How is Data Analysis used?
Zippia reviewed thousands of resumes to understand how data analysis is used in different jobs. Explore the list of common job responsibilities related to data analysis below:
- Create and implement data analysis and reporting for management that is used for maintaining controls, creating objectives and enhancing productivity.
- Provided oceanographic and atmospheric data analysis to update and provided forecasts for Navy Central Command Combined Maritime Forces 5th Fleet operations.
- Performed data analysis, organized meetings and delivered monthly progress reports to senior management and other stakeholders on genetic testing.
- Provided technical research and data analysis for making business decisions, planning strategies and managing resources to achieve operational objectives.
- Redefined many attributes and relationships in the reverse engineered model and cleansed unwanted tables/columns as part of Data Analysis responsibilities.
- Provided data analysis for creation of new backup environments, capacity additions and technology refresh to the existing environments.
Are Data Analysis skills in demand?
Yes, data analysis skills are in demand today. Currently, 65,490 job openings list data analysis skills as a requirement. The job descriptions that most frequently include data analysis skills are reinsurance claims analyst, fuel cell engineer, and information systems consultant.
How hard is it to learn Data Analysis?
Based on the average complexity level of the jobs that use data analysis the most: reinsurance claims analyst, fuel cell engineer, and information systems consultant. The complexity level of these jobs is challenging.
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What jobs can you get with Data Analysis skills?
You can get a job as a reinsurance claims analyst, fuel cell engineer, and information systems consultant with data analysis skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with data analysis skills.
Reinsurance Claims Analyst
- Data Analysis
- Surety
- Client Accounts
- Reconciliations
- Reinsurance Contracts
- Financial Reports
Fuel Cell Engineer
Job description:
A fuel cell engineer is tasked with the design, evaluation, or construction of components or systems that make up a fuel cell. They are also tasked with designing and implementing any programs that deal with fuel cell testing or development. They write technical reports related to any engineering project and collaborate with other engineers to plan fuel cell reduction. On special occasions, they give specifications for materials that make up the fuel cell.
- Data Analysis
- FEA
- LabVIEW
- PEM
- Test Results
- Fuel Cell System
Information Systems Consultant
Job description:
Information system consultants, sometimes known as information system analysts, design and manage an organization's information system. They have to develop policies and procedures for information systems. In most organizations, they play an advisory role on issues such as security, quality assurance, and system expansion. However, they also have to analyze computer system capability specifications, procedures, and issues with automating or upgrading existing systems.
- Data Analysis
- Cycle Management
- Business Process
- Project Management
- Data Warehouse
- SQL Server
Senior Information Analyst
Job description:
A senior information analyst is a technical expert who guides and directs other professional staff members and solves complex issues. They develop strategic programs to create and modify the organization's systems and applications and analyze and evaluate computer network design, operate business and systems, and consult with professionals from different departments. A senior information analyst identifies places for strategic networks and databases and operates systems or application upgrades and improvements. Also, they develop technical solutions to improve and automate business processes.
- Data Analysis
- Epic
- Risk Assessments
- Data Entry
- Management System
- SharePoint
Gas Analyst
Job description:
A gas analyst is faced with different responsibilities in the workplace. They are required to manage internal physical transactions with the gas management system. They may also be called upon to train new employees in GC-MS software and how to handle cylinders properly. Another duty of theirs is to analyze high-pressure cylinders of gas and check for purity using GC-MS. They may be in charge of monitoring some SCADA alarms and alerting field technicians to any problems.
- Data Analysis
- Gas Supply
- SQL
- VBA
- Macro
- LDC
Dimensional Integration Engineer
- Data Analysis
- Dimensional Issues
- CAD
- CATIA
- Dimensional Analysis
- Lean Manufacturing
Decision Analyst
Job description:
A decision analyst helps companies make decisions using different research strategies and mathematical equations based on relevant data. Although their duties vary upon their industry or company of employment, it usually includes understanding the company's vision and mission, conducting market research and analyses, gathering and interpreting data, analyzing consumer feedback, developing sales forecasts, performing risk assessments, and studying the competition. Through their research findings, a decision analyst comes to a conclusion and develops recommendations that will not just help make decisions but also be vital in optimizing procedures and solving existing issues.
- Data Analysis
- SQL
- SAS
- PowerPoint
- Data Collection
- Credit Card
Senior Analysis Specialist
Job description:
A senior analysis specialist provides business analysis to their company. They should be able to understand the market and gain in-depth insights into customer needs. They manage monthly and quarterly customer analysis reporting. They must also use common SQL codes to design system architecture for databases.
- Data Analysis
- SQL
- Escrow Analysis
- Real Estate
- SAS
- Business Processes
Data Analysis Assistant
Job description:
A data analysis assistant works with data analysts and senior stakeholders to note data analysis requirements using these professionals' services. Also, data analyst assistants interpret data sets and monitor trends and patterns using statistical tools. These professionals correct primary and secondary data and reorganize it in a format that machines or human beings can understand.
- Data Analysis
- R
- Analyze Data
- Technical Support
- Behavior Analysis
- Tableau
Data Processing Auditor
- Data Analysis
- Audit Results
- SQL
- Data Entry Errors
- Data Integrity
- Epic
Lead Operations Analyst
Job description:
An Operations Analyst is responsible for ensuring that all the company's objectives are met. In the way of creating the right solution, especially when it comes to the customer's welfare. Their job is to analyze and determine the operation and project scope of a company. They prepare customer contracts as well the specification of the system, make an alternative solution and program flow to provide support, and maintain the integrity and security of the company by complying with its rules and regulations.
- Data Analysis
- Mainframe
- Business Processes
- Linux
- Process Improvement
- Incident Management
Business Information Analyst
Job description:
Business information analysts evaluate and recommend improvements to the company's information technology systems. They assist in identifying the best technological solutions in analyzing business information and engage in IT projects, from development to execution. They work closely with stakeholders to better understand the company's operational issues and to develop technology systems to resolve them. A business information analyst is also responsible for preparing reports for senior management, facilitating and conducting quality training to customers, and overseeing the database for customer purchase orders.
- Data Analysis
- Strong Analytical
- Ad-Hoc Reports
- Tableau
- SAS
- Provider Data
Field Consultant
Job description:
The duties of a field consultant depend on one's line of work or industry of employment. Their responsibilities typically include performing research and analysis to identify new business opportunities, gathering and analyzing data to determine the ideal business practices, figuring out the strengths and weaknesses of existing operations, and developing strategies to optimize field procedures. There are also instances when a field consultant must reach out to clients and address any issues or concerns, resolving them promptly and efficiently.
- Data Analysis
- Store Management
- Guest Service
- Project Management
- Address Performance Issues
- Fuel Sales
Assistant Project Director
- Data Analysis
- Construction Projects
- Research Projects
- Public Health
- R
- Community Outreach
Research Physicist
Job description:
A research physicist's job is to conduct research into physical phenomena, develop theories based on observation and experiments, and devise methods to apply physical laws and theories. Their duties and responsibilities include describing observations, developing simulations, and advising authorities on procedures to be followed.
- Data Analysis
- Laser
- Python
- Data Collection
- Technical Reports
- RF
Economic Research Analyst
Job description:
An economic research analyst uses modeling, qualitative analysis, and quantitative methods to gather and evaluate statistical data and economic data. They forecast patterns/trends and discuss economic phenomena by compiling data, analyzing data, reporting data, and applying statistical techniques and models. Besides formulating plans, policies, and recommendations to resolve economic issues, economic research analysts also work hand-in-hand with economists on matters relating to country strategy papers and policy-based loans. They provide research and background material needed in making effective policies.
- Data Analysis
- Stata
- SAS
- Macro
- Research Projects
- SQL
Information Scientist
Job description:
Information Scientists work with the knowledge database of a given organization and ensure that it is always available to those who need to use it. The creation of systems that simplify the finding of knowledge is an important activity every day as an information scientist. They are required to routinely archive and store information, check new information stack tools, and review the information to generate reports and findings.
- Data Analysis
- Literature Searches
- R
- Clinical Data
- FDA
- Pharmaceutical Industry
Complaint Evaluation Officer
- Data Analysis
- Program Monitoring
- Data Quality
- Data Collection Tools
- Capacity Building
- Data Collection Instruments
Records Analysis Manager
- Data Analysis
- SQL
- Value Analysis
- Medicare
- Financial Statements
- Financial Analysis
Strategic Analyst
Job description:
Strategy analysts are professionals who lead the consulting sessions of organizations. The analysts do their duties with rate strategy proposals in line with corporate objectives. They manage a business, determine growth areas, and make model analysis for strategy recommendations. It is also their responsibility to utilize data to solve the primary problems of businesses. Also, they provide significant insights to help organizations. They need to develop skills in management, communication, strategic planning, and attention to detail.
- Data Analysis
- PowerPoint
- Email Marketing
- Business Development
- Business Processes
- SAS
How much can you earn with Data Analysis skills?
You can earn up to $92,324 a year with data analysis skills if you become a reinsurance claims analyst, the highest-paying job that requires data analysis skills. Fuel cell engineers can earn the second-highest salary among jobs that use Python, $92,756 a year.
Job Title  | Average Salary | Hourly Rate |
|---|---|---|
| Reinsurance Claims Analyst | $92,324 | $44 |
| Fuel Cell Engineer | $92,756 | $45 |
| Information Systems Consultant | $97,215 | $47 |
| Senior Information Analyst | $94,541 | $45 |
| Gas Analyst | $72,163 | $35 |
Companies using Data Analysis in 2025
The top companies that look for employees with data analysis skills are Intel, Deloitte, and Guidehouse. In the millions of job postings we reviewed, these companies mention data analysis skills most frequently.
| Rank | Company | % Of All Skills | Job Openings |
|---|---|---|---|
| 1 | Intel | 21% | 1,317 |
| 2 | Deloitte | 11% | 17,982 |
| 3 | Guidehouse | 8% | 1,884 |
| 4 | Highmark | 6% | 3,730 |
| 5 | Robert Half | 5% | 9,678 |
20 courses for Data Analysis skills
1. Intro to Data Analysis
Start your data science journey right with this hands-on introduction to the discipline of data analysis. In this course you'll learn the 5 key stages of the data analysis process and apply them to real data sets using Python libraries NumPy, pandas, and Matplotlib...
2. Data Analysis Immersive (Full-time)
Online
40 hours; 12 weeks, Full-time
Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries...
3. Exploratory Data Analysis
This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data...
4. Data Analysis and Interpretation
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.\n\nThe Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions...
5. Data Analysis with Python
The Data Analysis specialization will provide a comprehensive overview of various techniques for analyzing data. The courses will cover a wide range of topics, including Classification, Regression, Clustering, Dimension Reduction, and Association Rules. The courses will be very hands-on and will include real-life examples and case studies, which will help students develop a deeper understanding of Data Analysis concepts and techniques. The courses will culminate in a project that demonstrates the student's mastery of Data Analysis techniques...
6. Data Analysis with R
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis...
7. ChatGPT Advanced Data Analysis
ChatGPT Advanced Data Analysis is going to transform tasks by helping amplify your productivity and supporting your creativity. ChatGPT Advanced Data Analysis can help you augment your intelligence and automate tasks, such as: 1. Turning an Excel file into visualizations and then slides inside a PowerPoint presentation; extracting data from a series of PDFs 2. Answering questions about what is in the PDFs, and visualizing the data; automatically determining if a receipt complies with a travel policy captured in a PDF 3. Transforming a document into a training presentation and associated quizzes; reading and reorganizing a set of documents based on what they contain 4. Producing social media and marketing content from a series of documents or video transcripts 5. Automating resizing and editing of videos/images while also cataloging them in a CSV Anyone with ChatGPT Advanced Data Analysis can tap into these capabilities without any prior experience in programming. The course teaches you how to converse with ChatGPT Advanced Data Analysis to accomplish these tasks, how to think about problem solving, and what types of tasks are good fits for the tool. You will learn a wide range of building blocks that you can apply in your own work and life. Large language models respond to instructions and questions posed by users in natural language statements, known as “prompts”. Although large language models will disrupt many fields, most users lack the skills to write effective prompts. Expert users, who understand how to write good prompts, are orders of magnitude more productive and can unlock significantly more creative uses for these tools. This course will introduce you to prompt writing skills that target ChatGPT Advanced Data Analysis...
8. Data Analysis and Visualization
By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do’s and don’ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story. Material features online lectures, videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line. It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations. It is the second course in the Data-Driven Decision Making (DDDM) specialization. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=Oi4mmeSWcVc&list=PLQvThJe-IglyYljMrdqwfsDzk56ncfoLx&index=11...
9. Data Analysis with Python
Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge...
10. Data Analysis with R
The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems that you want to solve with data and the answers you need to meet your objectives. This course starts with a question and then walks you through the process of answering it through data. You will first learn important techniques for preparing (or wrangling) your data for analysis. You will then learn how to gain a better understanding of your data through exploratory data analysis, helping you to summarize your data and identify relevant relationships between variables that can lead to insights. Once your data is ready to analyze, you will learn how to develop your model and evaluate and tune its performance. By following this process, you can be sure that your data analysis performs to the standards that you have set, and you can have confidence in the results. You will build hands-on experience by playing the role of a data analyst who is analyzing airline departure and arrival data to predict flight delays. Using an Airline Reporting Carrier On-Time Performance Dataset, you will practice reading data files, preprocessing data, creating models, improving models, and evaluating them to ultimately choose the best model. Watch the videos, work through the labs, and add to your portfolio. Good luck! Note: The pre-requisite for this course is basic R programming skills. For example, ensure that you have completed a course like Introduction to R Programming for Data Science from IBM...