HARTMANN software group

Snowflake SQL for Data Analysis and Reporting Training in Nashville

Enroll in or hire us to teach our Snowflake SQL for Data Analysis and Reporting class in Nashville, Tennessee by calling us @303.377.6176. Like all HSG classes, Snowflake SQL for Data Analysis and Reporting may be offered either onsite or via instructor led virtual training. Consider looking at our public training schedule to see if it is scheduled: Public Training Classes
Provided there are enough attendees, Snowflake SQL for Data Analysis and Reporting may be taught at one of our local training facilities.
We offer private customized training for groups of 3 or more attendees.
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Course Description

  
This hands-on workshop teaches students how to write, troubleshoot, and optimize SQL queries in Snowflake for reporting, analytics, and data validation.

Participants will learn core SQL fundamentals, master joins and aggregations, work with dates and strings, build reusable queries using CTEs, analyze data with window functions, and leverage Snowflake-specific capabilities such as QUALIFY.

Special emphasis is placed on:

  • Avoiding duplicate rows caused by joins

  • Preventing incorrect aggregations

  • Understanding fan-out problems

  • Writing maintainable production SQL

  • Building analytical queries used in real-world reporting environments

This hands-on workshop teaches students how to write, troubleshoot, and optimize SQL queries in Snowflake for reporting, analytics, and data validation.

Participants will learn core SQL fundamentals, master joins and aggregations, work with dates and strings, build reusable queries using CTEs, analyze data with window functions, and leverage Snowflake-specific capabilities such as QUALIFY.

Special emphasis is placed on:

  • Avoiding duplicate rows caused by joins

  • Preventing incorrect aggregations

  • Understanding fan-out problems

  • Writing maintainable production SQL

  • Building analytical queries used in real-world reporting environments

Course Length: 1.5 Days
Course Tuition: $990 (US)

Prerequisites
Basic understanding of SQL

Course Outline

  

Module 1: SQL Foundations

Basic Query Structure

Filtering Data

Aggregations

DISTINCT vs COUNT(DISTINCT)

Aliasing

 

Hands-On Labs

Lab 1:

Query customer data

Filter records

Sort results

 

Lab 2:

Aggregate sales data

Compare COUNT(*) vs COUNT(DISTINCT)

 

Module 2: Joins and Avoiding Fan-Out

INNER JOIN

LEFT JOIN

RIGHT JOIN

FULL OUTER JOIN

Multi-Condition Joins

The Fan-Out Problem (Critical Topic)

 

Hands-On Labs

Lab 3:

Build each join type

Lab 4:

Intentionally create fan-out

Diagnose incorrect totals

Repair query

Module 3: Data Types and Casting

Common Data Types

CAST

CAST(value AS NUMBER)

Snowflake Shorthand - value::NUMBER

Date Conversions

Time Zones

 

Hands-On Labs

Lab 5:

Convert strings to dates

Convert timestamps

Adjust time zones

Module 4: String and Date Functions

String Functions

Pattern Matching

Date Functions

Business Use Cases

 

Hands-On Labs

Lab 6:

Build reporting periods

Parse and clean text values

Module 5: Conditional Logic

CASE

Snowflake IFF

NULL Handling

COALESCE()

NULLIF()

NVL()

 

Hands-On Labs

Lab 7:

Categorize customers

Replace NULL values

Build reporting flags

 

Module 6: CTEs, Subqueries, and Window Functions

Common Table Expressions

Nested CTEs

Subqueries

Window Functions

Understanding Windows

Ranking Functions

Comparison Functions

Value Functions

PARTITION BY vs ORDER BY

DISTINCT vs Window-Based Deduplication

 

Hands-On Labs

Lab 8:

Top-N reports

Latest record selection

Period-over-period comparisons

 

Module 7: Snowflake QUALIFY

Traditional approach

Snowflake approach

 

Hands-On Labs

Lab 9:

Deduplicate customer records

Select latest transaction

 

Module 8: Query Performance and Best Practices

Why Duplicates Happen

Filter Early

Avoid SELECT *

ORDER BY Costs

Partition Pruning

 

Hands-On Labs

Lab 10:

Compare efficient and inefficient queries

Observe scan reductions

 

Module 9: Good SQL Habits

Formatting Standards

Meaningful Aliases

Effective Comments

Validation Techniques

Capstone Lab (Final Exercise)

Students build an executive sales report that includes:

Multiple joins

Date filtering

Aggregations

Window functions

QUALIFY

Ranking

Deduplication

Performance review

Students must identify and correct an intentional fan-out issue before producing final metrics.

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