What Does a Data Analyst Do? Career Path, Skills & Salary in 2025

Introduction

This blog is for aspiring and early-career professionals exploring the field of data analysis. It offers a clear overview of the role, skills, tools, and career path of a data analyst. You’ll understand what the job involves and why it is a smart career move in 2025.

What is Data Analysis?

Data analysis refers to the process of gathering, cleansing, structuring, and analyzing data to reveal patterns, make conclusions, and inform decision-making. It encompasses both qualitative and quantitative approaches to respond to certain questions or resolve business issues.

Using tools such as Excel, SQL, and Python, data analysts interpret vast datasets, making raw information usable insights. Whether it's customer trends in retail or patient care in healthcare, data analysis assists companies in making faster, wiser decisions. Essentially, it converts information into business value.

Beginners aiming to build a solid base in data principles and cloud computing can benefit from the Microsoft Azure Data Fundamentals course.

What is a Data Analyst?

A data analyst is a professional who analyzes data to enable organizations to make sound decisions. They gather, process, and interpret data to discover trends, patterns, and insights that advance business objectives.

Their function bridges raw data and strategic action through translating numbers to valuable insights that inform planning, performance measurement, and problem-solving. From marketing to finance, healthcare to technology, data analysts assist in transforming information into quantifiable business results.

What Does a Data Analyst Do?

Data analysts convert raw data into useful insights that inform business decisions. Their day-to-day work covers the entire data life cycle, from collection to reporting. Let's take a closer look at the fundamental tasks they perform:

Data Collection

Data analysts collect data from different sources like databases, surveys, APIs, and spreadsheets. This includes finding the data points that are relevant to answer particular business questions or measure performance metrics. Those looking to work with large-scale data ingestion can explore the Data Engineering on Microsoft Azure course.

Data Cleaning

Collected data often contains errors, duplicates, or inconsistencies. Analysts clean and format data to ensure accuracy, reliability, and consistency before deeper analysis begins. To better understand secure handling of data, the Microsoft Security, Compliance, and Identity Fundamentals course is a strong starting point.

Data Analysis

With statistical methods and tools such as Excel, SQL, or Python, analysts analyze data to reveal patterns, trends, and anomalies. This process assists in answering business questions and enabling informed decisions.

Data Visualization

Analysts use charts, graphs, and dashboards for data visualization. Tools like Power BI or Tableau make findings easier to understand and communicate to non-technical stakeholders.

Reporting and Presentation

Data analysts prepare reports, slide decks, or dashboards to present insights clearly and concisely. They often tailor these outputs for executives, managers, or cross-functional teams.

Troubleshooting

When issues arise in data pipelines or reporting tools, analysts diagnose the problem, trace its source, and resolve it to ensure data integrity and functionality.

Problem Solving

Data analysts help solve real-world business problems by applying logic, statistical methods, and data-backed reasoning. Their insights support decision-making across product, marketing, finance, and operations. Courses like the Microsoft Power Platform Fundamentals help build automation and analytical thinking for real-world problem-solving.

How to Become a Data Analyst?

To become a data analyst, you need a mix of technical training, analytical thinking, and business insight. Most professionals start with a degree in a related field and build hands-on experience through tools and certifications.

Explore our complete guide on how to become a data analyst to learn more.

Must-Have Skills to Become a Data Analyst

Data Analyst Technical Skills

Database Tools

Knowing how to query, access, and manage data with tools such as SQL, Oracle, or MySQL is important for analysis.

Data Visualization

Visuals such as charts and dashboards assist in conveying insights in an understandable manner to decision-makers and stakeholders.

Data Mining and Cleaning

Preparing and analyzing raw datasets ensures accuracy and excludes errors prior to any analysis.

Programming Languages

Python, R, and SQL are extensively used to automate analysis, execute queries, and carry out statistical operations effectively.

Statistical Analysis and Math

Strong knowledge of statistics and basic math is crucial for interpreting patterns and running predictive models.

Data Analyst Workplace Skills

Problem-Solving

Data analysts have to tackle problems in a logical manner and provide data-driven solutions that solve business issues.

Communication

Clearly presenting findings to technical and non-technical teams is vital for driving data-informed decisions.

Industry Knowledge

Understanding your business domain adds context to analysis and helps identify relevant trends and patterns.

Top Tools Data Analysts Use

Data analysts rely on various tools to collect, process, visualize, and present data. Here are some of the most commonly used:

Microsoft Power BI

A powerful business intelligence tool used to create interactive dashboards and reports from multiple data sources. Learn how to master it through our Design and Manage Analytics Solutions Using Power BI course.

Microsoft Excel

A versatile spreadsheet tool for organizing, analyzing, and visualizing data, widely used across industries.

SAP BusinessObjects

An enterprise-level platform for comprehensive reporting and data analysis, often used in large organizations.

SQL

The standard language for querying relational databases and extracting meaningful data for analysis.

ThoughtSpot

A search-based analytics tool that enables users to run queries using natural language and generate quick insights.

Tableau

Popular for its drag-and-drop interface and advanced visualization capabilities, ideal for storytelling with data.

Google Sheets

Cloud-based spreadsheets that support real-time collaboration and basic data analysis functions.

Sisense

An end-to-end analytics platform that allows users to integrate, prepare, and visualize complex datasets at scale.

Data Analyst vs Data Scientist: A Comparison

Data Analysts focus on interpreting structured data to support business decisions, while Data Scientists build predictive models using advanced statistics and machine learning. Learn more about their key differences in our Data Scientist vs Data Analyst blog.

Analysts use tools like Microsoft Power BI, Excel, and SQL whereas Data Scientists rely on Python, R, and cloud platforms. Analysts typically hold bachelor's degrees with certifications, while scientists often pursue advanced degrees in STEM fields.

Data Analyst Salary and Job Outlook

Data analysts remain in great demand across sectors as companies increasingly turn to data to inform decisions. In the United States, salaries average about $82,000, with experienced practitioners - particularly in technology, finance, and healthcare - making more than $100,000, and some senior positions more than $120,000. The U.S. Bureau of Labor Statistics forecasts a 23% growth in analyst positions by 2032.

For those exploring this path, our Data Analyst Interview Questions with Answers blog can help assess your readiness and identify key areas to focus on.

Why Should You Become a Data Analyst?

Becoming a data analyst offers more than just a stable career. It provides opportunities to work on meaningful problems, grow technical and business skills, and create real impact across industries. Here’s why this path is worth considering:

High Demand and Job Security

Data analysts receive good salaries at both entry and senior levels. With the appropriate skills and experience, professionals can earn much more, particularly in high-growth sectors.

Competitive Salaries and Earning Potential

Data analysts earn attractive salaries at both entry and senior levels. With the right skills and experience, professionals can significantly increase their earning potential, especially in high-growth industries.

Problem-Solving and Analytical Skills

The role requires you to think critically, process intricate information, and derive actionable solutions, making it perfect for people who enjoy solving business puzzles in the real world.

Continuous Learning and Growth

New technologies, techniques, and tools are developed continuously in the analytics space. This generates ongoing opportunities for learning, up-skilling, and career progression. 

Impactful Work

Data analysts play a direct role in shaping business strategy. Their insights can drive decisions that improve products, enhance customer experiences, or boost operational efficiency.

Versatility and Career Opportunities

Skills in analytics are extremely portable across industries and functions, from finance and marketing to healthcare and e-commerce. This flexibility provides several career options. Professionals seeking broader analytics capabilities across hybrid data environments can explore the Microsoft Fabric Analytics Engineer course.

The Ability to Develop Skills

Data analysis promotes both technical and soft skill acquisition - anything from SQL and Python to communication, storytelling, and cross-functional collaboration.

Work in a Variety of Industries

Data analysts are needed everywhere from retail and banking to healthcare and education. This flexibility allows professionals to align their careers with their interests and goals. For those aiming to work in operations or finance analytics, the Microsoft Dynamics 365 Fundamentals (ERP) course is highly relevant.

Preparing for a Data Analyst Career with NetCom Learning

As a Microsoft-awarded learning partner, NetCom Learning offers targeted training programs that help aspiring analysts build expertise in essential tools like SQL, Tableau, Power BI, and Excel. Our role-based courses are designed to align with industry expectations and prepare learners for real-world challenges. To get a head start on interviews prep, check out these Data Analyst Interview Questions with Answers to understand what employers typically ask.

Is Data Analytics a Good Career?

Yes, data analytics is ranked among the brightest and most forward-thinking careers to pursue in today's workforce. With companies using data as much as they do, there remains an ever-growing need for those capable of reading and using it. The profession has good compensation packages, flexibility in one's career, and the chance to work across several sectors including tech, finance, healthcare, and retail. It is also suitable for people who are interested in solving problems and strategy. As data continues to shape how organizations operate, a career in analytics provides long-term stability, impact, and advancement opportunities for those who invest in the right skills and training.

Is Data Analytics a Stressful Job?

As with most analysis positions, data analytics can be stressful, particularly with working with deadlines, high-volume data sets, or life-and-death decisions. Yet, the work isn't necessarily stressful in and of itself - it really matters on environment, expectations, and equipment. Trained and supported analysts using automation software in an engaged collaborative environment usually consider the work engaging and challenging as opposed to suffocating. Efficient time management, good communication, and systematic workflows make huge impacts on mitigating stress levels. For many professionals, the reward of solving meaningful problems and contributing to real business impact outweighs the pressure that may come with the role.

Is Data Analytics Hard to Learn?

Data analytics can be challenging at first, especially if you’re new to technical tools or statistical concepts. However, with a structured learning path and hands-on practice, it is very approachable - even for beginners. Many professionals from non-technical backgrounds have successfully transitioned into data analytics by learning tools like Excel, Power BI, and SQL, and gradually advancing to Python and more complex analysis techniques. The key is consistency, curiosity, and the willingness to apply what you learn to real-world scenarios. With the right training and mentorship, data analytics becomes a practical and valuable skill set that is accessible to anyone.

You can begin by learning cloud basics through the Microsoft Azure Fundamentals course before diving deeper.

What Qualifies You to Be a Data Analyst?

To be a data analyst, you would mostly require a blend of analytical skills, technical skills, and business acumen. Most positions demand expertise in tools like Excel, SQL, and visualization tools like Power BI or Tableau. Knowledge about data cleaning, statistical analysis, and reporting is a must. A degree in a related field like business, statistics, or computer science would be helpful but is not necessary.

Courses like the Microsoft Data Analyst Professional can attest to your capabilities and enhance your employment readiness. Hands-on experience, even via projects or internships, also contributes immense worth.

Can I Be a Data Analyst with No Experience?

Indeed, most data analysts start their professional journey with no experience. It is your capability to learn and showcase basic skills in handling data, analyzing data, and visualizing data that matters most. Entry-level positions usually concentrate on basic tasks such as cleaning up data, producing reports, and developing dashboards. Online courses, getting certifications, and developing portfolio projects can make you stand out as a candidate. Internships or freelance projects can also be stepping stones. By demonstrating your hands-on experience and problem-solving skills, you can easily move into a data analyst position even without official work experience.

What Are Entry-Level Data Analyst Jobs?

Typical entry-level data analyst jobs have job positions like Junior Data Analyst, Business Analyst, Reporting Analyst, and Data Associate. These jobs are about collecting data, cleaning up and preparing datasets, making simple reports, and assisting senior analysts with research and visualization work. Employers require applicants who have the ability to work with Excel, SQL, and visualization tools like Power BI or Tableau. These roles serve as a foundation for learning how data informs business strategy and operations. Entry-level positions are a great opportunity to build technical expertise, gain industry knowledge, and develop the skills needed for more advanced roles.

Do I Need to Be Good at Math to Be a Data Analyst?

You don’t need to be a math expert to succeed as a data analyst, but a solid grasp of basic math and statistics is important. Skills like calculating averages, percentages, correlations, and understanding probability are frequently used. Most of the heavy lifting is done through tools and software, so your ability to interpret results and apply logic is more critical than solving equations manually. With the right training, you can develop the necessary math skills alongside learning how to use tools like Excel, SQL, and Python. In short, comfort with numbers helps but it’s not a barrier.