Introduction
In this course, SQL for marketers, we’ll start from the basics – installing SQL onto your Mac, Linux, or Windows machine and explaining what a relational database is. Next, we’ll look at basic tasks like creating tables and loading data into those tables. We will look at a wide variety of SQL commands and I will show you how to speed things up using indexes.
By end of this course you will learn about Advanced SQL queries on Spark, the big data framework that is the successor to MapReduce and also runs on top of Hadoop.
Course Objective
Participant will learn to:
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Know how to answer all of their marketing-related questions using a SQL query
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Understand what a relational database is
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How to install SQL on Mac, Linux, or Windows
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How to create a table
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How to import data into a table
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How to query a table
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How to insert into, update, and delete from a table
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Speed things up using indexes
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Join tables together to merge data
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Aggregate data using count, sum, and average
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Determine where in the sales funnel customers are being lost
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Chart your year over year revenue
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Group and sort sales by location
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Use SQL on Spark
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Install Spark
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Create a Spark cluster on AWS EC2
Target Audience
This course is intended for professionals who want to learn SQL from a practical, marketing and business analytics perspective, including:
- Marketing Analysts and Digital Marketing Professionals
- Product Managers and Growth Managers
- Business Analysts and Data Analysts
- Sales Analysts and Revenue Optimization Teams
- Professionals making data-driven marketing decisions
- Beginners in SQL who want real-world business applications
- Anyone interested in analyzing customer behavior, funnels, and revenue data
- Professionals looking to expand into Big Data and Spark SQL
Course Outline
Day 1: SQL Fundamentals & Database Basics
Introduction to SQL
What is a Relational Database
Installing SQL (Mac, Linux, Windows)
Overview of SQL Databases
Creating Tables
Loading Data into Tables
Basic SQL Commands
Querying Data (SELECT Basics)
Day 2: Data Manipulation (CRUD Operations)
Creating Tables in Detail
Modifying Table Structure
Insert, Update & Delete Operations
Understanding CRUD Concepts
Importing Data into Tables
Working with Tab-Separated Data
Basic Filtering with IN & BETWEEN
Day 3: Joins & Data Relationships
Understanding Data Relationships
Joining Tables
Inner Joins
Merging Multiple Data Sources
Join Use Cases in Marketing Data
Querying Combined Datasets
Day 4: Aggregation, Analytics & Marketing Insights
COUNT, DISTINCT, SUM
MIN, MAX, AVG Functions
GROUP BY Queries
Sorting and Limiting Results
Marketing Analytics Use Cases
Sales by Location
Funnels Analysis (Customer Drop-off)
Year-over-Year Revenue Analysis
Day 5: Performance, Indexing & Spark SQL
Understanding Indexes
Speed Optimization with Indexes
Index Performance Comparison
Advanced Query Optimization
Introduction to Spark SQL
Installing Spark
Creating a Spark Cluster on AWS EC2
Running SQL on Big Data (Spark)
Final Practice Exercises
