Snowflake: Run Your First SQL Query

Key insights

• This tutorial video walks you through how to use a Snowflake SQL worksheet; start by setting your role, warehouse, database, schema, and table before running queries.
  Use the Snowflake sample data to follow along quickly and avoid manual setup.
• Run basic commands: use SELECT to retrieve data, add WHERE to filter rows, apply ORDER BY to sort, and use LIMIT to restrict results.
  Keywords are case-insensitive and it helps to end statements with a semicolon while you type.
• Inspect results safely: begin with SELECT * plus LIMIT 10 to preview data, then select specific columns to narrow output.
  Reading the result grid verifies values and helps spot data issues fast.
• Filter and sort examples: use WHERE with patterns like LIKE to match values (e.g., email domains), and use ORDER BY to control row order.
  Combine filters and sorting to get precise, readable query results.
• Test compute trade-offs: try different warehouse sizes (for example XS vs M) to compare speed and cost.
  Run simple benchmark queries to find the best balance between performance and budget.
• Load and manage data: bring data from staged files or use DML commands like INSERT, UPDATE, and DELETE to change rows.
  Snowflake separates storage and compute, supports semi-structured data (JSON), and offers features like time travel for recovery and auditing.

Overview of the Video

Pragmatic Works published a concise YouTube tutorial titled Writing Your First SQL Query in Snowflake, which walks viewers through creating and running basic queries in a Snowflake worksheet. The video uses the platform's sample data to demonstrate common commands and shows how to filter and sort results, making it a practical introduction for beginners. In addition, the presenter benchmarks two warehouse sizes to illustrate how Compute choices affect query speed and cost.

Getting Started: Hands-on Demonstration

The video begins by opening a SQL worksheet and loading the sample dataset so viewers can follow step by step. Viewers see role, warehouse, database, schema, and table settings applied in sequence, which helps clarify how environment context affects query results. Then, the presenter runs a simple SELECT with a LIMIT to inspect rows and shows how to read the results pane, which reinforces basic workflow patterns for new users.

Next, the tutorial narrows results by selecting specific columns and applying a WHERE filter, and it demonstrates sorting with ORDER BY. Throughout this demo, the instructor emphasizes that SQL keywords are case-insensitive and that statements often end with a semicolon, which is useful guidance when typing queries interactively. These practical steps help reduce friction for learners who are unfamiliar with the Snowflake worksheet interface.

Core SQL Concepts Covered

The video focuses on foundational SQL constructs, presenting them clearly and with examples that beginners can replicate. The presenter covers SELECT to retrieve data, WHERE to filter rows, and ORDER BY to sort outputs, while also explaining how to limit record count for faster iteration. Consequently, viewers gain a practical sense of how simple clauses combine to answer common data questions.

In addition, the session touches on data loading and basic DML operations, so learners understand the full lifecycle from staging files to querying tables. The walkthrough avoids deep technical jargon and instead prioritizes readable examples, which helps beginners build confidence before moving on to more advanced features. As a result, the tutorial serves as a gentle bridge from theory to hands-on practice.

Performance Versus Cost: Warehouse Sizing Tradeoffs

A notable portion of the video compares small and medium warehouse sizes to show real-world tradeoffs between speed and expense. The presenter runs the same query on an XS warehouse and then on an M warehouse, demonstrating that larger Compute resources reduce latency but increase cost. Therefore, teams must balance the need for faster results with budget constraints when choosing warehouse sizes.

Moreover, the tutorial highlights that autoscaling and concurrency behaviors can alter cost dynamics, especially for production workloads with variable load. While larger warehouses improve single-query runtime, smaller clusters with concurrency scaling may be more cost-effective in multi-user environments. Thus, understanding workload patterns and monitoring actual usage becomes essential to optimize both performance and spend.

Practical Challenges and Next Steps

While the video makes the basics accessible, it also surfaces common challenges that learners will face when moving to production. For instance, sample data simplifies the experience but rarely reflects the messiness of real datasets, which can include inconsistent types, missing values, and complex semi-structured formats. In addition, permission and role management in Snowflake adds administrative steps that teams must plan for as they onboard more users.

Finally, the presenter offers sensible next steps, urging learners to practice with their own data and to explore performance tuning, query profiling, and Storage-management features. For those who want deeper skills, the logical path includes learning about clustering keys, caching behavior, and cost governance. Overall, the video by Pragmatic Works provides a solid starting point while pointing toward the practical work required to run reliable queries at scale.

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