campus offers an immersive, robust curriculum that aids students in developing analytical and technical skills. The bootcamp provides training in analytics and visualization tools like SQL and Python, and includes 20+ hands-on mini projects as well as a capstone project, ultimately creating a tangible portfolio that can be shared with prospective employers. Apply today to launch your career.