How to Develop Data Analytics Skills

In the artificial intelligence (AI) era, organizations are increasingly concerned about their ability to draw accurate insights from data. Nearly two-thirds of enterprises either lack the data management practices to support AI or are unsure whether they have them, according to a 2024 Gartner report.

Professionals with data analytics skills who understand how to prepare and maintain data inputs for data-hungry AI platforms are ideally equipped for the data analytics roles of tomorrow.

The best foundation for these in-demand roles is a degree program that teaches data theory, programming, and engineering.

What Is Data Analytics?

Data analytics involves examining datasets to extract meaning and answer specific questions. Analysts use data to help make better decisions and spot risks and opportunities. 

Data analytics and data science are often grouped together, but the two fields differ in scope. Data science is a broader discipline that focuses on building systems to process data, including using machine learning. Data analytics focuses on querying, interpreting, and visualizing data to answer business questions.

6 In-Demand Data Analytics Skills

Different analytics processes serve different purposes, depending on what analysts want to explore: 

• Descriptive analytics evaluates current datasets to assess what has already happened. 
• Diagnostic analytics pinpoints why a particular outcome occurred.
• Predictive analytics uses patterns in historical data to forecast what is likely to happen in the future.
• Prescriptive analytics takes forecasting a step further by recommending what should be done to achieve a specific outcome. 

Technical skills are key to data analytics careers. Most employers also look for core skills in statistics, programming, visualization, and data management. Below are some in-demand data analytics and data science skills and tools.

1. Statistical Analysis and Data Modeling

Statistical knowledge helps analysts spot patterns in data and draw reliable conclusions. Data modeling supports this by organizing information clearly. Together, these data analytics skills let professionals turn complex data into easy-to-understand models that can aid decision-making.

2. Programming Language Expertise

The three most common programming languages in data analytics are SQL, Python, and R. 

• SQL: Used to query databases and solve sophisticated data challenges
• Python: Used to collect, clean, model, and visualize data, with a rich ecosystem of libraries for data manipulation, machine learning, and visualization
• R: Used to perform statistical analysis and generate high-quality data visualizations 

3. Data Visualization and Reporting

Visualization tools let analysts translate complex information into accessible visual formats through charts, graphs, and dashboards. Popular visualization and reporting tools include Tableau and Microsoft Power BI.

4. AI Data Preparation

AI platforms pull data from many sources, and that data must be consistent and well organized to provide reliable results. Analysts who know how to check incoming data, spot problems, and keep data pipelines accurate are becoming more valuable to teams using AI.

5. Problem-Solving and Critical Thinking

Problem-solving means finding the root cause of a data issue, figuring out what extra information is needed, and creating practical solutions. Critical thinking is key because analysts must be able to identify what the data truly shows, rather than massaging it to produce a preferred result.

6. Communication and Data Storytelling

The ability to share findings with different audiences, including executives, managers, and coworkers, who may not have a data background, helps influence decisions. Data storytelling is a way to communicate by telling a clear story: here’s what we wanted to learn, here’s what we found, and here’s what it means for the business.

How to Develop Data Analytics Skills

There’s no one way to build data analytics skills. Successful analysts typically combine formal education, practical experience, and credentials that demonstrate their qualifications to employers. Below are some key steps for building data analytics skills.

Enroll in an Academic Program

A bachelor’s degree in mathematics, statistics, computer science, or economics can provide the quantitative skills that many data analytics roles require. For advanced and senior positions, many employers prefer candidates with a master’s degree in a field such as data analytics, data science, or information systems.

Build a Portfolio

Working on real datasets through personal projects, open-source work, or competitions — such as those on Kaggle, a platform and community for data analysts — helps strengthen skills and gives employers something real to review. Entry-level jobs also offer hands-on experience that builds both judgment and technical ability.

Pursue Certifications

Professional certifications can demonstrate specific technical skills and help candidates stand out in a competitive job market. Popular certifications include Google, IBM, and Microsoft Power BI credentials. 

Data Analytics Career Paths and Salary Expectations

The median annual salary for data analysts was approximately $70,000 as of March 2026, according to Payscale. Job titles for professionals with data analytics skills can vary depending on interest, focus, and industry. Based on U.S. Bureau of Labor Statistics (BLS) data, common roles for individuals with data analysis skills and salaries include the following:

• Data scientists draw on mathematics, statistics, computer science, and software engineering to build data and AI systems. This role is among the fastest-growing careers in the nation, with employment expected to increase by 34% between 2024 and 2034. The median annual salary for data scientists was $112,590 in 2024. 
• Management analysts, also known as business analysts or management consultants, use data analytics skills to improve how organizations work. Employment for this role is expected to increase by 9% between 2024 and 2034, much faster than the job market at large. The median annual salary for management analysts was $101,190 in 2024.
• Market research analysts focus on understanding consumer behavior and market trends. Employment for this role is expected to increase by 7% between 2024 and 2034. The median annual salary for market research analysts was $76,950 in 2024.
• Health care analytics professionals use health care data to find patterns and insights that help providers identify optimal treatments and enhance operational efficiency. Employment for this role, which the BLS classifies as health information technologists and medical registrars, is expected to increase by 15% between 2024 and 2034. The median annual income for health data analysts was approximately $75,000 as of March 2026, according to Payscale.

Prepare for a Data Analytics Career

Expectations for data analysts are changing as technology evolves. Those who understand these changes need to prepare to combine data analytics skills with leadership, strategy, and communication competencies.

The online Master of Science in Data Science degree program offered by Tseng College at California State University, Northridge, offers coursework in data science, data mining, machine learning, and more through its remote two-year program. For those interested in health care, CSUN also offers a Master of Science in Healthcare Data Analytics program. 

Find out how Tseng College at CSUN can help you decide your future.