Businesses are increasingly embracing data-driven decision-making to take advantage of the vast amounts of data produced and captured daily. North America currently accounts for 45 percent of the global data analytics market, which is expected to grow rapidly over the next decade.
Collecting and processing large amounts of data is challenging. Emerging technologies like artificial intelligence (AI) and machine learning can make it much more manageable. These innovations are creating rapid and unprecedented changes in data analytics and the broader realm of information science. Computer and data science professionals must upskill to keep pace and remain competitive in the evolving job market.
This article defines some key terms, explores how technologies like AI are changing how organizations process data, highlights emerging career possibilities, and explains how earning an advanced degree in computer science—like the one offered online by the University of Tennessee (UT)—can help professionals keep up with industry changes.
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What Is Data Mining?
Data mining is the process of identifying patterns and extracting valuable insights from big data sets using statistical and AI algorithms. Many industries use data mining to turn raw data into actionable knowledge. Industries actively using data mining include:
- Finance: The finance industry uses data mining to identify risks and detect unusual transaction patterns that could indicate fraud, to streamline credit scoring, to optimize portfolio performance, and to optimize marketing segmentation.
- Retail: Retailers frequently analyze purchase data to identify products often bought together (e.g., bread and butter). This insight helps design promotions and improve product placement strategies. Data mining also helps with store location optimization and improves inventory management.
- Healthcare: Healthcare providers often use data mining to analyze patient data to diagnose medical conditions, personalize treatments, predict disease outbreaks, expedite drug development, and improve efficiency at healthcare facilities.
- Manufacturing: Manufacturers use data mining to optimize numerous processes and improve performance. For example, data mining can be used to analyze historical equipment performance data and predict when machinery is likely to fail. This enables proactive maintenance that reduces downtime and improves operational efficiency.
- Logistics: Logistics companies mine data from supply chain operations to identify bottlenecks, forecast demand, manage risk, reduce costs, and optimize delivery routes.
How Do Data Scientists Use AI?
While data mining has existed for decades, AI has dramatically improved its efficiency, scalability, and accuracy. Modern data mining leverages AI and machine learning capabilities for optimal analysis. Unlike traditional data analysis methods, which often rely on predetermined rules, AI systems can adapt and improve their performance over time as they process more data. For example, AI-powered data mining tools help Amazon power its recommendation engine and JPMorgan Chase review commercial loan agreements.
The widespread adoption of AI is reshaping the roles of data scientists, data analysts, and business intelligence (BI) specialists, among others. AI-driven data mining tools allow these professionals to automate routine tasks such as data cleaning, preparation, and basic analysis, freeing their time so they can focus on higher-value tasks like strategic decision-making and complex problem-solving.
However, data scientists, analysts, and BI professionals must be familiar with and know how to use AI systems and tools to fully benefit from them. Many companies are adding AI-related responsibilities to their job descriptions, meaning industry professionals must focus on upskilling to remain competitive.
After the MSCS: Careers in Data Mining
Data scientists, information research scientists, and tech-related analyst roles rank among the fastest-growing jobs in the U.S. Many of these roles are evolving as companies introduce new AI applications to their data mining processes.
Data Scientist Jobs
A data scientist organizes and analyzes complex data using statistics, machine learning, and programming. They work at the intersection of math, computer science, and domain expertise to help organizations make data-driven decisions. Their day-to-day responsibilities typically include:
- Data collection and processing
- Identifying trends, correlations, and anomalies using statistical analysis and visualization
- Building predictive models and machine learning algorithms to forecast outcomes or solve business problems
- Improving the quality of data or product offerings using machine learning techniques
- Communicating insights and recommendations to others in the organization
Data scientists are in high demand across various industries, including finance, healthcare, entertainment, manufacturing, and information technology. Their job titles may vary depending on the industry and focus of their role; common alternative job titles include machine learning scientist, data product manager, and big data specialist.
According to the U.S. Bureau of Labor Statistics (BLS), the employment of data scientists should increase by 36 percent over the next decade, much faster than the average four percent across all occupations. Data scientists earn an average yearly income of $108,000, making it an attractive career choice. Most employers require (or at least prefer) data science job candidates to have an advanced degree, e.g., a master’s in computer science.
Big Data Engineer Careers
Data engineers design, build, and maintain the infrastructure that allows data to be collected, stored, processed, and analyzed efficiently. Their work ensures that data is clean, reliable, and accessible for data scientists, analysts, and business intelligence teams. Big data engineers specialize in large-scale data processing systems that can handle massive volumes of data.
The day-to-day responsibilities of big data engineers (often also called data solutions engineers, data architects, or enterprise data engineers) include:
- Designing, developing, testing, and maintaining an organization’s complete data management system
- Managing ETL (Extract, Transform, and Load) processes while optimizing data pipelines, including streaming data
- Building data models to reduce system complexity and lower overall costs
- Overseeing and implementing disaster recovery systems and processes
Industries that hire data engineers include finance, banking, healthcare, e-commerce, retail, technology, and IT. Most employers require candidates to have a master’s degree in computer science, engineering, or a related field, as well as a few years of relevant work experience. Big data engineers earn an average yearly salary of $131,000.
Business Data Analytics Jobs
Business data analytics focuses on using data to drive strategic decisions, improve business performance, and optimize operations. Business data analytics job roles include:
- Business intelligence analyst: A BI analyst collects, analyzes, and visualizes data to help organizations make informed business decisions by identifying trends, patterns, and key performance indicators (KPIs). These professionals earn an average yearly salary of $100,000.
- Information security analyst: An information security analyst protects an organization’s systems, networks, and data from cyber threats by implementing security measures, monitoring for vulnerabilities, and responding to incidents like breaches or attacks. BLS data indicates that information security analysts earn around $120,400 annually.
- Computer systems analyst: Computer systems analysts study an organization’s current computer systems and design ways to improve efficiency. They earn an average yearly salary of $103,800.
Business data analytics professionals can work for any company looking to make data-driven decisions. The top industries employing these professionals include finance, technology and software, insurance, and government.
Advance Your Skills—and Your Career—with an Online MS in Computer Science
The technology industry is marked by rapid innovation and continuous change, making it essential for computer and data science professionals to stay current with best practices and the latest tools. Enrolling in a specialized master’s degree program can help you acquire the latest skills and knowledge to supplement your existing computer science expertise. UT’s online Master of Science in Computer Science (MSCS) is designed with working professionals in mind. The program’s flexible, 100 percent online format makes it easier to expand your horizons without having to relocate or put your career on hold.
Find Your Focus with a Data Mining and AI Concentration
The UT online MSCS offers a concentration in data mining and intelligent systems. Students in this concentration take courses focused on AI, deep learning, natural language processing (NLP), and data mining.
The online MSCS concentration in data mining and intelligent systems is ideal for professionals interested in using data mining tools and AI to develop creative automation and big data applications. The coursework covers the latest trends and technologies.
Study with Data Science Experts at a Top Engineering School
UT online MSCS students benefit from attending a highly ranked school of engineering and learning from expert faculty members with in-depth industry experience. Teachers include Garrett Rose, who led research efforts in hardware security and nanocomputing at the Air Force Research Laboratory, and Michela Taufer, whose research focuses on high-performance computing, cloud computing, and big data analytics.
Take the Next Step: Apply to the OMSCS Program at UT
The demand for skilled data science professionals is soaring and is expected to grow even further as more organizations embrace data-driven decision-making. As the industry evolves, professionals with skills in emerging tools and technologies—including data mining and AI—will be in increasingly high demand. Earning a specialized master’s degree, like the UT online MSCS in data mining and intelligent systems, can help you gain the skills and expertise needed to take advantage of this demand and stand out in the job market.
If you’re ready to accelerate your career, explore the UT online MSCS admissions requirements and start your application today. Alternatively, get in touch to request more information or discuss your career objectives and learn how an MSCS can help you achieve your goals.
