Data powers decisions across every industry. As organizations rely on analytics to improve operations, uncover opportunities and solve complex business challenges, professionals are increasingly expected to use data for everyday decision-making. In fact, analytical thinking ranked as the most sought-after core skill in the World Economic Forum’s 2025 employer survey. 

For professionals considering a career change or looking to strengthen their data analysis skills, UC Davis Continuing and Professional Education offers a 15-week online Data Analytics Professional Program. Through hands-on projects, industry-relevant tools and authentic business data sets, learners gain practical, job-ready skills they can apply immediately—while building a portfolio of work to share with employers. 

How Data Analytics Skills Support Better Decisions 

Professionals skilled in data analysis help their teams identify key details, avoid misunderstandings and make more informed decisions. 

Chase Winterberg, an instructor in UC Davis CPE’s Data Analytics Professional Program whose background combines applied research and talent analytics, uses data analysis and business intelligence tools to help organizations make better-informed decisions. His approach to data analytics emphasizes asking useful questions, carefully checking data and making findings understandable for decision-makers. 

“I want learners to understand that producing an analytical output and evaluating it are different skills,” he said. “Professionals need to judge whether the data are trustworthy, interpret what the results actually support and explain how those findings should inform a decision.” 

Winterberg describes a learning center deciding which courses should receive additional sessions based on registration and attendance records, room capacities and staffing information. 

“Those records do not automatically tell the manager where to put limited resources,” he said. “An analyst would first clarify the decision and check what each record represents. They could then compare registrations with available spaces, reconcile course names across files, investigate missing attendance and explain which offerings warrant a closer look.” 

According to Winterberg, without this more detailed analysis, the team could confuse registrations with unique learners, interpret missing attendance data as zero or count the same sessions twice when merging files. 

“A modest analysis that someone can reproduce and defend can be more persuasive than an elaborate dashboard whose conclusions are hard to explain,” he said. 

Winterberg cautions that even accurate data visualizations can lead to misleading conclusions. Careful analysis provides the context and comparisons needed to interpret data correctly and communicate findings that support sound decisions. 

How Data Analytics Skills Apply Across Roles 

Professionals in marketing, finance, operations and human resources may be closer to a data analytics role than they realize. 

“They know which questions matter, how measures are defined and what practical constraints a recommendation must respect,” said Winterberg. “Listening to stakeholders, questioning assumptions and explaining a tradeoff all transfer well into analytics.” 

The Data Analytics Professional Program is designed for professionals who bring workplace experience and want to develop formal analytical skills—without requiring prior programming experience. The program helps learners connect technical skills to their current work, whether they want to contribute more effectively in their existing roles or explore a career in analytics. 

For professionals interested in transitioning to an analytics career, Winterberg’s advice is to start with what’s familiar and look at it through an analytical lens. 

“Choose a small question you care about and a public or otherwise authorized dataset and try to produce one useful comparison and write a short explanation of what it suggests, what it cannot tell you and what you would investigate next,” he said. 

Learners who enjoy investigating unexpected results, asking questions and explaining their findings may be well suited to roles involving data analysis. 

“Being able to explain a limitation or change your recommendation when the evidence changes is part of becoming a capable analyst,” Winterberg said. 

What Technical Skills Do Data Analysts Need? 

Data analysis requires a range of technical skills, including retrieving and combining data with SQL, preparing and analyzing data with Python and creating clear visualizations. Data analysts also need a strong understanding of statistical reasoning, including uncertainty and the difference between association and causation. 

“Another person should be able to follow the steps, check the result and rerun the analysis,” Winterberg said. “Version control, documentation and validation are part of that competence.” 

Throughout UC Davis CPE’s Data Analytics Professional Program, learners develop these skills through applied analytics projects. 

“The program progresses from Excel and data foundations into Python, data preparation, SQL, visualization, statistical reasoning and responsible AI-assisted development,” said Winterberg. 

A distinctive feature of the program is an employer-project experience with Riipen, which gives learners an opportunity to demonstrate not only their technical abilities but also their capacity to ask relevant questions, interpret findings and make informed recommendations. 

“It gives learners a concrete way to practice both technical work and stakeholder communication,” said Winterberg. “The employer-project experience with Riipen offers a documented analysis and a useful decision-support product, with a recommendation the learner can explain and defend.” 

You Don’t Have to Be an Analyst to Use Analytics 

According to Winterberg, professionals can benefit from adding data analysis to their skill sets even if “analyst” isn’t part of their job titles. 

The Data Analytics Professional Program helps learners apply analytical skills to challenges in their current work. By connecting findings to practical recommendations and communicating both the evidence and its limitations, professionals can contribute more effectively to decisions and prepare for new opportunities. 

“Knowing how to evaluate data and use it to support a decision can help you take on more meaningful responsibility in the role you already have,” he said.