SQL Foundations for Data Analysis
Published by Pearson
Improve your PostgreSQL and SQL skills in just four hours
- Learn the most essential SQL queries and PostgreSQL concepts for data analysis.
- Build real-world projects using SQL to extract, clean, and analyze data.
- Gain practical experience with PostgreSQL, a leading database for analytics.
SQL is one of the most in-demand skills for data professionals and mastering it can open doors to roles in data analytics, business intelligence, and beyond. Whether you're new to SQL or looking to strengthen your data-querying skills, this hands-on course will help you build a solid foundation in SQL using PostgreSQL, a powerful and widely used database system.
No prior SQL experience? No problem! We start with the basics, guiding you through fundamental SQL queries and gradually introducing more advanced techniques like aggregations, joins, and window functions. By the end of this course, you’ll have the confidence to query, manipulate, and analyze data efficiently—skills that are essential for any aspiring data analyst.
This course is perfect for anyone looking to break into data analytics, transition to a data-focused role, or sharpen their SQL skills for day-to-day data work.
What you’ll learn and how you can apply it
- Query, filter, and sort data using SQL.
- Perform JOINs, aggregations, and CASE WHEN statements.
- Use PostgreSQL window functions for ranking and advanced analytics.
- Manipulate and analyze date/time data in PostgreSQL.
This live event is for you because...
- You want to become proficient in SQL and PostgreSQL for data analysis.
- You work with data and want to extract insights efficiently.
- You are transitioning into data analytics and need SQL skills to land a job.
Prerequisites
- No prior SQL experience needed—we start from the basics!
- Familiarity with spreadsheets (Excel or Google Sheets) is a plus.
Course Set-up
- PostgresSQL database download (instructions provided in GitHub)
- GitHub link: https://github.com/kedeisha1/PostgreSQL-for-Data-Analysts
- Sample datasets provided for hands-on exercises
Recommended Preparation
- Watch: Learning SQL by Ben Forta
Recommended Follow-up
- Attend: Smarter SQL for Data Science by James Powell
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Segment 1: SQL Basics & Querying Data (50 min)
- Understanding relational databases and PostgreSQL
- Writing SELECT queries
- Filtering data with WHERE and ORDER BY
- Exercise: Querying a customer dataset
Break (5 mins)
Q&A (5 minutes)
Segment 2: Aggregations & Joins (45 min)
- Calculating metrics with SUM, COUNT, AVG
- Grouping data with GROUP BY & HAVING
- Combining tables with INNER JOIN, LEFT JOIN
- Exercise: Analyzing sales trends with joins
Break (5 mins)
Q&A (5 minutes)
Segment 3: CASE WHEN & Common Table Expressions (CTEs) (45 min)
- Using CASE WHEN for conditional logic
- Categorizing data based on conditions
- Writing Common Table Expressions (CTEs) for better readability
- Exercise: Solve complex problems with CTEs and CASE WHEN
Break (5 mins)
Q&A (5 minutes)
Segment 4: Window Functions (45 min)
- What are window functions, and why are they useful?
- Using ROW_NUMBER, RANK, and DENSE_RANK for ranking data
- Applying LEAD & LAG for sequential analysis
- Exercise: Analyzing customer behavior and ranking top performers with window functions
Break (5 mins)
Q&A (5 minutes)
Course wrap-up and next steps (15 minutes)
- Best practices for SQL query optimization
- Next steps for mastering SQL & PostgreSQL
Your Instructor
Kedeisha Bryan
Kedeisha Bryan is a Data Scientist who helps career changers launch $100k data careers without going back to school. She founded Data in Motion LLC in 2022 and leads a community of over 55,000. Her students have landed roles at Microsoft, Roku, Zendesk, and more.