Name: 100 Cost Optimization Techniques in Snowflake
Rating: 4.4 (134 reviews)

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Creado porCristian Scutaru

Última actualización: 5/2026

Inglés

Lo que aprenderás

Create and run cost-effective queries
Consolidate underutilized warehouses
Monitor and improve query performance
How using a bigger warehouse could cost you less
Watch over longest running and frequently executed queries
Serverless features in detail: cost and how they work
Avoid cost traps by setting different parameter values
How to combine different Snowflake editions
Save on costs with parallel data transfer and processing
Design and architect applications with cost impact in mind

Contenido del curso

13 secciones • 121 clases • 14 h 13 m de duración total

Course Structure and Content7:29
Best Ways to Benefit from this Course3:11
SnowPro Snowflake Certifications: Added Material!3:06
Create a Free Trial Snowflake Account3:54
Free Hands-On Project Setup8:27

Introduction to Virtual Warehouses1:39
Tip #1: Larger Virtual Warehouses May Actually Cost You Less12:50
Tip #2: Auto-Suspend Any Warehouse After One Minute8:16
Tip #3: Any Resumed Warehouse Will Cost You at Least One Minute8:48
Tip #4: Never Auto-Suspend Any Warehouse After Less Than One Minute2:12
Tip #5: X-Small Warehouses Could Be Powerful Enough3:27
Tip #6: Resized Warehouses are for More Complex Queries3:13
Tip #7: Multi-Cluster Warehouses are for Multiple Users and Concurrency3:54
Tip #8: Multi-Cluster Warehouses Should Always Have Min Clusters 11:54
Tip #9: Use Economy Scaling Policy To Save Money17:43
Tip #10: When to Use Snowpark-Optimized Warehouses3:10
Test Your Knowledge

Introduction to Compute Workloads2:34
Tip #11: Use Resource Monitors17:27
Tip #12: Use Account-Level Budgets10:45
Tip #13: Prevent Never-Ending Queries6:46
Tip #14: Manually Kill Running Queries5:45
Tip #15: Reduce Warehouse Sizes3:44
Tip #16: Consolidate All Warehouses20:08
Tip #17: Use Parallel Jobs for Batch Transformations9:58
Tip #18: Avoid Checking Too Much on Metadata12:33
Tip #19: Charts for Warehouse Monitoring9:48
Tip #20: Revisit the Main Traps with Warehouses16:02
Test Your Knowledge

Introduction to Snowflake Accounts1:48
Tip #21: What to Choose for a Free Trial Account6:40
Tip #22: When to Use a Free Trial Account5:42
Tip #23: Understand Price Tables for Virtual Warehouse Compute Services9:05
Tip #24: Understand Price Tables for Cloud and Serverless Services7:20
Tip #25: Understand Price Tables for Storage and Data Transfer5:46
Tip #26: Use the Account Overview Interface in Snowsight6:06
Tip #27: Use Organization Accounts6:30
Tip #28: Limit Warehouse Changes with Access Control7:12
Tip #29: Adjust Default Values of Account-Level Parameters5:18
Tip #30: Careful with Reader Accounts4:52
Test Your Knowledge

Introduction to Snowflake Editions1:24
Tip #31: When to Choose Enterprise over Standard Edition10:21
Tip #32: How to Avoid Multi-Cluster Warehouses10:07
Tip #33: When to Use Incremental Materializations3:59
Tip #34: How to Emulate Materialized Views7:20
Tip #35: The Case for Extended Time Travel15:59
Tip #36: Use Standard Edition Account for Analytics6:13
Tip #37: Use Separate Standard Edition Account for Common Queries2:36
Tip #38: How to Reduce Costs to Zero for an Inactive Paid Account7:19
Tip #39: When to Choose the Business Critical Edition3:48
Tip #40: When to Choose the Virtual Private Snowflake (VPS) Edition3:22
Test Your Knowledge

Introduction to Query Monitoring2:03
Tip #41: Monitor Longest Running Queries11:35
Tip #42: Interpret Query History10:05
Tip #43: More Charts for Query Monitoring6:08
Tip #44: Use Query Tags9:19
Tip #45: Reduce Frequency of Simple Queries4:34
Tip #46: Reduce Frequency of Metadata Queries5:20
Tip #47: Reduce Frequency of SHOW Commands10:13
Tip #48: Clone Less Frequently3:15
Tip #49: Change Query Schedules10:55
Tip #50: Parallel over Sequential Transfer and Processing11:01
Test Your Knowledge

Introduction to Query Optimization2:39
Tip #51: Use the Query Profile13:35
Tip #52: Use the Explain Statement9:57
Tip #53: Use Data Caching11:18
Tip #54: Queries on Data Lakes9:00
Tip #55: Use Vectorized Python UDFs6:25
Tip #56: Use Batch Commands to Prevent Transaction Locks4:43
Tip #57: Reduce Query Complexity and Compilation Time8:01
Tip #58: Check for Cross Joins and Exploding Joins9:16
Tip #59: Process Only New or Updated Data4:14
Tip #60: Remote Spillage Optimization14:13
Test Your Knowledge

Introduction to Serverless Features1:56
Tip #61: Monitor the Cost of Automated Jobs13:52
Tip #62: Estimate Cost of Scheduled Tasks11:24
Tip #63: When to Use Serverless Tasks10:29
Tip #64: Replace Snowpipe with Snowpipe Streaming3:02
Tip #65: Estimate Cost of Automatic Clustering on Tables5:46
Tip #66: Estimate Cost of the Query Acceleration Service (QAS)12:56
Tip #67: Estimate Cost of the Search Optimization Service (SOS)8:59
Tip #68: Reduce Materialized Views Maintenance Cost6:06
Tip #69: Reduce Database Replication Cost8:56
Tip #70: Estimate Cost of Hybrid Tables10:58
Test Your Knowledge

Introduction to Data Storage1:56
Tip #71: Use On-Demand Storage When You Don’t Know Your Spending Pattern6:42
Tip #72: Copy and Keep Less Data8:15
Tip #73: Lower Data Retention with No Time Travel2:36
Tip #74: Estimate Storage Cost of the Fail-Safe3:56
Tip #75: Use Transient or Temporary Tables9:05
Tip #76: Use Zero-Copy Cloning7:46
Tip #77: Clone Less Data1:28
Tip #78: Ensure Tables Are Clustered Correctly17:47
Tip #79: Drop Unused Tables and Other Objects18:19
Tip #80: Remove Old Files from Stage Areas5:16
Test Your Knowledge

Introduction to Data Transfer1:43
Tip #81: Data In is Free, Data Out is Expensive19:27
Tip #82: Choose the same Provider and Region Where Your Data Is5:20
Tip #83: External Access Integrations vs External Functions5:08
Tip #84: Use Data Compression3:33
Tip #85: Use Batch Transfer with Path Partitioning1:40
Tip #86: Use Bulk Loads instead of Single-Row Inserts5:56
Tip #87: Use Parallel Data Uploading3:00
Tip #88: Design Cost-Effective Data Pipelines1:49
Tip #89: Use External Tables in a Data Lake5:00
Tip #90: Query Parquet Files instead of CSV3:09
Test Your Knowledge

Requisitos

Basic knowledge of the Snowflake Data Cloud
Basic knowledge of SQL
Optional knowledge of some basic programming in Python

Descripción

What You Will Learn About Spending

How to use even bigger virtual warehouses for less expensive queries.
How to avoid huge cost traps in Snowflake by changing different parameter values.
How to optimize queries, compute, storage and overall costs in Snowflake.
How to properly consolidate underutilized warehouses.
How each serverless feature in Snowflake works and how to estimate their cost.
How to use parallel data transfer and processing everywhere you can.
How to combine different Snowflake editions in your organization.
How to use better data visualizations to estimate spending.
How to reduce your spending on all your Snowflake accounts.
I also offer over 300 high-quality presentation slides with the summary on each tip or technique!

Where You May Use This Knowledge

Drastically reduce costs on your own Snowflake accounts.
Create more Snowflake accounts - with different editions - and use them efficiently.
Help your clients reduce spending on their Snowflake accounts.
Help your employer reduce costs on Snowflake in your own organization.
Learn to recognize the traps most people fall into when using Snowflake.
Create not just highly performant, but also cost-effective SQL queries.
Learn how to get cheaper queries with huge warehouses, using hundreds of nodes.
I also offer an open-source GitHub repository with dozens of hands-on exercises and experiments!

What You Will Learn About Snowflake

Learn all about the virtual warehouses.
Learn how to monitor and optimize queries.
Learn about resource monitors and budgets.
Learn query acceleration and search optimization
Estimate efficient automatic clustering and maintenance of materialized views.
Learn all that matters about time travel and zero-copy cloning.
Learn how to efficiently deploy and combine Snowflake with other applications.
I have many brief but focused hands-on presentations of different Snowflake features!

Who I Am

The only world-class expert from Canada selected for the Snowflake Data Superhero program in 2021.
SnowPro Certification SME (Subject Matter Expert) - many SnowPro exam questions have been created by me.
Passed four SnowPro certification exams to date (with no retakes): Core, Architect, Data Engineer, Data Analyst.
Specialized in Snowflake for the past few years: I worked for Snowflake Partner companies, I served dozens of clients in this capacity or as an independent consultant, today I share my knowledge with highly specialize courses on Snowflake.

This is truly "the" Bible on Snowflake spending!

No other course, book or documentation around will offer as much insights, hands-on experiments and knowledge transfer on optimizing the cost on Snowflake as my course here, guaranteed!

Enroll today, and keep this course forever!

[Disclaimer: We are not affiliated with or endorsed by Snowflake, Inc.]

¿Para quién es este curso?

Snowflake account owners who want to reduce their spending
Snowflake consultants who want to advise their clients on Snowflake spending
Anyone using Snowflake in their organization who wants to control their costs
Managers looking to cut their Snowflake spending by half
Technical persons who want to learn about all ways to cut spending on this data warehouse
Data Engineers and Architects looking to create cost-effective apps around Snowflake
Data Scientists who want to avoid spending traps when using Snowflake for Data Science apps

Lo que aprenderás

Ver temas relacionados

Contenido del curso

Introduction5 clases • 26 min

Virtual Warehouses11 clases • 1 h 7 min

Compute Workloads11 clases • 1 h 56 min

Snowflake Accounts11 clases • 1 h 6 min

Snowflake Editions11 clases • 1 h 12 min

Query Monitoring11 clases • 1 h 24 min

Query Optimization11 clases • 1 h 33 min

Serverless Features11 clases • 1 h 34 min

Data Storage11 clases • 1 h 23 min

Data Transfer11 clases • 56 min

Requisitos

Descripción

¿Para quién es este curso?