SQL for Data Science: Turning Raw Data into Business Insights

October
06
2026 (Tuesday)
Time 10:00 AM PDT | 01:00 PM EDT
Duration: 60 Minutes
15 Days Left To REGISTER
Id: 213712
Instructor
Soorya S 
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Live
Recorded
Live + Recorded

Overview

A practical, beginner-friendly session introducing SQL fundamentals for data science and analytics workflows. Attendees will learn how to write essential queries to extract, filter, sort, and aggregate data, and how these skills map directly onto real analyst and data science tasks like reporting, KPI tracking, and dashboarding.

Why you should Attend

If you can't write a SQL query, you're locked out of most data roles today "SQL basics" is now a baseline filter recruiters use before they even look at your resume.

Areas Covered in the Session

  • What SQL is and why it's foundational to data science and analytics
  • SELECT, WHERE, ORDER BY, and filtering data effectively
  • Aggregations: GROUP BY, COUNT, SUM, AVG
  • JOINs: combining data across multiple tables
  • Writing subqueries and CTEs for cleaner analysis
  • Common beginner mistakes and how to avoid them
  • How SQL fits into the broader data stack (Excel, Python, BI tools)
  • Live query walkthrough on a real-world dataset

Who Will Benefit

  • Data Analysts
  • Business Analysts
  • Quality Analysts
  • Reporting Analysts
  • Aspiring Data Scientists
  • BI Professionals
  • Excel Power users upskilling
  • Students/Career-Switchers into data roles
  • Operations & Compliance Analysts
  • Product/Marketing Analysts

Speaker Profile

Soorya is a Data Analyst with hands-on experience in compliance case management, KPI monitoring, product disposition decisions, and cross-functional stakeholder coordination, working extensively with SQL, Excel, and BI dashboards. Currently deepening this expertise through a structured data science and machine learning program, Soorya brings a practitioner's lens to teaching - breaking down technical concepts using real workplace data problems, making sessions practical and immediately applicable rather than purely theoretical.
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