How to Become a Data Analyst with an Online MSCS: Skills, Certifications, and Career Outlook

Today’s data-driven economy runs on analytics. Analytics lies at the heart of evidence-based management, an approach that prioritizes rigorous data gathering and evaluation over intuition and personal experience.

Rapidly progressing technology has opened up new frontiers in data analytics. High-powered computing and artificial intelligence have converged to facilitate innovative applications and technologies, “enabling us to tackle complex problems, process massive amounts of data, and achieve unprecedented levels of efficiency,” according to DataCenters.com.

The US Bureau of Labor Statistics (BLS) identifies data scientists as the nation’s fastest-growing profession through 2031. In a job market growing at a 5 percent clip, data scientists should increase their ranks by a whopping 36 percent over that period. The World Economic Forum marks similar global trends.

Interested in entering or advancing in this career? The University of Tennessee, Knoxville, offers a pathway via its online Master of Science in Computer Science (online MSCS). This article takes a deep dive into the program. It explores the skills you’ll gain, certifications to consider, and the career outlook for data analysts.

What Does a Data Analyst Do?

A data analyst collects data, analyzes it for patterns and insights, and clearly communicates findings to support informed business decisions. Core job responsibilities include:

• Gathering and cleaning data
• Interpreting data
• Using statistical tools and databases
• Inspecting data for inconsistencies
• Visualizing data for business decisions
• Collaborating and coordinating with others
• Solving problems and supporting decisions

Data analysts help organizations improve efficiency, make decisions faster and more effectively, and bolster financial performance. They solve problems across a wide range of industries, including:

• Healthcare: Data analysts mine patient and operational data to enhance diagnostics, optimize treatments, and increase efficiency.
• Accounting: Data analytics helps detect fraud and errors. It can also streamline financial processes, reporting, and decision-making.
• Banking and finance: Data analytics can detect patterns in large data sets to identify risk, detect fraud, and forecast market trends.
• Manufacturing. Data analysts review production data to improve efficiency, optimize supply chains, and predict maintenance needs.

Data analysts can help solve a surprisingly wide range of problems for companies and organizations, including:

• High employee turnover: Data analysis can track trends in exit interviews, performance reviews, and engagement surveys to identify common causes of attrition. The result: better retention strategies and smarter hiring practices.
• Ineffective marketing campaigns: Tracking campaign performance through such measures as clicks, conversions, and audience engagement can help marketers understand what works and what doesn’t.
• Poor inventory management: Businesses can maintain the right inventory levels by analyzing historical sales data, seasonality, and demand patterns. Doing so helps to reduce costs and improve customer satisfaction.
• Declining customer satisfaction: Analytics can identify problems with products or services by examining feedback surveys, support tickets, and usage data. This allows organizations to prioritize improvements based on real customer insights rather than assumptions.
• Missed revenue opportunities: Analytics can unearth untapped opportunities by tracking sales trends, competitor benchmarking, and customer behavior. This process may yield new product lines, emerging markets, or cross-selling strategies. 

Assessing the Data: Career Outlook and Salary Expectations 

Current and prospective data analysts should enjoy a robust job market in coming years. “The overall outlook for the data analyst profession is exceptionally positive, indicating a sustained period of high demand and growth, making it a promising career path for individuals equipped with the necessary skills and a commitment to ongoing learning,” according to LinkedIn.

The largest employers of data scientists, according to the BLS:

• Computer systems design and related services (11 percent of the job market)
• Insurance carriers and related activities (10 percent)
• Management of companies and enterprises (9 percent)
• Management, scientific, and technical consulting services (6 percent)
• Scientific research and development services (5 percent)

Data analyst compensation It varies by experience, degree level, location, and type of employer. Data scientists (the job title under which the BLS groups data analysts) earned a median annual income of $112,590 in May 2024. Those among the highest 10 percent made more than $194,410.

Below is income data by industry:

• Computer systems design and related services: $128,020
• Management of companies and enterprises: $126,940
• Scientific research and development services: $120,090
• Management, scientific, and technical consulting services: $110,240
• Insurance carriers and related activities: $108,920

Many employers require or prefer that data analysts have an advanced degree. About half of all data analytics job postings in 2024 that mentioned degree level required a master’s degree or higher, according to 365datascience.com. 

How an Online MSCS Builds the Right Skills for Data Analytics Careers

Job listings for data analysts reveal which skills employers value most. According to 365datascience.com, these are the skills that appeared most frequently in 2024 job ads.

• Stakeholder communication (59 percent)
• SQL (49.6 percent)
• Excel (41.3 percent)
• Python (32.5 percent)
• Problem solving (29.2 percent)
• Tableau (28.1 percent)
• Power BI (24.7 percent)
• Data visualization (22 percent)
• R (19.6 percent)
• Data management (17.4 percent)
• Presentation skills (14.1 percent)
• Sales expertise (13.9 percent)
• Machine learning (13.7 percent)
• Microsoft Office (11.7 percent)
• ETL (8.3 percent)
• Statistical analysis (8.3 percent)
• Data governance (7.5 percent)
• Forecasting (7 percent)
• Data modeling (6.6 percent)

The computer science curriculum at UT cultivates these skills. The program includes foundational courses in algorithms, databases, and statistics and offers a comprehensive selection of courses for students pursuing a data-focused specialization. Students can choose from among these courses:

• Machine Learning covers both the theory and application of techniques used in pattern recognition, including statistical, syntactic, and ensemble methods.
• Artificial Intelligence explores both the theory and real-world applications of AI, covering topics such as problem solving, search algorithms, knowledge representation, reasoning, decision-making under uncertainty, machine learning, and multi-agent systems.
• Algorithms focuses on analyzing algorithms and how this analysis informs the design of efficient computational solutions, with topics including sorting, searching, graph algorithms, pattern matching, dynamic programming, and approximation techniques.
• Visualization explores graphical methods for uncovering key patterns in collected and simulated data across scientific, medical, and engineering fields. Topics may include visual perception, scalar field visualization, and time-dependent data, along with the use and design of advanced visualization software tools..
• Data Mining offers a hands-on introduction to big data analytics, combining theoretical concepts with practical experience. Students learn current data science techniques, work with real-world datasets, and utilize high-performance and cloud computing tools to uncover meaningful insights from data.
• Databases and Scripting Languages introduces fundamental concepts of database theory, data models, and query development. It also explores various scripting languages and how they interact with databases for practical applications.

Why Choose UT for Your Online MS in Computer Science 

The online MSCS program at UT combines rigorous coursework with the convenience of online learning. The affordable, flexible online MSCS program helps mid-career adults advance while balancing life and work. A career-ready curriculum offers technical depth along with valuable support from experienced faculty and access to UT’s alumni network. 

Numerous sources project strong growth in the data analyst job market for years to come. Openings for high-paying jobs look promising from coast to coast for people with the right qualifications. A master’s degree can help you meet those qualifications, even if you’re new to the field or lack a strong STEM background. Begin your journey by connecting with a UT enrollment advisor, or click here to learn about other career paths with an MSCS.