If you are beginning your journey into data analytics, one of the first questions that probably comes to mind is
Should I start with Excel or SQL
Both tools are essential in the world of data, and each has its strengths. The answer depends on your background, goals, and how you plan to use data analytics in your career. In this post, we will break down the differences between Excel and SQL, what they are best used for, and which one makes more sense to start with in the year twenty twenty five.
What is Excel
Microsoft Excel is a spreadsheet tool that allows you to store, organize, and analyze data. It is known for its user-friendly interface and is widely used in business, finance, marketing, and entry-level analytics roles.
Key features of Excel include
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Formulas and functions for calculations
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Pivot tables for summarizing data
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Charts and graphs for visualization
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Simple filtering and sorting options
What is SQL
SQL or Structured Query Language is a programming language used to communicate with databases. It allows you to extract, manipulate, and manage large volumes of structured data stored in relational databases.
Key features of SQL include
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Query and filter large datasets
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Join multiple data tables
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Aggregate and group data
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Use in most enterprise-level systems and applications
Excel versus SQL - A Comparison
Ease of Use
Excel is very beginner-friendly
SQL requires learning some basic syntax
Data Size
Excel is best for small to medium-sized data
SQL can handle large datasets efficiently
Visualization
Excel includes built-in charts and pivot tables
SQL by itself does not offer visual outputs
Automation
Excel has limited automation capabilities
SQL is highly automatable using scripts
Speed
Excel may slow down with very large data
SQL performs faster with complex queries
Use Cases
Excel is great for reports, dashboards, and calculations
SQL is used for retrieving and processing data from databases
Learning Curve
Excel has a gentle learning curve
SQL has a moderate learning curve but is highly valuable
When to Start with Excel
You should begin with Excel if
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You are completely new to data analysis
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You want to quickly explore and understand datasets
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You are working in business, marketing, or administrative roles
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You need to create reports or dashboards easily
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You prefer visual and hands-on tools to get started
Excel helps you learn the basics of data manipulation and builds confidence to move toward more advanced tools.
When to Start with SQL
You should begin with SQL if
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You plan to work with databases or large data sources
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You want to become a data analyst, data engineer, or data scientist
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You are comfortable with typing logic-based commands
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You are aiming for technical roles in data or software companies
SQL is a core skill in data analytics and is used in almost every company that stores data in a database.
Best Learning Path in the Year Twenty Twenty Five
A recommended order of learning is
Step One - Start with Excel
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Learn sorting, filtering, pivot tables, and basic formulas
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Explore how to clean and visualize data
Step Two - Move to SQL
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Learn how to write basic and intermediate queries
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Practice grouping, filtering, and joining tables
Step Three - Combine Both
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Use SQL to pull the data you need
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Use Excel or tools like Power BI to create reports and dashboards
What Employers Look For
In twenty twenty five, most data analyst job postings expect knowledge of both Excel and SQL. Employers often want you to
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Be able to write queries in SQL
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Create visual reports or dashboards in Excel or other tools
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Understand how to clean and prepare data for analysis
Having skills in both tools makes you more valuable and flexible in the job market.
Final Recommendation
If you are a beginner, start with Excel. It is easier to learn and helps you understand basic data handling. Once you are comfortable, begin learning SQL to unlock more advanced capabilities and handle larger datasets.
Both tools are important. Mastering Excel first will make your transition to SQL smoother and more effective.
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