Businesses can even use data to anticipate the future, allowing them to identify upcoming opportunities or market shifts. As such, data analysis skills are highly coveted. 

Individuals considering a career in analytics should familiarize themselves with the most in-demand skills and tools used in the field. To develop essential data analysis skills, aspiring data analysts should also consider degree programs such as an applied computer science or a computer information systems degree.  

What Do Data Analysis Professionals Do? 

Data analysts collect, organize and interpret data to help companies make evidence-based decisions. Analysts work with large datasets to uncover patterns, spot trends and create reports that guide strategy and performance. 

For example, a data analyst might help a retailer identify the best-selling products by region, assist a hospital in optimizing patient check-in processes or support a financial institution in forecasting economic risks. 

Careers in data analysis appeal to people who enjoy problem-solving, critical thinking and technology. With more organizations relying on analytics to develop strategies and inform decision-making, data analysts are key players in modern business environments.  

Essential Data Analysis Skills 

To succeed in this field, individuals must have a combination of technical expertise and soft skills. Here are some of the most important data analysis skills every aspiring analyst should focus on: 

• Technical skills: Knowing how to use Structured Query Language (SQL) and programming languages such as Python and R allows analysts to efficiently extract, manipulate and analyze data from databases and other sources.  

• Data visualizations: Data analysts must clearly present their findings using graphs, charts, dashboards and other visualizations. These visualizations help stakeholders and executives quickly grasp complex trends and key insights.  

• Machine learning: Although not every industry has adopted machine learning (ML), familiarity with the concept can enhance an analyst’s ability to identify predictive trends and automate data analysis tasks using algorithms.  

• Data warehousing and preparation: Understanding how to work with data warehouses and prepare data for analysis is critical. This includes cleaning, formatting and ensuring accuracy before analysis begins. 

• Critical thinking: Data doesn’t speak for itself. Analysts need strong critical thinking skills to ask the right questions, interpret results accurately and draw meaningful conclusions.  

• Problem-solving: Data analysts often need to troubleshoot issues in datasets or find creative ways to answer complex business questions using analytics.  

• Project management: Managing multiple datasets, deadlines and deliverables requires strong project management skills. Analysts must prioritize tasks and keep data projects on track.  

• Communication: Data analysts must clearly communicate their findings to individuals without technical backgrounds. Strong written and oral communication skills help bridge the gap between analysis and action.  

Important Data Analysis Tools 

Proficiency in the following data analysis tools allows professionals to work efficiently and provide more accurate, actionable insights: 

• Apache Spark: Apache Spark is an open-source tool that supports multiple programming languages. With its versatility, it can perform data engineering, data science and ML tasks on both single-computer systems and distributed computing clusters. 

• Google Analytics: Google Analytics is used for tracking and analyzing website traffic, user behavior and digital marketing performance. 

• KNIME: KNIME is a free open-source tool for data analytics, reporting and integration. It features a visual, workflow-driven interface that simplifies data analysis, making it a user-friendly platform for both technical and nontechnical individuals. 

• Microsoft Excel: Microsoft Excel is a widely used data analysis tool that provides robust features for importing, cleaning, analyzing and visualizing data. Its intuitive interface and versatility make it suitable for tasks ranging from simple calculations to complex statistical analysis across numerous industries. 

• Microsoft Power BI: Microsoft Power BI is a business intelligence (BI) platform for users to visualize and analyze data and generate actionable insights. It includes a collection of software services, applications and tools that allow individuals to discover, build and share BI across their organizations. 

• Python: Python is a versatile programming language that’s used for data cleaning, analysis and ML. 

• Qlik: Qlik is a data analytics platform for discovery and visualization that supports guided analytics and dashboard creation. 

• R: R is a powerful programming language for statistical computing, modeling and data visualization. 

• RStudio: The RStudio integrated development environment (IDE) for both R and Python offers a console; a syntax-highlighting editor with direct code execution; and tools for plotting, debugging, history tracking and workspace management. 

• SAP BusinessObjects: SAP BusinessObjects is a suite of tools for BI reporting, analytics and data integration. 

• SAS: Augmented analytics from SAS integrates artificial intelligence (AI) and ML into the SAS analytics platform to streamline and enhance key stages of the data analysis process. It automates tasks such as preparing data, generating insights and interpreting analytical results. 

• Tableau: Tableau is a user-friendly visual analytics platform that allows users to explore and understand their data. It supports BI and data visualization by allowing users to connect to multiple data sources, build interactive dashboards and share insights across teams.  

Degree Programs That Develop Data Analysis Skills and Competencies 

To build a career in data analysis, pursuing a relevant degree program can develop both data analysis skills and technical fluency with data analysis tools. Majors for aspiring data analysts include math, statistics, computer science and information technology (IT).  

Two program areas professionals may want to consider are applied computer science and computer information systems. 

Applied Computer Science 

Applied computer science programs equip students with technology skills in programming languages, research methods, advanced AI, ML, data analytics, computer architecture, cloud computing and more. Due to the broad nature of the degree program, graduates with an applied computer science degree can enter a wide range of technology careers.  

Computer Information Systems 

A computer information systems degree focuses on the intersection of technology and business. Students learn database design, IT project management, cybersecurity and enterprise information systems. The curriculum often includes software engineering, web development, cybersecurity, IT project management and data analytics — helping students master the tools and techniques used in real-world data analysis roles.  

Continue Your Professional Journey with Data Analysis Skills 

Data science is one of the fastest-growing career fields today, with the U.S. Bureau of Labor Statistics anticipating 36 percent growth from 2023 to 2033. By focusing on essential data analysis skills and gaining experience with top data analysis tools, such as Tableau, Microsoft Power BI and Python, aspiring professionals can set themselves up for a successful and rewarding career. 

SEMO Online offers two degree programs that can help professionals develop the skills and expertise they need for success in this field: an online Bachelor of Science in Computer Information Systems and an online Master of Science in Applied Computer Science.  

Learn more about SEMO Online’s programs to see how they can support your professional aspirations. 

Recommended Readings 
Benefits of Getting a Degree 
How to Choose the Right College: 5 Questions to Ask Yourself 
A New Age of Technology: Game On at SEMO 
 
Sources: 
Apache Spark 
Google, How Google Analytics Works 
Indeed, “18 Key Data Analyst Skills to Get You Hired” 
Indeed, 11 Data Analysis Tools (Including Tips for Choosing One) 
Indeed, 12 Reasons to Be a Computer Science Major (Plus Jobs) 
Indeed, Computer Science vs. Computer Information Systems Degrees 
Indeed, What Does a Data Analyst Do? (With Requirements and Salary) 
Investopedia, “Data Analytics: What It Is, How It's Used, and 4 Basic Techniques” 
KNIME, About Us 
Microsoft, Power BI 
Microsoft, Understanding Data Analysis: A Beginner’s Guide 
Posit, RStudio IDE 
Python, What Is Python? Executive Summary 
Qlik, Why Choose Qlik?  
SAP, SAP BusinessObjects Business Intelligence Suite 
SAS, Augmented Analytics 
Stitch, Top 24 Tools for Data Analysis and How to Decide Between Them 
Tableau, Tableau Desktop 
TechTarget, “R Programming Language” 
U.S. Bureau of Labor Statistics, Data Scientists