What does a Data Analyst do?

What does a Data Analyst do: Qualification, Skills, and Salary

Summary: Explore the pivotal role of a Data Analyst in transforming raw data into actionable insights through collection, analysis, and visualisation. Discover the qualifications required and steps to embark on a rewarding career in this dynamic field.


As the world becomes data-driven, we are witnessing a massive rise in its application across the industry spectrum. Data Analysts play an integral role in implementing their analysis, thus helping the organisation strategise its future propositions and eventually making the business more productive and profitable.

Owing to the growing penetration of data-based decision-making, the demand for analytics roles in India will rise by 45%. A similar pattern is visible in the global market as well. Hence, it has become one of the most progressive career opportunities. 

Suppose you, too, are looking forward to making a career in this domain. In that case, this blog will run you through the different aspects related to the Data Analyst job profession. 

What is a Data Analyst?

A Data Analyst is a professional who interprets data to inform business decisions, employing statistical techniques and analytical tools. They gather, clean, and organise data from various sources, ensuring accuracy and completeness. 

They present their findings to stakeholders using visualisation techniques, such as charts and graphs, facilitating understanding and actionable insights. Transitioning between data collection, analysis, and reporting phases, 

Data Analysts play a pivotal role in transforming raw data into valuable information. Their skills in programming languages like Python or R and proficiency in database querying enable them to extract meaningful patterns and trends, contributing to strategic decision-making processes.

Roles and Responsibilities of a Data Analyst

The roles and responsibilities of a Data Analyst are crucial in transforming raw data into actionable insights. Data Analysts play a vital role in helping organisations make data-driven decisions that enhance business strategies and performance. Here are the primary roles and responsibilities of a Data Analyst:

  • Data Collection and Analysis: Gather data from various sources, including databases, surveys, and other data collection tools, and analyse it to identify trends, patterns, and insights.
  • Data Cleaning and Preparation: Ensure the accuracy and quality of data by cleaning and preparing it for analysis, removing duplicates, and handling missing data.
  • Statistical Analysis and Modeling: Use statistical techniques and software tools to analyse data, build predictive models, and generate insights.
  • Reporting and Visualisation: Create reports and dashboards to present findings clearly and visually appealingly, helping stakeholders understand complex data.
  • Collaboration: Work closely with other departments, such as IT, marketing, and finance, to understand their data needs and provide support.
  • Data Interpretation: Translate complex data into actionable insights, making recommendations to improve business processes and strategies.
  • Data Governance: Ensure data privacy and security by adhering to data governance policies and best practices.
  • Continuous Improvement: Stay updated with the latest tools, technologies, and industry trends to continually improve Data Analysis processes.

The roles and responsibilities of a Data Analyst are dynamic and evolving, making this position integral to any data-driven organisation.

Essential Skills for Data Analysts

Data Analysis is a complex field that requires a combination of technical and soft skills. Mastering these essential skills for Data Analysts will equip professionals to excel in their roles, driving data-informed decision-making within organisations. Here are some crucial skills for Data Analysts:

  • Data Processing and Analysis: Data Analysts should have robust data processing, cleaning, and analysis skills. They should be proficient in software tools such as Excel and SQL and programming languages such as R and Python.
  • Statistical Analysis: Data Analysts must be familiar with statistical concepts such as probability, hypothesis testing, and regression analysis to analyse and interpret data accurately.
  • Data Visualisation: Data Analysts should be able to create clear and concise visualisations to communicate their findings effectively. They should have expertise in tools like Tableau and Power BI and Python libraries like Matplotlib and Seaborn.
  • Critical Thinking: Data Analysts should be able to analyse and interpret data critically and objectively, which results in more precise and unbiased outcomes.
  • Problem-solving: Data Analysts should have problem-solving skills to identify and resolve data quality, accuracy, and completeness issues.
  • Communication: A data Analyst’s role is not limited to deriving insights and patterns. They should also be able to communicate complex data findings to both technical and non-technical stakeholders. Hence, having expertise in communication language is paramount.
  • Business Acumen: It is essential to comprehend the business objective before working on it. Hence, Data Analysts should have a good understanding of the business and industry in which they work. This includes key performance indicators, industry trends, and business operations.
  • Time Management: Data Analysts often work on multiple projects simultaneously and must manage their time effectively to meet deadlines and deliver high-quality work. 

Salary of a Data Analyst

A Data Analyst’s salary in India varies significantly based on experience, skills, and location. Entry-level Data Analysts can expect to earn between ₹ 1.8 Lakhs and ₹ 13.0 Lakhs annually. On average, a Data Analyst in India earns around ₹ 6.4 Lakhs per year. 

This salary range reflects the demand for skilled professionals who can interpret complex data sets, provide actionable insights, and support strategic decision-making. As businesses increasingly rely on data-driven strategies, the role of a Data Analyst becomes crucial, further enhancing their earning potential and career growth opportunities in the field.

How to Become a Data Analyst

How to Become a Data Analyst

The above discussion highlights the growing popularity of Data Analyst job roles. Suppose you, too, are looking forward to making a career in this domain. In that case, the easiest way is to enrol in a Data Analytics certification program by Pickl. AI. 

This certification course will expose you to the concepts of Data Analytics. However, to enrol in this program, one must have basic Data Analyst qualifications and skills, such as expertise in mathematics, statistics, and programming languages.

Data Analyst Qualifications

Candidates must meet specific educational and professional criteria to qualify as Data Analysts. A bachelor’s degree in statistics, information technology, economics, computer science, or mathematics is essential, as is a minimum 60% or equivalent CGPA.

Additionally, candidates should possess three to four years of practical experience in data mining. This experience is crucial as Data Analysts require theoretical knowledge and hands-on expertise to analyse and interpret data effectively. 

These qualifications ensure that aspiring Data Analysts are equipped to handle the complexities of Data Analysis tasks and make informed decisions based on thorough data insights. These credentials validate proficiency and prepare individuals for the dynamic and demanding role of a Data Analyst in various industries.

Roadmap to Become a Data Analyst

Becoming a Data Analyst involves a strategic roadmap that blends technical skills with analytical insight. This guide outlines essential steps and milestones for successfully navigating this career path.

  • Acquire Fundamental Skills: To build a solid foundation, master Excel, SQL, and basic statistics.
  • Learn Data Visualisation Tools: Familiarise yourself with tools like Tableau or Power BI for effective data presentation.
  • Gain Proficiency in Programming: Learn Python or R for data manipulation, analysis, and visualisation.
  • Understand Data Wrangling: Learn techniques to clean, transform, and preprocess data for analysis.
  • Develop Analytical Skills: Practice interpreting data, drawing insights, and making data-driven decisions.
  • Expand Knowledge of Machine Learning: Gain insights into algorithms, model evaluation, and implementation.
  • Build a Portfolio: Showcase projects demonstrating your analytical and problem-solving skills.
  • Stay Updated: Follow industry trends, attend webinars, and join communities to stay abreast of advancements.

By following this roadmap to become a Data Analyst, you’ll equip yourself with the necessary skills and experiences to thrive in this dynamic field, where the ability to turn data into actionable insights is highly valued. 

Is Data Analysis a good career? 

Is Data Analysis a promising career? Absolutely. In today’s data-driven world, the role of a Data Analyst is pivotal across industries. Data Analysts interpret complex data sets to inform business decisions, identify trends, and solve problems. This role offers substantial opportunities for professional growth and plays a crucial role in shaping organisational strategies.

Data Analysts are in high demand due to their ability to turn raw data into actionable insights. Companies rely on them to make informed decisions, optimise processes, and gain a competitive edge. The job market for Data Analysts continues to expand, offering a variety of career paths in fields such as finance, healthcare, technology, and marketing.

One of the critical attractions of pursuing a career as a Data Analyst is its dynamic nature. It allows professionals to continually learn and apply new skills in Data Analysis, statistical methods, and visualisation. This constant evolution ensures that Data Analysts remain valuable assets in any organisation.

Moreover, the career path for Data Analysts often includes opportunities for advancement into roles such as Data Scientists, business analysts, or even managerial positions. This progression reflects the importance of Data Analytics in driving innovation and efficiency within businesses.

Frequently Asked Questions

What does a Data Analyst do?

Data Analysts interpret large datasets using statistical tools like Python or R to extract insights that inform strategic business decisions. They clean and organise data, create visualisations, and present findings to stakeholders, facilitating data-driven strategies and business growth.

What are the critical roles of a Data Analyst?

Data Analysts play a crucial role in gathering data from diverse sources and cleaning and preparing it for analysis. They apply statistical methods to identify trends, build predictive models, and produce reports and dashboards that guide operational improvements and strategic initiatives across departments.

How can I become a Data Analyst?

To pursue a career as a Data Analyst, develop proficiency in data processing tools like Excel and SQL and programming languages like Python or R. Obtain a degree in statistics, IT, economics, or related fields, and gain practical experience in data mining and analysis to meet industry demands.


Data Analysts play a crucial role in helping organisations make sense of large amounts of data. In the times to come, the role of a Data Analyst will progress. If you are still on the fence regarding your career as a Data Analyst, you can connect with a team at Pickl.AI. You will get answers to all your queries here.



  • Neha Singh

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    I’m a full-time freelance writer and editor who enjoys wordsmithing. The 8 years long journey as a content writer and editor has made me relaize the significance and power of choosing the right words. Prior to my writing journey, I was a trainer and human resource manager. WIth more than a decade long professional journey, I find myself more powerful as a wordsmith. As an avid writer, everything around me inspires me and pushes me to string words and ideas to create unique content; and when I’m not writing and editing, I enjoy experimenting with my culinary skills, reading, gardening, and spending time with my adorable little mutt Neel.