How Many Hours Do Data Analysts Work?

Careers that involve working with data are currently in high demand around the country. The Global Big Data Analytics Market is expected to be worth $105 billion by 2027, which reflects a more than 12% growth from 2019 to 2027. Now is a better time than ever to enter the field of data analytics.

There are many benefits to a career in Data Analytics. Data Analysts typically receive competitive pay and good benefits, and have the opportunity to be part of the decision-making process at a company or business. For those who are interested in pursuing a career in this in-demand field, this article will explore the common life-work balance for Data Analysts, as well as how many hours they generally work in a typical week.

What Does a Data Analyst Do?

Data Analysts process and analyze large stores of data to locate information and trends about past and current practices, as well as offer predictions about what is likely to happen at a company or business based on these numbers. In addition, they transform these numbers into engaging visualizations that are accessible to all members of a team or business. These clear and engaging visual aids can be used to help employers make sound business decisions. 

The Bureau of Labor and Statistics places the annual salary for a Data Analyst at $86K, and consulting firm Robert Half lists Data Analysts’ average salary as $106K. Although these estimates differ, the good news for aspiring Data Analysts is that each is much higher than the average salary for all jobs in America, which was listed at $56K in 2021. Given the current demand, as well as the high pay in this field, becoming a Data Analyst in 2022 is a great career option.

Work-Life Balance of Data Analysts

Working as a Data Analyst is a demanding job in many ways, in terms of concentration, focus, time-management, and attention to detail. However, for the most part, Data Analysts work a routine schedule. While it’s impossible to project a uniform number of hours all Data Analysts work each week across industries, it is possible to provide a general estimate based on various factors and tasks that must be completed.

During the course of a typical day, a Data Analyst often completes the following tasks:

• Meeting with the analytics team to discuss daily tasks and brainstorm solutions to problems.
• Working with data:
• Collecting data. The time involved with this task can vary, depending on how accessible databases are. For some projects, gathering data can be a fairly straightforward and simple process, and for others it may require searching and digging.
• Cleansing the data to remove outliers and correct errors. This can be a time-consuming process for most Data Analysts, as it is crucial to properly clean data to ensure that it is reliable and able to be included in analysis.
• Processing the data. This component of the data analytics process typically involves leveraging various data tools and programming languages, such as R or Python, to offer the most viable solutions to the problem at hand.
• Visualizing data findings. This aspect of Data Analysts’ jobs involves creating data visualizations based on their findings, with the help of programs such as Tableau. 
• Presenting conclusions. Once the data has been collected, cleaned, analyzed, and visualized, the next step in the data analytics process pertains to sharing this information with others at the organization, or even to external stakeholders. That way, the insights gathered can be actionable and used to affect real changes in a company or business. Reporting on data provides key insights about areas for improvement, as well as emerging trends. A successful report involves much more than collecting numbers to display; it must weave together a clear, compelling narrative that can be accessed by decision-makers who aren’t trained as analysts.
• Documenting findings. Detailed documentation is an important component of a Data Analyst’s job. It ensures that their process can be revisited and even recreated if needed, and changed in the future to adapt to variables.

How Many Hours can a Data Analyst Expect to Work?

Generally speaking, Data Analysts can expect to work between 40 and 60 hours a week, typically on a Monday through Friday schedule, which would correspond with the hours the business or company is open. This often means a 9-5 or 8-6 day. Some companies offer Data Analysts flexible hours, which enables them to work around other commitments while still finishing required work. In addition, work-from-home options have become increasingly common during the COVID-19 pandemic, which can provide greater flexibility in terms of set work hours. When deadlines are approaching, or when pressing problems occur that must be handled, Data Analysts may need to work more to meet these demands. 

The following variables can affect not only the amount of work you may be required to do as a Data Analyst, but also the pay you receive:

• Location. The location of a company is a contributing factor to how demanding a data analytics job may be. For example, companies located in major cities or tech hubs often expect more of their employees, in terms of hourly commitment. They also tend to offer more competitive pay rates as well. In these places, however, the cost of living is also higher.
• Experience: For those who are new to data analytics, it may take more time to learn programming languages, software, and visualization applications, which can lead to a longer workday. In addition, just like any other profession, years of training/background working with coding languages and software, as well as work experience, are factored into salary rates for Data Analysts. With higher pay rates comes a greater expectation of technological fluency. In addition, those who move up the employment ladder into managerial positions may be required to work longer hours than those just getting started in data analytics. 
• Company size: Generally speaking, larger companies pay their Data Analysts higher salaries than smaller organizations because they have a larger budget for working with data. However, it's important to note that working for a large company can be a more demanding and fast-paced environment than it would be in a smaller company. This means that if you work for a larger company, you may be expected to keep longer hours than would be necessary at a smaller organization.
• Industry focus. There are a variety of industries that tend to require longer hours from their Data Analysts, such as positions in finance or security. 

In addition to in-house Data Analytics jobs, which are typically set-schedule work environments, Freelance Data Analysts may work more erratic hours, depending on deadlines for projects as well as workflow.

Hands-On Data Analytics Classes

A great way to learn about the current best practices, trends, and industry-standard software and tools in data analytics is to enroll in one of Noble Desktop’s data analytics classes. Courses are offered in New York City, as well as in the live online format in topics like Python, Excel, and SQL. 

In addition, more than 180 live online data analytics courses are also available from top providers. Topics offered include FinTech, Excel for Business, and Tableau, among others. Courses range from three hours to nine months and cost from $229 to $60,229.

Those who are looking to study an intensive educational environment may also consider enrolling in a data analytics or data science bootcamp. These rigorous courses are taught by industry experts and provide timely, small-class instruction. Over 110 bootcamp options are available for beginners, intermediate, and advanced students looking to master skills and topics like data analytics, data visualization, data science, and Python, among others. 

Are you searching for a data analytics class near you? If so, Noble Desktop’s Data Analytics Classes Near Me tool provides an easy way to locate and browse over 400 data analytics classes currently offered in in-person and live online formats. Course lengths vary from three hours to nine months and cost $119-$60,229.