Hello, everyone! welcome to the insight of data.
A data analyst gathers, organizes, and studies big sets of information. They figure out ways to use data to find answers to questions and solve problems.
Understanding the Role of a Data Analyst.
Before we dive into the roadmap, let’s understand what a Data analyst does. In a Data science project, the data analyst plays a crucial role in the initial stages. They are involved in requirement gathering, analyzing data, creating reports, and providing valuable insights to stakeholders. The entire process involves collaboration with domain experts, business analysts, and other teams.
Skills to become Data Analyst :
1. Python Programming Language
Python is a popular general-purpose programming language. It is used in web development, desktop applications, Data science, machine learning, and many other fields. Fortunately for beginners, Python has a simple, easy-to-use syntax. This makes Python a great language to learn for beginners.
2. Databases (SQL)
SQL (Structured Query Language) is a powerful and essential tool used for querying and manipulating data stored in relational databases. Data analysts leverage SQL to extract valuable insights, perform calculations, and transform raw data into a more meaningful and structured format.
3. Google Sheet and Excel
Google sheet and Excel is a widely used spreadsheet software that plays a significant role in data analysis. It provides a user-friendly interface and a range of tools that make it accessible to users with varying levels of expertise. they both are versatile tool for managing, organizing, and analyzing data. 
3. Business Intelligence with Power BI.
Power BI is a business analytics tool developed by Microsoft that provides interactive visualizations and business intelligence capabilities with an interface simple enough for end-users to create their reports and dashboards. It is part of the Microsoft Power Platform, which includes Power Apps, Power Automate, and Power Virtual Agents. There are various other BI tool like Tableau, QLIK, etc.
Conclusion
By following this roadmap diligently, you’ll equip yourself with the necessary skills to become a proficient data analyst in 2024. Remember, consistent practice and hands-on experience are key to mastering these concepts.