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Description of  100 Snowflake Cost Optimization Techniques

Published 3/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.68 GB | Duration: 13h 46m by World-Class Snowflake Expert, former Data Superhero and SnowPro Certification SME 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 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 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 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 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 w