How to become a Data Analyst in 2023?| Complete Roadmap

July 5, 2023

Complete Roadmap for Data Analyst

Here you will find in detail, How to become a Data Analyst in 2023: Complete roadmap, skills required and much more.
Data Analyst is a professional who collects, analyzes, and interprets large volumes of data to uncover meaningful insights and inform business decisions.

Table of Content :

Who is a Data Analyst?
What is Data Analysis?
How to become a Data Analyst?
Roadmap to become a Data Analyst.
- Skills required to become a Data Analyst.
Salary of a Data Analyst

Who is a Data Analyst?

A professional who gathers, organizes, analyzes, and interprets data to provide valuable insights and support decision-making processes within an organization. They work with large volumes of data from various sources, such as databases, spreadsheets, and other data repositories, and use analytical tools and techniques to extract meaningful information.

What is Data Analytics?

Data analysis is the process of inspecting, cleansing, transforming, and modeling data to uncover useful information and draw conclusions. It involves examining large datasets to identify patterns, trends, and relationships that can provide valuable insights. Data analysis employs various techniques such as statistical analysis and predictive modeling to extract meaningful information from raw data. Ultimately, data analysis enables organizations to make informed decisions, optimize processes, and identify opportunities for improvement.

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How to become a Data Analyst in 2023?

The most common question who can become a data Analyst, answer to this question is anyone can become if they possess some required skills, have a great knowledge of statistics and sense of programming language too. Students from Technical background as well as Non-Technical background can become a data analyst after having the above mentioned skills.

Responsibilities of a Data Analyst

Data Collection: Gather data from various sources, such as databases, spreadsheets, APIs, and other relevant sources. Ensure data accuracy, completeness, and reliability.
Data Cleaning and Preprocessing: Cleanse and preprocess data to remove errors, inconsistencies and missing values. This step involves transforming, reformatting, and structuring the data appropriately.
Data Analysis: Apply statistical techniques and data mining methods to analyze and explore datasets. Identify patterns, trends, and correlations within the data to extract valuable insights.
Report Generation: Create clear and concise reports, dashboards, and visualizations to present findings and communicate results effectively to stakeholders. Use tools like Excel, Tableau, Power BI, or other data visualization software.
Data Quality Assurance: Perform quality checks on data to ensure accuracy, consistency, and integrity. Validate data against predefined metrics and standards, and address any data quality issues.

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Skills required to become a Data Analyst for both Tech and Non-Tech

Excel
Maths and Statistics
BI Tools
Programming

Data Analyst Roadmap 2023

6 Steps to Become a Data Analyst in 2023

1. Excel:

Excel is the first step you should learn for this specific role. Most of the student ignore this skill but without excel you will not be able to learn this Course. Excel is divided into different Sub-parts.

Topics to cover on priority basis

BASIC : SUM, AVERAGE, MEAN, MEDIAN, SUM PRODUCT, CONCATENATE

STATISTICS : VLOOKUP, INDEX, MATCH, XLOOKUP, IF, COUNTIF, SUMIF

KEY FORMULAS : Remove Duplicates, Conditional Formatting, Pivot Yable, Pivot Chart

2. Mathematics and Statistics:

This is the second step towards this role. You need to have a good calculation, mathematics and problem solving skill. It helps in an organization to solve problems and effectively apply complex data in any type of business challenges.

Here are some topics you need to study in Maths and Stats.

MATHEMATICS : Average, Arithmetic, Percentile, Cumulative Sum

STATISTICS : Mean, Median, Mode, Standard Deviation, Normal Deviation

3. SQL:

It is a programming language which manipulates and reads data to help the analyst to analyze the data and make the best possible outcome.

Here are some topics you need to study in SQL

BASIC QUERIES : WHERE, INSERT, UPDATE, SELECT, BETWEEN, LIKE

ADVANCE QUERIES : CTE, Data Time Function, Window Function

JOINS : Left, Right, Inner, Outer

4. Programming:

You need to learn the programming language R and Python. But most preferrable language is Python because, Python is an incredibly powerful and popular programming language that has become a go-to tool. It offers a wide range of libraries and frameworks specifically designed for data analysis, making it a versatile and efficient choice.

Topics to Learn

Topics: Variables, Function, Class and Object, Lists, Tuples, Data Types, Modules

Python Libraries: Pandas, Matplotlib

5. BI TOOLS:

BI tools are extensively used to gather, analyze, visualize, and present data to support decision-making processes. These tools provide a range of functionalities that enable them to extract valuable insights from complex data sets.

These are some of the tools:

Power BI

Tableau

6. Additional Skills:

You need to have a good command on the skills given below, also you must have an account on LinkedIn and GitHub to make your profile better.

Skills:

Communication Skill

Business Solving Skill

Problem Solving Skill

GitHub

Projects

To know more about Data Analyst, Complete roadmap and the skills required required. Click on the link given below and do checkout our video.

Salary of a Data Analyst

The Average salary of a Data Analyst varies depending upon the different Job Role and the amount of experience they have in this field.

Years	Salary Per Annum
Fresher	3 – 3.5 LPA
1-3 years	4 – 5 LPA
3-5 years	5 – 7 LPA
Experienced	8 – 13 LPA

FAQ's on How to become a Data Analytics in 2023

How to begin with Data Analytics?

Study the effective skills. Learn programming language and enhance in essential tools to start with and master this. On this page you will get all the information and skills that will help you in becoming a Data Analytics.

What are the languages needed for Data Analytics?

Languages necessary for Data Analytics:

R
Python
SQL

SQL is very important for Data Analytics and among Python and R, you should prefer Python.

What are the tools necessary for Data Analytics?

Proficiency in tools like:

Excel
Power BI
Tableau

How is a data analyst different from a data scientist?

While there is some overlap between the roles of a data analyst and a data scientist, there are also key differences. A data analyst primarily focuses on analyzing existing data to extract insights and provide reports or recommendations. Their work often involves data cleaning, statistical analysis, and data visualization.

Click here to know about “Data Science”

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