How to Get Into Data Analytics for Engineering

Project management is a critical element of any engineering operation. It’s multifaceted work that requires professionals to identify solutions to a number of challenges. A 2023 study published in the journal Buildings cited common challenges in managing engineering projects that include the following:

• Controlling costs
• Ensuring quality
• Addressing risks
• Managing project scope

Fortunately, incorporating data analytics into engineering project management can help to address each of those challenges and more. Valuable insights gleaned from data analysis enable engineering project managers to improve efficiency, optimize resources, and reduce costs.

Putting the power of data analysis to work in engineering project management opens up new ways to oversee projects and complete them on schedule and within budget. Individuals who are considering enrolling in an engineering management master’s degree program can benefit from learning how to get into data analytics for engineering and how to use the power of data in managing engineering projects.
 

What Is Engineering Data Analysis?

In its broadest sense, engineering data analysis involves extracting insights from data that can be used to guide decision-making on an engineering project. For example, engineers can rely on the results of data analysis to do the following:

• Improve work breakdown structures
• Detect anomalies and make prompt corrections
• Minimize project downtime
• Optimize resource allocation
• Prepare meaningful project status reports for stakeholders
• Create data visualizations that stakeholders can use when making project decisions

To conduct data analysis for engineering projects, professionals do the following:

• Work to identify the data needs of the engineering project
• Identify, filter, and prepare the data for analysis
• Perform statistical analysis of the data
• Monitor key performance indicators in the data
• Recognize and interpret patterns and trends in the data
• Create dashboards and other data visualizations for use in decision-making

To perform many of these tasks, data analytics professionals need to be proficient in using data analysis tools and software. For example, being able to use programs such as Tableau, which is used to create dashboards and other data visualizations, and coding languages such as Python, which features relatively easy syntax for data analysis, is beneficial.
 

Is It Difficult to Get Into Data Analytics for Engineering?

Knowing how to get into data analytics for engineering can make entering the field relatively straightforward.

While data analytics professionals take a variety of paths toward working in the profession, individuals who want to work in data analytics specifically in engineering can benefit from earning certain undergraduate and graduate degrees. The availability of online degree programs gives individuals who aspire to careers in engineering data analysis flexibility in earning the credentials they need.
 

Steps to Become an Engineering Data Analyst

To become an engineering data analyst, an individual can generally follow the steps outlined below.

1. Earn a Relevant Undergraduate Degree

Earning an undergraduate degree in engineering, data science, statistics, or a related discipline is an important first step for those interested in pursuing a career as an engineering data analyst. It establishes a solid foundation of expertise needed by every professional in the field.

2. Earn a Relevant Graduate Degree

While earning a graduate degree is not always required to work in data analysis, graduate programs offer students many benefits. For example, completing a master’s in engineering management degree program is a great way to learn about using data analysis in engineering project management.

Master’s in engineering management degree programs provide students with critical data analysis skills and crucial knowledge in areas such as working with cross-functional engineering teams, analyzing supply chains, and meeting quality standards in engineering projects.

3. Gain Experience

After completing the necessary education, individuals can start gaining experience working as data analysts or engineers and putting their expertise to use. Beginning in entry-level positions and progressing on the career path as they continue to work in the field, individuals can benefit from on-the-job opportunities to enhance their skills and take advantage of work-related professional development training.
 

4. Develop Key Skills for Engineering Data Analysis

Through earning an advanced degree and gaining experience in the field, individuals who work in engineering data analysis benefit from cultivating skills in areas such as the following:

• Data analytics tools, software, and programming languages
• Critical thinking
• Organization and the ability to work on multiple assignments
• Data visualization
• Problem-solving
• Attention to detail

5. Consider Earning Certifications

While earning certifications is not always required to work in engineering data analysis, obtaining certifications demonstrates an individual’s credentials and dedication to learning new skills.

Examples of common certifications in data analysis include:

• Associate certified analytics professional (aCAP) certification from the Institute for Operations Research and the Management Sciences (INFORMS)
• CompTIA Data+ certification from CompTIA
• Certified advanced analytics professional certification from SAS
   

Engineering Data Analyst Salary and Job Outlook

Data from the U.S. Bureau of Labor Statistics (BLS) reveals attractive salaries and job prospects for individuals who want to work in engineering data analysis. The BLS reports the following for data scientists:

• Median annual salary of $108,020 as of May 2023
• Projected job growth of 35% from 2022 to 2032 (which significantly exceeds the 3% growth projected for all occupations)

Individuals may prefer to use their data analytics skills while working primarily as engineering managers. The BLS reports the following for architectural and engineering managers:

• Median annual salary of $165,370 as of May 2023
• Projected job growth of 4% from 2022 to 2032
   

Learning About Engineering Data Analytics Can Lead to a Rewarding Career

Acquiring cutting-edge skills and expertise in engineering data analytics can equip an individual to progress on a fulfilling and meaningful career path. Data analysis can uncover valuable insights to keep engineering projects on a trajectory for success.

Individuals who are interested in advancing their education in engineering data analytics can explore the online Master of Science in Engineering Management degree program at Tseng College at California State University, Northridge, to learn how it can help them achieve their goals.

Featuring options to either focus strictly on engineering management or add a data analytics concentration, the program can position students for leadership roles in the engineering field and related industries. Start advancing your knowledge of engineering management today.