100 Snowflake Cost Optimization Techniques

What you'll learn
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
Requirements
Basic knowledge of the Snowflake Data Cloud
Basic knowledge of SQL
Optional knowledge of some basic programming in Python
Description
What You Will Learn About SpendingHow 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 KnowledgeDrastically 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 SnowflakeLearn all about the virtual warehouses.Learn how to monitor and optimize queries.Learn about resource monitors and budgets.Learn query acceleration and search optimizationEstimate 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 AmThe 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!
Overview
Section 1: Introduction
Lecture 1 Course Structure and Content
Lecture 2 Best Ways to Benefit from this Course
Lecture 3 Create a Free Trial Snowflake Account
Lecture 4 Free Hands-On Project Setup
Section 2: Virtual Warehouses
Lecture 5 Introduction to Virtual Warehouses
Lecture 6 Tip #1: Larger Virtual Warehouses May Actually Cost You Less
Lecture 7 Tip #2: Auto-Suspend Any Warehouse After One Minute
Lecture 8 Tip #3: Any Resumed Warehouse Will Cost You at Least One Minute
Lecture 9 Tip #4: Never Auto-Suspend Any Warehouse After Less Than One Minute
Lecture 10 Tip #5: X-Small Warehouses Could Be Powerful Enough
Lecture 11 Tip #6: Resized Warehouses are for More Complex Queries
Lecture 12 Tip #7: Multi-Cluster Warehouses are for Multiple Users and Concurrency
Lecture 13 Tip #8: Multi-Cluster Warehouses Should Always Have Min Clusters 1
Lecture 14 Tip #9: Use Economy Scaling Policy To Save Money
Lecture 15 Tip #10: When to Use Snowpark-Optimized Warehouses
Section 3: Compute Workloads
Lecture 16 Introduction to Compute Workloads
Lecture 17 Tip #11: Use Resource Monitors
Lecture 18 Tip #12: Use Account-Level Budgets
Lecture 19 Tip #13: Prevent Never-Ending Queries
Lecture 20 Tip #14: Manually Kill Running Queries
Lecture 21 Tip #15: Reduce Warehouse Sizes
Lecture 22 Tip #16: Consolidate All Warehouses
Lecture 23 Tip #17: Use Parallel Jobs for Batch Transformations
Lecture 24 Tip #18: Avoid Checking Too Much on Metadata
Lecture 25 Tip #19: Charts for Warehouse Monitoring
Lecture 26 Tip #20: Revisit the Main Traps with Warehouses
Section 4: Snowflake Accounts
Lecture 27 Introduction to Snowflake Accounts
Lecture 28 Tip #21: What to Choose for a Free Trial Account
Lecture 29 Tip #22: When to Use a Free Trial Account
Lecture 30 Tip #23: Understand Price Tables for Virtual Warehouse Compute Services
Lecture 31 Tip #24: Understand Price Tables for Cloud and Serverless Services
Lecture 32 Tip #25: Understand Price Tables for Storage and Data Transfer
Lecture 33 Tip #26: Use the Account Overview Interface in Snowsight
Lecture 34 Tip #27: Use Organization Accounts
Lecture 35 Tip #28: Limit Warehouse Changes with Access Control
Lecture 36 Tip #29: Adjust Default Values of Account-Level Parameters
Lecture 37 Tip #30: Careful with Reader Accounts
Section 5: Snowflake Editions
Lecture 38 Introduction to Snowflake Editions
Lecture 39 Tip #31: When to Choose Enterprise over Standard Edition
Lecture 40 Tip #32: How to Avoid Multi-Cluster Warehouses
Lecture 41 Tip #33: When to Use Incremental Materializations
Lecture 42 Tip #34: How to Emulate Materialized Views
Lecture 43 Tip #35: The Case for Extended Time Travel
Lecture 44 Tip #36: Use Standard Edition Account for Analytics
Lecture 45 Tip #37: Use Separate Standard Edition Account for Common Queries
Lecture 46 Tip #38: How to Reduce Costs to Zero for an Inactive Paid Account
Lecture 47 Tip #39: When to Choose the Business Critical Edition
Lecture 48 Tip #40: When to Choose the Virtual Private Snowflake (VPS) Edition
Section 6: Query Monitoring
Lecture 49 Introduction to Query Monitoring
Lecture 50 Tip #41: Monitor Longest Running Queries
Lecture 51 Tip #42: Interpret Query History
Lecture 52 Tip #43: More Charts for Query Monitoring
Lecture 53 Tip #44: Use Query Tags
Lecture 54 Tip #45: Reduce Frequency of Simple Queries
Lecture 55 Tip #46: Reduce Frequency of Metadata Queries
Lecture 56 Tip #47: Reduce Frequency of SHOW Commands
Lecture 57 Tip #48: Clone Less Frequently
Lecture 58 Tip #49: Change Query Schedules
Lecture 59 Tip #50: Parallel over Sequential Transfer and Processing
Section 7: Query Optimization
Lecture 60 Introduction to Query Optimization
Lecture 61 Tip #51: Use the Query Profile
Lecture 62 Tip #52: Use the Explain Statement
Lecture 63 Tip #53: Use Data Caching
Lecture 64 Tip #54: Queries on Data Lakes
Lecture 65 Tip #55: Use Vectorized Python UDFs
Lecture 66 Tip #56: Use Batch Commands to Prevent Transaction Locks
Lecture 67 Tip #57: Reduce Query Complexity and Compilation Time
Lecture 68 Tip #58: Check for Cross Joins and Exploding Joins
Lecture 69 Tip #59: Process Only New or Updated Data
Lecture 70 Tip #60: Remote Spillage Optimization
Section 8: Serverless Features
Lecture 71 Introduction to Serverless Features
Lecture 72 Tip #61: Monitor the Cost of Automated Jobs
Lecture 73 Tip #62: Estimate Cost of Scheduled Tasks
Lecture 74 Tip #63: When to Use Serverless Tasks
Lecture 75 Tip #64: Replace Snowpipe with Snowpipe Streaming
Lecture 76 Tip #65: Estimate Cost of Automatic Clustering on Tables
Lecture 77 Tip #66: Estimate Cost of the Query Acceleration Service (QAS)
Lecture 78 Tip #67: Estimate Cost of the Search Optimization Service (SOS)
Lecture 79 Tip #68: Reduce Materialized Views Maintenance Cost
Lecture 80 Tip #69: Reduce Database Replication Cost
Lecture 81 Tip #70: Estimate Cost of Hybrid Tables
Section 9: Data Storage
Lecture 82 Introduction to Data Storage
Lecture 83 Tip #71: Use On-Demand Storage When You Don't Know Your Spending Pattern
Lecture 84 Tip #72: Copy and Keep Less Data
Lecture 85 Tip #73: Lower Data Retention with No Time Travel
Lecture 86 Tip #74: Estimate Storage Cost of the Fail-Safe
Lecture 87 Tip #75: Use Transient or Temporary Tables
Lecture 88 Tip #76: Use Zero-Copy Cloning
Lecture 89 Tip #77: Clone Less Data
Lecture 90 Tip #78: Ensure Tables Are Clustered Correctly
Lecture 91 Tip #79: Drop Unused Tables and Other Objects
Lecture 92 Tip #80: Remove Old Files from Stage Areas
Section 10: Data Transfer
Lecture 93 Introduction to Data Transfer
Lecture 94 Tip #81: Data In is Free, Data Out is Expensive
Lecture 95 Tip #82: Choose the same Provider and Region Where Your Data Is
Lecture 96 Tip #83: External Access Integrations vs External Functions
Lecture 97 Tip #84: Use Data Compression
Lecture 98 Tip #85: Use Batch Transfer with Path Partitioning
Lecture 99 Tip #86: Use Bulk Loads instead of Single-Row Inserts
Lecture 100 Tip #87: Use Parallel Data Uploading
Lecture 101 Tip #88: Design Cost-Effective Data Pipelines
Lecture 102 Tip #89: Use External Tables in a Data Lake
Lecture 103 Tip #90: Query Parquet Files instead of CSV
Section 11: Snowflake Apps
Lecture 104 Introduction to Snowflake Apps
Lecture 105 Tip #91: Estimate Cost Impact of Data Sharing in Snowflake
Lecture 106 Tip #92: Estimate Cost Impact of Client and Server (Snowpark) Applications
Lecture 107 Tip #93: Estimate Cost Impact of Streamlit in Snowflake and Native Applications
Lecture 108 Tip #94: Estimate Cost Impact of Data Science Applications
Lecture 109 Tip #95: Check All Connected Applications
Lecture 110 Tip #96: Third-Party Apps Saving Money Will Spend Money
Lecture 111 Tip #97: Free Marketplace Native Apps Will Cost Money
Lecture 112 Tip #98: Keep App Versions Updated
Lecture 113 Tip #99: Cache Data in Third-Party Tools
Lecture 114 Tip #100: Auto-Abort Running Queries from Disconnected Apps
Section 12: Wrapping Up
Lecture 115 Congratulations, You Made It!
Lecture 116 Bonus Lecture
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

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