SQL for Data Analysis

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Duration 2 days – 14 hrs

 

Overview

 

This course equips participants with essential SQL (Structured Query Language) skills to query, clean, and manipulate data directly from relational databases. Designed for professionals working with data, the training emphasizes practical, hands-on exercises that demonstrate how SQL is used in real-world analytics scenarios. Participants will learn how to extract insights from large datasets—an essential skill for analysts, business users, and data professionals.

 

Objectives

 

  • Understand SQL fundamentals and database concepts
  • Write queries to select, filter, and sort data from multiple tables
  • Clean and transform raw data using SQL functions
  • Perform aggregations, grouping, and subqueries
  • Join tables effectively for analysis
  • Apply SQL techniques to solve common business data questions

 

Audience

  • Aspiring data analysts and business analysts
  • Professionals in marketing, finance, operations, and HR
  • Excel users transitioning to database querying
  • Anyone responsible for working with data stored in relational databases

 

Pre- requisites 

  • Basic computer literacy
  • No prior SQL experience required
  • Familiarity with data concepts (e.g., tables, rows, columns) is helpful

Course Content

 

Day 1: SQL Essentials and Data Extraction

 

Introduction to Databases and SQL

 

  • What is a relational database?
  • Key components: tables, rows, columns, keys
  • SQL syntax and query structure

 

Writing Basic Queries

 

  • SELECT, FROM, WHERE clauses
  • Filtering data with conditions
  • Sorting data with ORDER BY

 

Working with Data Types and Operators

 

  • Numeric, text, and date/time types
  • Logical and comparison operators

 

Aggregate Functions and Grouping

 

  • Using COUNT, SUM, AVG, MIN, MAX
  • Grouping data with GROUP BY
  • Filtering groups with HAVING

 

Hands-On Lab:

Querying a sample business database

 

Day 2: Data Manipulation, Joins, and Advanced Queries

 

Joining Tables for Analysis

 

  • INNER JOIN, LEFT JOIN, RIGHT JOIN
  • Combining data across tables

 

Data Cleaning and Transformation with SQL

 

  • Using CASE, NULL handling
  • Data formatting and conversion
  • String and date functions

 

Subqueries and Nested Queries

 

  • Writing subqueries in SELECT, WHERE, and FROM
  • Common subquery patterns in analytics

 

Using SQL for Business Use Cases

 

  • Cohort analysis, customer segmentation
  • Trend analysis using date functions

 

Capstone Project:

 

  • Solve a business case using SQL queries
  • Present a mini-report using query results

 

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