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Data analyst skills for your resume and career

Updated January 8, 2025
6 min read
Quoted experts
Dr. Todd Wittman Ph.D.,
Pavel Chernyavskiy Ph.D.
Data analyst example skills

A data analyst's most important hard skill set is their knowledge and command of data analysis tools. These tools can include python, SQL, SAS, and more. It's also crucial for data analysts to show skill in using these tools, and other data management tools, to improve processes and procedures.


Some soft skills a data analyst will likely need include comprehension and statistical knowledge. Data analysts need to be able to deal with large amounts of complex data, and to make sense of this data. A great understanding of, and typically a specialized training in, statistics in order to avoid common errors.

Below we've compiled a list of the most critical data analyst skills. We ranked the top skills for data analysts based on the percentage of resumes they appeared on. For example, 10.2% of data analyst resumes contained data analysis as a skill. Continue reading to find out what skills a data analyst needs to be successful in the workplace.

15 data analyst skills for your resume and career

1. Data Analysis

Here's how data analysts use data analysis:
  • Conducted data analysis and trend interpretation for developing statistical process control methods in support of aviation information and readiness reporting requirements.
  • Provided data analysis and portfolio stratification across entire credit risk portfolio in support of capital modeling and credit risk reporting.

2. Python

Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.

Here's how data analysts use python:
  • Worked on sentiment analysis in python to analyze the severity of crime/fraudulent activity from the articles.
  • Develop Python solutions associated with GIS data collection, management and utilization.

3. Power Bi

Here's how data analysts use power bi:
  • Created multiple data visualization solution for initial Power BI business preview.
  • Developed Reporting solutions using Power BI.

4. Data Management

The administrative process that involves collecting and keeping the data safely and cost-effectively is called data management. Data management is a growing field as companies rely on it to store their intangible assets securely to create value. Efficient data management helps a company use the data to make better business decisions.

Here's how data analysts use data management:
  • Contributed to development of new products and functionality by working in conjunction with editorial, data management and technology groups.
  • Performed Data Management duties; acquired validated, processed, stored and protected data for reliable accessibility to data users.

5. Visualization

Here's how data analysts use visualization:
  • Initiated and designed dashboards locally before publishing to Tableau Server for data visualization, statistical trend analysis and KPI evaluation.
  • Developed MySQL database implementation, effectively merging over 10 data sources for efficient reporting and Tableau visualization of campaign metrics.

6. Data Quality

Here's how data analysts use data quality:
  • Partner with cross functional teams and business stakeholders to identify issues and implement business process improvement to enhance overall data quality.
  • Conducted data quality investigations and made necessary improvements, in response to operational assessments, self-driven investigations, and customer inquiries.

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7. Data Collection

Data collection means to analyze and collect all the necessary information. It helps in carrying out research and in storing important and necessary information. The most important goal of data collection is to gather the information that is rich and accurate for statistical analysis.

Here's how data analysts use data collection:
  • Maintained leadership responsibility to ensure data consistency and quality across the end to end process from data collection through metric reporting.
  • Devised innovative strategies that streamlined data collection, daily deposits and decreasing daily backlog process to drive team member productivity.

8. SAS

SAS stands for Statistical Analysis System which is a Statistical Software designed by SAS institute. This software enables users to perform advanced analytics and queries related to data analytics and predictive analysis. It can retrieve data from different sources and perform statistical analysis on it.

Here's how data analysts use sas:
  • Developed SAS program to auto generate PDF school specific reports for educational facilities participating in the vaccination assessment.
  • Utilize SAS programming knowledge and statistical analysis methods to produce quarterly reports based on wayside detector data.

9. BI

Here's how data analysts use bi:
  • Directed and participated in BI solution scoping, requirements analysis, and architectural/database design activities for 3 clients.
  • Designed and implemented proof of concept solutions and created advanced BI visualizations using Tableau platform.

10. Analyze Data

Analyze data or data analysis refers to the practice of studying, organizing, and transforming data to make it more useful. It also includes the cleansing of non-useful information which helps in better decision making regarding any particular matter. Analyze data is a practice that is used widely in the field of business, social sciences, and science.

Here's how data analysts use analyze data:
  • Collect and analyze data to identify financial representatives based on incomplete/inaccurate information
  • Gathered requirements, analyze data and create functional/technical specifications to functionality required by new business rules, regulations or standards change.

11. Customer Service

Customer service is the process of offering assistance to all the current and potential customers -- answering questions, fixing problems, and providing excellent service. The main goal of customer service is to build a strong relationship with the customers so that they keep coming back for more business.

Here's how data analysts use customer service:
  • Provide exceptional customer service to internal and external data product customers by troubleshoot hardware and software issues and identify network/applications issues.
  • Partnered with customers that provided Verizon with a low customer service rating to identify center and organizational opportunities.

12. PowerPoint

Here's how data analysts use powerpoint:
  • Developed PowerPoint presentations and various marketing collateral for Membership Director to present at Chamber budget meetings and Women in Commerce conferences.
  • Produce graphical analysis and PowerPoint presentations for director level management and litigation team to be utilized as legal documentation of compliance.

13. Strong Analytical

Here's how data analysts use strong analytical:
  • Achieved and Maintained strong analytical skills while efficiently utilizing excellent oral and written communication skills.
  • Maintain strong analytical and problem solving skills, excellent communication and presentation skills.

14. Statistical Analysis

Here's how data analysts use statistical analysis:
  • Developed data analysis solutions based on predictive, behavioral or other models via statistical analysis and use of relevant modeling techniques.
  • Planned strategies and performed statistical analysis for companies in litigation or arbitration to reduce judgment-based error and improve risk assessment.

15. Patients

Here's how data analysts use patients:
  • Generated informational reports for the organization based on information forwarded by insurance claims related to patients and providers.
  • Expanded and maintained Visual Studio Reports providing upcoming appointments of Medicare Advantage patients to Clinical Innovations Department.
top-skills

What skills help Data Analysts find jobs?

Tell us what job you are looking for, we’ll show you what skills employers want.

What skills stand out on data analyst resumes?

Dr. Todd Wittman Ph.D.

Associate Professor, The Citadel

I would strongly recommend any mathematics major to get a good background in statistics and computer programming, even if that is not going to be their primary field of study. You can still concentrate on the topics that interest you, but it is important to diversify your skill set.

Getting involved in a research project tells a prospective employer that you have done work beyond the classroom. It shows that you can tackle a difficult problem that does not have an answer in the back of the textbook. At most colleges and universities, faculty are eager to work with bright undergraduate students on projects. Students are often intimidated by their faculty, but it does not hurt to ask. It might result in an interesting research experience, internship, or even a lead on a job after graduation.

What data analyst skills would you recommend for someone trying to advance their career?

Pavel Chernyavskiy Ph.D.

Assistant Professor of Statistics, University of Wyoming

Statisticians with subject-matter expertise tend to be more in-demand, all else being equal. For example, quantitative biologists, statistical geneticists, bioinformaticians, industrial statisticians can all be thought of as "statisticians with subject-matter expertise," at least in my opinion. With that in mind, if an applicant can develop their knowledge of a particular area of application during their gap year, it should help them in the job market.

What type of skills will young data analysts need?

Zhixin Wu Ph.D.Zhixin Wu Ph.D. LinkedIn profile

Associate Professor, DePauw University

Problem solving skills, analytical skills, self-learning ability, and good communication skills.

What soft skills should all data analysts possess?

Dr. Anne Paulet Ph.D.Dr. Anne Paulet Ph.D. LinkedIn profile

Professor, History Department, Humboldt State University

In terms of soft skills, those probably won't change much, they will simply be practiced differently. Being flexible is important since jobs may switch between home and office and since one may be dealing with someone else working from home and the challenges that can present-what cat owner hasn't had their cat walk in front of the camera or step on the wrong computer key? The ability to work in groups will continue to have importance as well as the ability to manage your own time and meet deadlines. At the same time, the nature of computer camera interaction means that people will have to learn to "read" others differently than they would in an in-person environment. Many recent articles have talked about how it is harder to read facial cues or detect emotional responses on the computer. Again, those presently taking synchronous classes have the opportunity to practice these skills--providing students turn on their cameras rather than relying only on audio. If the past year has demonstrated anything, it is that people need to be more culturally aware and sensitive and also be able to work with people of diverse backgrounds. History classes are a great way for students to better understand what others have gone through and how that might impact interaction today. Additionally, history classes-as well as college in general-should provide students with the skills to help create the kind of changes in institutions and companies that need to be made to make them more inclusive. Perhaps the greatest skill college students have is the ability to learn. I never intended to teach online, yet here I am doing just that. It required learning new ways to approach teaching, reconsideration of the ways students learned in the new environment, and figuring out new online programs to make all this happen. I was forced to do this as a result of the pandemic but most students will find that this sort of adjustment-whether foreseen or not-will be a regular part of their career path. The ability to learn these new skills, to apply new methods and to approach issues in new and innovative ways will help them stand out when it comes to looking for a job.

What hard/technical skills are most important for data analysts?

Sal Aurigemma Ph.D.

Associate Professor of CIS, J. Bradley Oxley Professor of Computer Information Systems, University of Tulsa

Students graduating with Information Systems and related degrees usually have little problem finding employment upon graduation. However, the pandemic upended that paradigm for some. For those who recently graduated and are still looking for employment, keep the faith and develop your technical skills. Developers should show prospective employers that they are familiar with agile programming methodologies and modern DevOps stacks and processes. Data analysts should be focused on presenting their ability to work with structured and unstructured data, effectively query data using SQL & NoSQL, and, most importantly, provide actionable insight by making data accessible and relatable to decision-makers at all levels of an organization. Those interested in cloud architecture and cyber security careers have to keep current on their skills and certifications. Cloud engineers need to stay aware of the constant changes happening at the major providers (AWS, Azure, GCP) and, as with all other IT fields, provide tangible evidence of your skills via real projects that you have worked on. Prospective cyber security analysts should first focus on identifying their first specialization because there are too many security roles to learn them all at once, especially as beginners. Two popular entry-level cyber security jobs include information security consultant and Security Operations Center (SOC). Both of these roles require a sound foundation in networking fundamentals, vulnerability identification and mitigation, and an understanding of organizationally relevant security and privacy frameworks and regulations.

List of data analyst skills to add to your resume

Data analyst skills

The most important skills for a data analyst resume and required skills for a data analyst to have include:

  • Data Analysis
  • Python
  • Power Bi
  • Data Management
  • Visualization
  • Data Quality
  • Data Collection
  • SAS
  • BI
  • Analyze Data
  • Customer Service
  • PowerPoint
  • Strong Analytical
  • Statistical Analysis
  • Patients
  • ETL
  • Data Entry
  • Data Integrity
  • SQL Server
  • Data Warehouse
  • Access Database
  • Data Models
  • Pivot Tables
  • Java
  • Math
  • Excellent Interpersonal
  • VBA
  • Business Processes
  • Extraction
  • Profiling
  • Financial Data
  • HR
  • R
  • SPSS
  • PL/SQL
  • SharePoint
  • Work Ethic
  • Excellent Organizational
  • Technical Support
  • Data Issues
  • Management System
  • Data Validation
  • Salesforce
  • Data Elements
  • Data Extraction
  • Regression
  • Data Lake
  • Business Rules

Updated January 8, 2025

Zippia Research Team
Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

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