Data Analyst Job Description & Roles and Responsibilities
A data analyst is an individual who collects and interprets data and communicates the findings to help businesses solve problems and make decisions regarding a variety of issues. The data analyst may work with data related to fields like finance, business, science, and even government.
The basic task of a data analyst is to convert unprocessed and unorganised data into essential information which can be further used to understand trends and take up the required steps for further improvement of processes. He or she uses several programming and analytical tools for analysing the data. In this article, we have explained the Data Analyst Job Description. Read more to know about How To Become a Data Analyst.
Data Analyst Job Description
A data analyst’s job is to collect, clean, process, and analyse huge data of the organisations and help them in making informed decisions. A data analyst conveys the findings of analysis by preparing reports or presentations. A data analyst job description involves helping the organisation in searching for solutions to high-level problems.
A variety of tools like SQL, Python, R, and other programming languages are majorly used by data analysts for their analysis. A data analyst also works with stakeholders to offer practical solutions. Insights of a data analyst might be required in tasks like A/B testing, database designing, and improvement of data quality. Strong analytical abilities and attention to detail are useful skills
Also Read:
What are Data Analyst Roles and Responsibilities?
Data Analyst roles and responsibilities majorly involve collecting, processing and analysing valuable data. They are responsible for gathering, sanitising, and classifying data from multiple sources. Continuous learning and staying updated on industry trends are essential for effectively utilising evolving technologies and methodologies in their role. Sometimes, the duty of a data analyst might include the following:
Data Collection: Data collection is a crucial role for data analysts as it forms the foundation for meaningful analysis. Analysts can derive important insights, spot trends, and arrive at wise conclusions from complete and accurate data sets. Effective data gathering guarantees the accuracy and applicability of the information, assisting companies in accomplishing their goals.
Data Visualisation: A data analyst must master data visualization since it reduces complex data sets to easily understood graphics and facilitates the effective sharing of insights with stakeholders who are not technical. Visualizations make data-driven insights accessible and actionable for improved organisational knowledge and strategic planning. They also show patterns, aid in decision-making, and improve comprehension.
Data Security and Privacy: Since data analysts work with sensitive data, data security and privacy are essential. Ensuring adherence to regulations protects unauthorised access and upholds privacy for individuals. Establishing strong security protocols and moral data handling procedures helps the company stay credible, foster confidence, and reduce legal and reputation threats.
Problem-Solving: Data analysts face a variety of difficulties while cleaning, analysing, and interpreting large, complicated databases, therefore problem-solving skills are essential. Finding and fixing problems guarantees data dependability, correctness, and insightful information that supports well-informed decision-making. It also helps organisations succeed by improving the general efficacy of data-driven tactics.
Database Management: The efficient organisation, storage, and retrieval of data make database management nt an essential skill for data analysts. Data analysts use software like SQL to access and modify data correctly. Database management improves the quality of analysis which helps the company in making better plans and strategies.
Career Progression of Data Analysts
A data analyst job duties begin at the entry-level roles and gains knowledge and skills to advance to senior positions. Starting as a Junior Data Analyst, the roles in the career of data analyst advance to positions like Mid-Level Data Analyst and Data Manager. This upgrade also comes up with various challenging tasks and responsibilities. Below we have mentioned some of the Data Analyst Job Description along with the career progressions.
Junior Data Analyst: An Entry-Level data analyst duties and responsibilities involve carrying out basic tasks like gathering and cleaning small databases, simple analysis, and adding insights derived from the analysed data. In this position, a data analyst learns the fundamentals of data analysis and visualization while working under the supervision of trained and more experienced team members.
Mid-Level Data Analyst: A mid-level data analyst uses predictive modelling and sophisticated statistical tools to work on increasingly complicated data analysis tasks. They offer insights to stakeholders, guide more junior analysts, and participate in strategic decision-making. Their advanced abilities are essential for deciphering data patterns and making practical suggestions. They must never stop learning as they advance to more senior data analytics positions.
Senior-Level Data Analysts: Senior Data Analysts, with years of experience, lead complex analytical projects, provide strategic insights, and mentor junior analysts. By utilising sophisticated statistical methods and their knowledge of data interpretation, they make a substantial contribution to organisational decision-making. Senior data analysts are essential in developing data strategies. They can go on to become managers or develop further specialisations in different fields.
Data Analytics Manager or Director: A Data Analytics Manager or Director oversees the strategic implementation of data analytics within an organisation. A manager oversees the efficient use of data to inform corporate choices, set goals, and manage teams. Among the duties are creating data-driven plans, overseeing resources, and coordinating analytics initiatives with overarching corporate objectives.
Data Analyst Job Qualification
The basic qualifications required to become a data analyst include graduation in subjects like mathematics, computer science, or statistics. Some employers may ask for higher qualifications like a Masters's degree or specialised certification courses relevant to the field to discharge data analyst duties properly. Excellent knowledge of programming languages and data visualization is also preferred as an important aspect. Some options are listed below:
Bachelor Courses:
Master degree Courses:
What are the Skills Required to Become a Data Analyst?
Data analysts work description states some required skills like detailed analysis, proficiency in programming languages, and good knowledge of data visualization. They should possess a solid understanding of statistics, mathematics, and database management. Effective communication, problem-solving abilities, and attention to detail are crucial.
Continuous learning and adaptability to emerging technologies are essential to navigate the evolving landscape of data analytics. Here are some key skills required to perform data analyst job duties:
- Analytical skills
- Programming skills
- Data analysis
- Problem-solving
- Attention to detail
- Communication skills
- Data Visualization
Data Analyst Top Recruiters
Data Analytics recruitment involves identifying candidates with strong analytical, statistical, and programming skills. Employers seek individuals with a background in statistics, mathematics, or computer science, and proficiency in SQL and Python.
Strong problem-solving abilities, business acumen, and effective communication skills are also crucial. The top recruiters for Data Analytics roles include major technology and consulting firms. Some of the top recruiters include:
- Amazon
- Genpact Data
- Microsoft
- TCS
- Accenture
- Tech Mahindra
- Wipro
- Infosys
Related:
Salary of Data Analysts in Popular Companies
The salary of a Data Analyst in India can vary based on factors such as experience, location, industry, and the organisation's size. The industry's rising demand for data analysts has also helped improve the salary structure. Here are the average salary structures for Data analysts and other related careers.
| Role | Average Annual Salary (Rs.) |
|---|---|
Microsoft | Rs. 17.10 Lakhs |
Amazon | Rs. 8.30 Lakhs |
Accenture | Rs. 7.60 Lakhs |
Tech Mahindra | Rs. 6.10 Lakhs |
TCS | Rs. 6 Lakhs |
Genpact | Rs. 6 Lakhs |
Source: Ambitionbox, Glassdoor
You May Also Like:
- Career Options for Maths Students
- Top 10 Best Career Options for Science Students
- Career Options After MBA – Highest Paying Management Jobs
- Top 10 Best Career Options in the Future [In-demand Jobs of the Future]
- Career Options after 12th PCM other than Engineering
Conclusion
Data analytics is a dynamic field in today's data-driven world. High-quality and competent analysis is required to help businesses make informed decisions about market trends and customer behaviour based on the available data. It helps in innovation and informed decision-making. The power of harnessing useful information from big data has helped data analysts shape businesses and industries in the most innovative ways in history.
Frequently Asked Questions (FAQs)
To become a data analyst, one must first earn a bachelor's degree that is required for most of the candidates enjoyinh the entry-level data analyst positions. The relevant disciplines are Computer Science, and Information Management.
Some of the most popular data analyst tools include SQL, Pyton, Tableau, Power BI, Google Analytics and more.
Both internships, and projets are an excellent way to gain practical experience in working with real-world data, and tools so that one can showcase their proficiency. This practical experience though not necessary can be of great help to budding data analysts.
Data analysts should keep updating their skills regularly as many times as possible. This will allow them to keep pace with the always evolving field of data science.
Programming knowledge is important for a data analyst since it helps with the automation of tasks. Proficiency in programming languages like Python or R is essential for being able to perform complex data analysis.
Articles
Questions related to
Yes. No doubt it will be beneficial. It is only going to open doors for you when you move towards getting a job. The certificate of data analytics will make your resume more complete.
Combination of BBA and data analytics is always good and does help in the future. With the help of certificate in data analytics, you can get into business analytics if you have great analytical skills.
Hello aspirant,
Hope you are doing well
Both the courses you mentioned are equally good .
The job roles offered for both the courses are pretty good.
Firstly it is important to know the course in which you are interested and then take up that .
Hope this helps you
All the best!
BSc Data Science is a 3 year full-time course that comes under the domains of Computer Science, Business Analytics and Artificial Intelligence.
Data Science is an interdisciplinary subject that includes the use of Statistics , Big Data Analytics , Machine Learning and related aspects in order to understand the problem or phenomena with respect to a set of real-world data.
This course is highly popular among students in India and Abroad because of its increasingly high demand and diverse future scope in tech companies, consultancies, market research companies and energy sector.
Admission to this course usually takes place on the basis of merit and performance in the university level Common Entrance Tests. The minimum eligibility required is the completion of Class 12 with Science stream (Physics, Chemistry, Mathematics).
IT is a particular subject with data science.
Thanks!
So you can have a rough idea about the two courses but which one is better is something only you can decide as you will know better which subject interests you more.
Hello Apu sarkar, Both the Universities are best for bsc and infastructure is also good but facilities are more in TIU like sports campus, wifi campus, and many more and they all are not in MAKAUT and placement is also good at TIU. So I personally preferred you to go for TIU.
Hope it will be helpful for you :)