Education Programs for Professionals | Careerhigh

Roadmap to become a Data Analyst





Data analyst is the one who has substantial understanding and abilities which they use to transform the raw facts into records that is helpful for the business to make choices.



  • In India, the average salary of entry-level Data Analyst is ₹325,616.
  • In India, the average salary of a mid-level Data Analyst is ₹635,379.
  • In India, the average salary of an experienced Data Analyst is ₹852,516.



The first and foremost, a data analyst needs to discover the organization`s goal. They need to investigate the resources, understand the business problem, and gather the proper facts. A data analyst-

  • Uses tools to extract data points from multiple primary and secondary sources.
  • Removes corrupted data points and solves coding mistakes and associated issues
  • Develops and retains databases, data systems – reorganizes data in a readable layout
  • Evaluates and analyses the quality and meaning of data
  • Reviews reports and performance indicators to filter data and identifies and correct code issues
  • Uses statistical gears to discover, analyse, and interpret patterns and trends in complicated data that might be beneficial for the diagnosis and prediction
  • Creates final reports for the stakeholders to take essential decisions based on the analysed data



An effective data analyst must have technical skills as well as leadership skills. While there are no definite training requirements for a data analyst, a background in mathematics, statistics, computer science, information management, or economics could be beneficial to build a career in data analyst profile.

i. Technical Skills

  • Solid mathematical skills to help collect, measure, organize, and analyse data
  • Knowledge of programming languages such as MATLAB, Oracle, R, SQL, and Python
  • Proficiency in database design building, data modelling, data mining and segmentation techniques.
  • Experience in managing reporting software packages such as Business Objects, programming (XML, ETL frameworks or JavaScript), databases etc.
  • Proficient in statistics and statistical packages such as SAS, SPSS or Excel used to analyse sets of data
  • Ability to use data processing platforms such as Apache Spark and Hadoop
  • Knowledge of data visualization software such as Qlik, Tableau, etc.
  • Knowledge of how to create and apply the most accurate algorithms to the dataset to find the solution
  • Proficient querying, report writing and presentation
  • Familiar with the three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.


ii. Soft skills

  • Communication skills - A data analyst's data is useless if he lacks the communication skills to make his findings understandable.
  • Problem Solving - Data analysts also use their problem solving skills when collaborating with their team on big problems and find the solution.
  • Research - You might think that all information is available to data analysts, but that is not the case. The truth is they should be prepared to dig if they want to get the most out of the data they collect.
  • Attention to detail - Data analysts must be attentive to identify and solve small errors that can lead to larger problems in the system.
  • Teamwork - Data analysts must be good at teamwork as they have to work with several teams like data scientists, web developers, etc.


iii. Minimum skills required

The skills needed for an entry-level job as a data analyst are as below:

  • Basic Understanding of Microsoft Excel: To find a job as a data analyst, you need to be familiar with Microsoft Excel. You can also learn Excel from YouTube. Some recommended videos are as follows:
  • Microsoft Excel Tutorial for Beginners | Excel Training | FREE Online Excel course (2021)
  • Microsoft Excel Tutorial for Beginners | Excel Training | Excel Formulas and Functions | Edureka
  • Microsoft Excel Tutorial for Beginners - Full Course
  • Good statistical knowledge: You need to be familiar with the statistics and distributions that are essential for data analysis. Also familiarity with inference and descriptive statistics, binomials and testing, and experimental and statistical design are required.
  • Video tutorial for statistics: Statistics for Data Science Course | Probability and Statistics | Learn Statistics Data Science
  • Powerful hands in mathematics: For entry-level work, you need to translate a word problem into a mathematical formula. You also need to be an expert in algebraic expressions, multivariable calculations, and solving different types of functions.
  • Some of the must have soft skills are communication skills and attention to details.



  • Get a bachelor's degree from a recognised university. A bachelor’s degree in an area that emphasizes statistical and analytical skills can be an added advantage.
  • Get a master's degree in data analytics (optional) and you could become a data engineer and later on be a data scientist.
  • Learn data analysis skills
  • Consider getting a certificate in data science or business analytics
  • Try to do some internships which are related to the data analyst background
  • Convert your first job as a data analyst 

One of the most important things is to emphasize your work on your resume and provide a nice looking answer. Create a well-designed and well-articulated resume. Also highlight your skills on your resume. Therefore, it is very important to write your resume very carefully while practicing the questions that are mainly asked during interviews of that of data analysts.



If you're considering becoming a data analyst but having no prior industry experience, you can start with a degree in an online data analyst course. The course will strengthen your foundational knowledge of the subject, also allowing you to build hands-on projects and you can learn and develop your skills. Later you can do an internship or get a freelance job to gain experience. Highlighting your data analyst skills, internship and freelance job in resume would help you to grab job easily.



There are many online data sources available for free datasets to use in your project. Here are some of the pages you might find useful:

Some project examples are given below that would be helpful to you for preparing your own projects:

Try creating your own project with several datasets. You can follow these steps:

  1. Put together a working project that touches on all phases of data analysis.
  2. Researching companies and market opportunities, establishing the parameters of the data you need to collect, gathering and cleaning that data, then modelling and analysing it using custom-built algorithms.
  3. Finally, transform the insights you gain from your work into beautiful visualizations and organize them into dashboards so that others can query and interact with your dataset in a user-friendly way.
  4. Participate in a series of hands-on projects to manipulate different types of data, mining structured data, text and images, audio, and even video, performing statistical analysis, identifying causal relationships, and making predictions.
  5. Expand and demonstrate your capabilities.
  6. Data analysts also need to be able to present results using these visualizations.
  7. Now that your project is ready, create a portfolio and show off your skills on your resume.


Do I need coding skills to become a data analyst?

No major programming skills are required, as described in Minimum Required Skills. No special coding specialists are required to become a data analyst, but experience in analytical software, data visualization software and data management programs are required.

The only important skill you need to have is the ability to understand and derive knowledge from the data. If you don't think you're a programmer, GUI tools are for you. The Graphical User Interface (GUI) is a type of user interface that allows users to interact with electronic devices through visual indicator representations. There are many such tools. You can start with old-fashioned Excel and move to more mature tools like Tableau and some RGUIs like R Commander and Rattle.



  1. Mu Sigma analytics
  2. Accenture Analytics
  3. Fractal Analytics
  4. Manthan
  5. Absolut Data
  6. Cartesian Consulting
  7. Latent View
  8. Unmetric  
  9. Convergytics 
  10. SIBIA Analytics



Students may be required by the university to do an internship to complete their research. In other cases, students can apply for an internship and gain work experience before embarking on a career as a full-time data analyst.

As a data analyst intern your day to day work responsibilities may differ from company to company some basic skills needed would be knowledge in excel, basic coding skills, good business communication skills, understanding of the terminology.

You can get plenty of opportunities in the field of data analyst intern through various job portals like LinkedIn,,, etc.

i. Internship fields

Some of internships that would be helpful for you to get a job as a data analyst in the future are mentioned below:

  • Data Analytics Intern
  • Business Analytics Intern
  • Data Engineering Intern
  • Excel Operator Intern
  • SQL Developer Intern
  • Power BI Intern
  • Data Entry Intern

ii. Companies hiring Data Analyst Interns:

Big tech companies like Google, Facebook, Amazon, Airbnb, Uber, etc. various start-ups, data analytics software providers like Tata Consultancy Services, Tech Mahindra, Capgemini India Pvt ltd, Genpact, ITILITE Bengaluru, Accenture Analytics, Ezzix Mumbai, Anaxee Digital Runners Private Limited, etc.



• Data analysts will play a major role in the market over the next few years. They will be recognized as a privacy advocate. They will protect data privacy and detect intruders.

• The Internet of Things acronym IoT is about to grow tremendously. The management, analysis, and security of large amounts of both structured and unstructured data generated by the IoT will continue to occupy a significant position in the market.

• There will be a tremendous growth in the field of cognitive analysis.

• Companies will be using data to generate financial gains and securing the scope of future in data analytics.

• Demand for data scientists will increase significantly.



  • Entry-Level Data Analyst- After doing your internship, your next step would be to get your first job as entry level data analyst or junior analyst. Your job would be to work closely with business stakeholders and use your skills which you have attained during your internship.
  • Mid-Level or Senior Data Analyst- The next typical step after gaining one or two years of experience would be to progress to a senior position. In this position, you will be taking ownership of the data processes in the company and also you’d manage a team of analysts.
  • Specialist data analyst career paths- Some of the data analysts will progress to senior management positions to focus on the overall data strategy of the company and to manage various other analysts. Some of the specialist job titles are: Digital marketing analyst, Financial analyst, Social data analyst, Insurance underwriting analyst, Healthcare analyst, Systems analyst, Machine learning analyst, etc.
  • From data analyst to data scientist- one of the popular routes that data analysts take is to move into a data scientist role. One specific skill that would help you form a strong foundation this transition is your data analysis skill.
  • Working as a data analytics consultant- after having a working experience of good six or seven years, you can work as a data analytics consultants. They do the same work of that of data analyst but for a number of clients and not just for one company. However, this is something that you might consider further down the line but before that the most important thing in your starting years is to gather more skills and experience.