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Data Analyst Roadmap – A Complete Guide

Last Updated : 04 Mar, 2024
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Dreaming of a career where you unlock the secrets hidden within data and drive informed business decisions? Becoming a data analyst could be your perfect path! This comprehensive roadmap unveils everything you need to know about navigating this exciting field. Whether you’re a complete beginner or looking to transition from another role, we’ll guide you through the essential skills, educational paths, and tools you’ll need to master to become a data analyst. Explore practical project ideas, conquer job search strategies, and discover the salary potential that awaits a skilled data analyst. Dive in and prepare to transform your future – your data-driven journey starts here!

How to Become Data Analyst

Data analyst demand is skyrocketing! This booming field offers amazing salaries, and growth, and welcomes diverse backgrounds. Ready to join the hottest IT trend? Our step-by-step roadmap equips you with the essentials to launch your data analyst career fast. Don’t wait – land your dream job today!

Did you know Bengaluru ranks among the top 3 global data analyst hubs? Have a look at the list:

  1. San Jose, California
  2. Bengaluru, India
  3. Geneva, Switzerland

Get ready to unlock exciting opportunities! Buckle up and let’s connect the dots to your data analyst future.

Join ourComplete Machine Learning & Data Science Program to master data analysis, machine learning algorithms, and real-world projects. Get expert guidance and kickstart your career in data science today!

What is Data Analysis?

The process of collecting and processing the raw data and preparing the required statistics are what data analysts do. Their job responsibilities rotate around this and it’s likely less typical than that of a Data Scientist. However, they play a very major role in taking business decisions (that being taken based on their extracted data and stats) and identifying the pain points of customers that eventually helps businesses in changing their approach for better growth. 

Who is a Data Analyst?

A data analyst is a professional who collects, cleans, analyzes, and communicates insights from data. They work in various industries, helping organizations make informed decisions based on evidence. Here’s a breakdown of their responsibilities:

1. Data Gathering and Cleaning:

  • Data analysts collect information from various sources like surveys, website records, financial data, or scientific experiments.
  • They then meticulously clean and organize the data, ensuring its accuracy and completeness before further analysis.

2. Data Analysis and Pattern Identification:

  • Using statistical methods, programming languages, and data visualization tools, analysts explore and analyze the data.
  • They search for patterns, trends, and anomalies, revealing hidden connections and insights within the information.

3. Insight Communication and Reporting:

  • A crucial skill for data analysts is translating complex findings into clear, concise, and actionable insights that stakeholders can understand and use.
  • This often involves creating reports, presentations, and dashboards that effectively communicate the data’s story.

4. Problem-Solving and Performance Optimization:

  • Data analysts go beyond interpreting data; they use it to solve problems and improve processes in various contexts.
  • This might involve analyzing customer behavior to optimize marketing campaigns, identifying fraudulent transactions in financial systems, or predicting equipment failures for better maintenance schedules.

What Does a Data Analyst Do?

There might be some questions in your mind like How to become a data Analyst or Is it hard to be a data analyst? Well, to answer all of these, you need to first understand step-by-step before entering this domain. To better clarity, let’s find out the responsibilities in a data analysis job during their day to day schedule.

Responsibilities of Data Analyst

Well, that depends upon the type of organization that you’ll be working on because nowadays every industry is looking out for such professionals despite their size (small-medium-large). Although, some of the key responsibility includes:

  • To develop and analyze the report
  • To manage master data right (create -> update -> delete)
  • To support the data warehousing in inspecting the reporting requirements. 
  • To troubleshoot the reporting DB environment and reports.
  • Coordinating with developers, and engineers to gather insight for improvement and making modifications for data governance.
  • Use of statistical tools to interpret data sets, and to follow any ongoing trend that could be valuable.

Why Data Analyst?

Being a Data Analyst you will be working on real-life problem-solving scenarios and with this fast-paced, evolving technology, the demand for Data Analysts has grown enormously. Moving with this pace of advancement, the competition is growing every day and companies require new methods to compete for their existence and that’s what Data Analysts do. Let’s understand the Data Analysts job in 4 simple ways:

  1. Being a Data Analyst, you’ll be working closely with the raw data and will generate valuable insights that will help companies to decide their future goals.
  2. If you’re someone who likes thinking out of the box then you are the perfect fit for this domain. Data Analysts help organizations to work with both business and data closely. This eventually maximizes the output for generating more business values.
  3. Nevertheless, this field gives you a handsome salary for all levels of expertise. Being a Data Analyst you can earn more than $80k per annum and around 4LPA in India (for starting level).
  4. According to multiple reports, the demand for Data Analysts job are high VS the supply to the market is comparatively less and that’s one of the reasons why people are shifting their career to Data Science. Till now, there are more than 28,000 job postings available in India and 414,000+ jobs are available worldwide. 

Types of Data Analysts

There are many different types of data analysts, each specializing in a specific area or industry. Here are some of the most common types :-

  1. Business Intelligence Analysts: Analyze business data for insights, informed decisions, and performance improvement.
  2. Financial Analysts: Focus on financial data for budgeting, investments, and market trends analysis.
  3. Healthcare Data Analysts: Work with healthcare data for patient outcomes, operational optimization, and medical research.
  4. Marketing Analysts: Analyze marketing data for campaign effectiveness, consumer behavior, and market trends.
  5. Operations Analysts: Optimize processes by analyzing operational data, enhancing efficiency, and reducing costs.
  6. Sports Analysts: Analyze sports data for performance evaluation, strategy improvement, and player/team assessment.
  7. Crime Analysts: Analyze crime data for pattern identification, assisting law enforcement in prevention and solving.
  8. Environmental Data Analysts: Analyze environmental data for ecological trends, climate patterns, and human impact assessment.
  9. Social Media Analysts: Analyze social media data for user behavior understanding and insights for marketing strategies.
  10. Economic Analysts: Study economic data for trend understanding, economic condition forecasting, and policy insights.

Can Anyone Become a Data Analyst Without Any Experience?

First, understand this, the field of Data Analyst is not about computer science but about applying computational, analysis, and statistics. This field focuses on working with large datasets and the production of useful insights that helps in solving real-life problems. The whole process starts with a hypothesis that needs to be answered and then involvement in gathering new data to test those hypotheses. There are 2 major categories of Data Analysts: Tech and Non-Tech. Both of them work on different tools and Tech domain professionals are required to possess knowledge of required programming languages too (such as R or Python). 

The working professional should be fluent in statistics so that they can present any given amount of raw data in a well-aligned structure.  

So, the answer to that is YES, anyone can become a Data Analyst if they like working on a real-life problem, are good with statistics, and always thinks out of the box. So, now let’s see how to build a successful data analyst career.

Average salary of a Data Analyst in India

Freshers (Less than 1 Year):

  • Average Salary: ₹3.25 Lakhs per annum (LPA)
  • Range: ₹2.5 LPA – ₹4 LPA
  • Focus: Building foundational skills in data analysis tools, SQL, and basic statistics.

Early Career (1-4 Years):

  • Average Salary: ₹4.94 LPA
  • Range: ₹4 LPA – ₹6 LPA
  • Focus: Refining analytical skills, exploring specific data analysis techniques, and gaining work experience on real-world projects.

Mid-Career (5-9 Years):

  • Average Salary: ₹7.75 LPA
  • Range: ₹6 LPA – ₹10 LPA
  • Focus: Specializing in specific areas like Machine Learning, Big Data, or industry-specific analysis. Taking on leadership roles and managing projects.

Late Career (10-19 Years):

  • Average Salary: ₹10.63 LPA
  • Range: ₹8 LPA – ₹15 LPA
  • Focus: Leading complex data analysis projects, mentoring junior analysts, and providing strategic insights to stakeholders.

Experienced (20+ Years):

  • Average Salary: ₹15 Lakhs and above
  • Focus: Senior leadership roles, managing large teams, and driving data-driven initiatives across the organization. Expertise in cutting-edge data analysis technologies.

How to Become a Data Analyst : Roadmap – Skills Required 

To become a data analyst, it’s essential to develop a strong foundation in mathematics and statistics. These skills form the backbone of data analysis, allowing you to understand and interpret complex datasets. Additionally, proficiency in programming languages like Python, R, or SQL is crucial for manipulating data and performing statistical analysis. Practical experience through real-world projects and certifications can further enhance your skills and make you more competitive in the job market. Continuous learning and staying updated with the latest trends and technologies in data analysis are also key to success in this field.

Data Analyst Roadmap

1. Mathematics and Statistics

Mathematics

Statistics

For Tech Domain

Programming Languages

Learning Edge – Also refer to the below-mentioned articles to get the full insight:

Required Skills for Data Analysts (Basic)

  1. Problem Solving
  2. Database Knowledge
  3. Data Wrangling
  4. Communication Skill

To learn more about Database with Python, refer to this article: Python Database Tutorial

Required Tools for Data Analysis (Tech)

  1. MS Excel
  2. Tableau
  3. RapidMiner

For Non-Tech Domain

Skills

  1. Domain Knowledge: Having general background knowledge of the field/environment in which you’ll be working is mandatory so that accurate methods and tools can be applied.
  2. Problem-Solving Skill: A data analyst must always be prepared to perform troubleshooting when any issue arises that’s why problem-solving skills become crucial while analyzing data.
  3. Computer Skills: At any point in time, any query can arise and to figure that out you must know to find out the solution so carrying basic skills related to computers is a ‘must to have’ skill.
  4. Dashboarding: To properly analyze any given set of data would require you to perform dashboarding. It helps in bringing all data together and displays all key metrics and insights.

Required Tools for Data Analysis (Non-Tech)

  1. MS Excel
  2. SAP
  3. Power BI

Best Courses For Data Analysts

To make a strong grip in this field will require you to have hands-on practice in some of the most crucial skills, which we’re mentioning below for the best reference:

SQL Foundation – Self-Paced

It’s best especially for beginners to understand the basics of handling data.

Data Analysis with Python – Self-Paced

This course is a perfect choice to brush up on skills to work with large sets of data.

Google Data Analyst Professional Certificate

Covers essential data analysis skills like data cleaning, manipulation, and visualization.

Microsoft Certified Azure Data Analyst Associate: 

Focuses on using Microsoft Azure cloud platform for data analysis.

CompTIA Data+

A vendor-neutral certification that validates foundational data analysis knowledge.

SAS Certified Base Programmer

Demonstrates proficiency in using SAS software for data analysis.

Career Path of a Data Analyst

Career Path of a Data Analyst

Data Analyst Career Path

  • Data Scientist
    • Senior Data Scientist 
    • VP / Director
    • Chief Data Officer / Chief Data Scientist
  • Business Insights / Business Analyst
    • Senior Business Analyst
    • Analytics / Engagement Manager
    • Head of Analytics
  • Management Consultant / Senior Analyst
    • Engagement Manager
    • Principle
    • Partner
  • Financial Analyst
    • Portfolio Manager
    • Group Finance Manager
    • CFO

Future Scope of Data Analyst

Today, Billions of companies are generating data on a daily basis and using it to make crucial business decisions. It helps in deciding their future goals and setting new milestones. We’re living in a world where Data is the new fuel and to make it useful data analysts are required in every sector. The more data – the more requirement and thus it is projected that the market share of data analysts are likely to grow by USD 650+ Billion at a CAGR of above 13% and that’s what makes it among the most sought-after profession in the world. So, the answer is YES, it’s an excellent choice to start your career towards becoming a successful Data Analyst.

Conclusion

In conclusion, data analysis offers a promising career path with high demand and attractive opportunities. Bengaluru ranks among the top cities for data analyst jobs, highlighting the global need for skilled professionals in this field. Data analysts play a crucial role in collecting, analyzing, and communicating insights that drive informed business decisions. Whether you’re just starting or looking to advance your career, mastering skills in mathematics, statistics, and data tools is essential. With the right skills and experience, you can embark on a rewarding journey as a data analyst, contributing to the ever-growing importance of data in shaping the future of businesses worldwide.

FAQs

How To Become a Data Analyst?

Step guidance to Become a successful Data Analyst:

  • Learn Programming Language first (Python, or R)
  • Build basic skills (such as Problem-solving, DB, Data Wrangling, etc.)
  • Start building a strong knowledge of basic tools (such as MS Excel, Tableau, etc.)
  • Try getting hands-on practice on Real-life projects for better clarity
  • Opt for a relevant certification/course which will add value to your portfolio
  • Start applying for entry-level jobs to begin your journey

What does Data Analyst do?

Data Analysts are responsible for developing and managing reports to solve and project different data. Besides this, a data analyst should have the knowledge and skills to turn any provided raw data into insightful ones that can directly impact any taken business decisions.

What can I do after the 12th to become a data analyst?

If you’re looking to get into the field of Data Analyst, then you must possess a degree in Computer Science or any relevant degree in the field of Statistics, Mathematics, etc. However, it is also to be noted that the necessary candidate should possess some of the necessary skills that are required in becoming a Data Analyst, these are:

  • Problem Solving
  • Strong Communication Skill
  • Knowledge of Database
  • Data Wrangling (Collection, Cleaning & Visualization)
  • MS Excel
  • Tableau
  • Power BI, etc.

What is required to become a data analyst?

To be a data analyst, master SQL, Python, and data visualization. Develop soft skills, explore education options, and build a portfolio for success in this dynamic field.

Is Python required for data analyst?

Python is crucial for data analysts, being the top programming language in demand, easy to learn, versatile, and powerful. Key tools like Jupyter Notebook and Pandas are Python-based, providing a competitive edge. Python skills also lead to higher salaries, with an average of $103,059 compared to $88,244 for those without.



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