Data Science & Analytics · PPL

SQL for Data Analysis Certification

A foundational program designed to develop practical SQL skills for querying, filtering, combining, transforming, and analyzing structured data for business insights.

  • 2 DaysDuration
  • PPLAccredited
  • 3 LanguagesArabic · English · Hindi
  • ₹2,999.00 Per delegate

This course is accredited by PPL

This is for all ppl accredited courses
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— The journey

Course Outline

What the programme covers, module by module.

Module 1: Introduction to SQL & Databases

  • SQL fundamentals
  • Relational databases
  • Tables
  • Rows and columns
  • Database schemas
  • SQL applications

Module 2: Retrieving Data with SELECT

  • SELECT statements
  • Selecting columns
  • Retrieving all columns
  • Column aliases
  • DISTINCT values
  • Query structure

Module 3: Filtering Data

  • WHERE clause
  • Comparison operators
  • Logical operators
  • BETWEEN
  • IN
  • Filtering conditions

Module 4: Sorting & Limiting Results

  • ORDER BY
  • Ascending order
  • Descending order
  • Multiple-column sorting
  • LIMIT concepts
  • Result management

Module 5: Working with NULL Values

  • Understanding NULL
  • IS NULL
  • IS NOT NULL
  • Handling missing values
  • COALESCE
  • NULL considerations

Module 6: Aggregate Functions

  • COUNT
  • SUM
  • AVG
  • MIN
  • MAX
  • Analytical summaries

Module 7: Grouping Data

  • GROUP BY
  • HAVING
  • Group-level calculations
  • Multiple grouping columns
  • Conditional aggregation
  • Summary reporting

Module 8: Joining Tables

  • Primary and foreign keys
  • INNER JOIN
  • LEFT JOIN
  • RIGHT JOIN
  • FULL JOIN concepts
  • Multi-table analysis

Module 9: Subqueries

  • Subquery concepts
  • Single-value subqueries
  • Multiple-row subqueries
  • Nested queries
  • Correlated subqueries
  • Analytical applications

Module 10: Common Table Expressions

  • CTE fundamentals
  • WITH clause
  • Multiple CTEs
  • Query organization
  • Reusable query logic
  • Readable analytical queries

Module 11: String Functions

  • Text manipulation
  • Concatenation
  • Case conversion
  • Trimming
  • Substrings
  • Pattern matching

Module 12: Date & Time Analysis

  • Date functions
  • Date extraction
  • Date differences
  • Date filtering
  • Time-based grouping
  • Period comparisons

Module 13: CASE Statements & Data Transformation

  • CASE expressions
  • Conditional logic
  • Data categorization
  • Derived columns
  • Business rules
  • Conditional calculations

Module 14: Window Functions for Analysis

  • Window function concepts
  • OVER clause
  • PARTITION BY
  • ROW_NUMBER
  • RANK
  • Running totals

Module 15: Practical SQL Data Analysis

  • Business question analysis
  • Data extraction
  • Data cleaning
  • Multi-table querying
  • KPI calculations
  • Analytical reporting
— 01.2 · Is it right for you?

Who it's for & what's included

Pick a delivery method to see exactly who it suits and everything you receive.

Who it's for

Classroom

Best for learners who want face-to-face tuition and to network with peers in person.

What's included

Everything you get

  • Live instructor on-site
  • Printed workbook & materials
  • Group exercises & case studies
Who it's for

Online Instructor-Led

Best for learners who want a live instructor and a fixed schedule, without the travel.

What's included

Everything you get

  • Live instructor via video call
  • Digital workbook & resources
  • Session recordings
Who it's for

Self-Paced

Best for self-motivated learners who need maximum flexibility around work and life.

What's included

Everything you get

  • On-demand video lessons
  • Interactive quizzes
  • 24/7 access on any device
— What you will master

Course Objectives

01

Understand relational database concepts and SQL fundamentals.

02

Write SQL queries to retrieve and filter structured data.

03

Sort, group, and aggregate datasets for analytical purposes.

04

Combine multiple tables using appropriate SQL joins.

05

Use subqueries and CTEs to structure analytical queries.

06

Apply string, date, and conditional functions for data transformation.

07

Use window functions to perform advanced analytical calculations.

08

Apply SQL techniques to practical business data analysis scenarios.

— Questions answered

Frequently Asked Questions

What is SQL for Data Analysis?
SQL for Data Analysis involves using Structured Query Language to retrieve, filter, combine, transform, summarize, and analyze information stored in relational databases.
Who should attend this course?
The course is suitable for working professionals, aspiring data analysts, business analysts, BI professionals, reporting professionals, and beginners interested in data analysis.
Do I need previous SQL experience?
No. The program starts with SQL and relational database fundamentals before progressing to joins, subqueries, CTEs, and analytical functions.
Which SQL concepts are covered?
The course covers SELECT, WHERE, sorting, aggregate functions, GROUP BY, joins, subqueries, CTEs, string and date functions, CASE statements, and window functions.
What practical skills will I develop?
You will develop skills in querying databases, filtering and combining datasets, calculating business metrics, transforming data, performing analytical calculations, and creating SQL-based reports.
— Trusted by learners

What our delegates say

★★★★★

"The structure, the practice exams, the instructor — all top tier. Passed first try."

AS
Aarti SharmaSenior Project Manager · TCS
★★★★★

"Best training I have attended. The content is exactly what modern projects need."

JD
James DonovanProgramme Director · Capgemini
★★★★★

"24/7 support actually means 24/7 — got help on my mock exam at 2am. Worth every dollar."

MO
Maya OkaforPMO Lead · Standard Bank

★ 4.8 / 5 from 12,000+ verified learner reviews on Trustpilot & Google.

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