100 Snowflake Cost Optimization Techniques
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!
Virtual Warehouses
Compute Workloads
-
5
Introduction to Virtual Warehouses -
6
Tip #1: Larger Virtual Warehouses May Actually Cost You Less
-
7
Tip #2: Auto-Suspend Any Warehouse After One Minute
-
8
Tip #3: Any Resumed Warehouse Will Cost You at Least One Minute
-
9
Tip #4: Never Auto-Suspend Any Warehouse After Less Than One Minute
-
10
Tip #5: X-Small Warehouses Could Be Powerful Enough
-
11
Tip #6: Resized Warehouses are for More Complex Queries
-
12
Tip #7: Multi-Cluster Warehouses are for Multiple Users and Concurrency
-
13
Tip #8: Multi-Cluster Warehouses Should Always Have Min Clusters 1
-
14
Tip #9: Use Economy Scaling Policy To Save Money
-
15
Tip #10: When to Use Snowpark-Optimized Warehouses
-
16
Test Your Knowledge
Snowflake Accounts
-
17
Introduction to Compute Workloads
-
18
Tip #11: Use Resource Monitors
-
19
Tip #12: Use Account-Level Budgets
-
20
Tip #13: Prevent Never-Ending Queries
-
21
Tip #14: Manually Kill Running Queries
-
22
Tip #15: Reduce Warehouse Sizes
-
23
Tip #16: Consolidate All Warehouses
-
24
Tip #17: Use Parallel Jobs for Batch Transformations
-
25
Tip #18: Avoid Checking Too Much on Metadata
-
26
Tip #19: Charts for Warehouse Monitoring
-
27
Tip #20: Revisit the Main Traps with Warehouses
-
28
Test Your Knowledge
Snowflake Editions
-
29
Introduction to Snowflake Accounts
-
30
Tip #21: What to Choose for a Free Trial Account
-
31
Tip #22: When to Use a Free Trial Account
-
32
Tip #23: Understand Price Tables for Virtual Warehouse Compute Services
-
33
Tip #24: Understand Price Tables for Cloud and Serverless Services
-
34
Tip #25: Understand Price Tables for Storage and Data Transfer
-
35
Tip #26: Use the Account Overview Interface in Snowsight
-
36
Tip #27: Use Organization Accounts
-
37
Tip #28: Limit Warehouse Changes with Access Control
-
38
Tip #29: Adjust Default Values of Account-Level Parameters
-
39
Tip #30: Careful with Reader Accounts
-
40
Test Your Knowledge
Query Monitoring
-
41
Introduction to Snowflake Editions
-
42
Tip #31: When to Choose Enterprise over Standard Edition
-
43
Tip #32: How to Avoid Multi-Cluster Warehouses
-
44
Tip #33: When to Use Incremental Materializations
-
45
Tip #34: How to Emulate Materialized Views
-
46
Tip #35: The Case for Extended Time Travel
-
47
Tip #36: Use Standard Edition Account for Analytics
-
48
Tip #37: Use Separate Standard Edition Account for Common Queries
-
49
Tip #38: How to Reduce Costs to Zero for an Inactive Paid Account
-
50
Tip #39: When to Choose the Business Critical Edition
-
51
Tip #40: When to Choose the Virtual Private Snowflake (VPS) Edition
-
52
Test Your Knowledge
Query Optimization
-
53
Introduction to Query Monitoring
-
54
Tip #41: Monitor Longest Running Queries
-
55
Tip #42: Interpret Query History
-
56
Tip #43: More Charts for Query Monitoring
-
57
Tip #44: Use Query Tags
-
58
Tip #45: Reduce Frequency of Simple Queries
-
59
Tip #46: Reduce Frequency of Metadata Queries
-
60
Tip #47: Reduce Frequency of SHOW Commands
-
61
Tip #48: Clone Less Frequently
-
62
Tip #49: Change Query Schedules
-
63
Tip #50: Parallel over Sequential Transfer and Processing
-
64
Test Your Knowledge
Serverless Features
-
65
Introduction to Query Optimization
-
66
Tip #51: Use the Query Profile
-
67
Tip #52: Use the Explain Statement
-
68
Tip #53: Use Data Caching
-
69
Tip #54: Queries on Data Lakes
-
70
Tip #55: Use Vectorized Python UDFs
-
71
Tip #56: Use Batch Commands to Prevent Transaction Locks
-
72
Tip #57: Reduce Query Complexity and Compilation Time
-
73
Tip #58: Check for Cross Joins and Exploding Joins
-
74
Tip #59: Process Only New or Updated Data
-
75
Tip #60: Remote Spillage Optimization
-
76
Test Your Knowledge
Data Storage
-
77
Introduction to Serverless Features
-
78
Tip #61: Monitor the Cost of Automated Jobs
-
79
Tip #62: Estimate Cost of Scheduled Tasks
-
80
Tip #63: When to Use Serverless Tasks
-
81
Tip #64: Replace Snowpipe with Snowpipe Streaming
-
82
Tip #65: Estimate Cost of Automatic Clustering on Tables
-
83
Tip #66: Estimate Cost of the Query Acceleration Service (QAS)
-
84
Tip #67: Estimate Cost of the Search Optimization Service (SOS)
-
85
Tip #68: Reduce Materialized Views Maintenance Cost
-
86
Tip #69: Reduce Database Replication Cost
-
87
Tip #70: Estimate Cost of Hybrid Tables
-
88
Test Your Knowledge
