Snowflake Database – Tips, Techniques and Cool Stuff

Snowflake Database – Tips, Techniques and Cool Stuff, available at $54.99, has an average rating of 4.8, with 52 lectures, based on 151 reviews, and has 1260 subscribers.

You will learn about Web UI tips and techniques Working with query and results history Dozens of SQL tips and techniques Many cool features and functions of Snowflake Techniques for analyzing data Tips for monitoring warehouse usage This course is ideal for individuals who are Anyone who is in the role of Snowflake data engineer, data warehouse developer or data architect It is particularly useful for Anyone who is in the role of Snowflake data engineer, data warehouse developer or data architect.

Enroll now: Snowflake Database – Tips, Techniques and Cool Stuff

Summary

Title: Snowflake Database – Tips, Techniques and Cool Stuff

Price: $54.99

Average Rating: 4.8

Number of Lectures: 52

Number of Published Lectures: 52

Number of Curriculum Items: 52

Number of Published Curriculum Objects: 52

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

Web UI tips and techniques
Working with query and results history
Dozens of SQL tips and techniques
Many cool features and functions of Snowflake
Techniques for analyzing data
Tips for monitoring warehouse usage

Who Should Attend

Anyone who is in the role of Snowflake data engineer, data warehouse developer or data architect

Target Audiences

Anyone who is in the role of Snowflake data engineer, data warehouse developer or data architect

Snowflake was founded in 2012 and released in late 2014. The company was founded by Benoit Dageville, Thierry Cruanes and Marcin Żukowski, who, between them, have over 120 patents. Dageville (PhD) spent 16 years at Oracle as an architect. Cruanes spent 13 years at Oracle focused on the optimization and parallelization layers in Oracle databases including as lead for the optimization group. Zukowski invented vectorized query execution for databases. His innovation emerged from his PhD research into optimizing database query execution for modern processors. These three legends have created a company that has currently has 250 petabytes under management, 1,300 partners, over 4,000 customers and $265M in revenue in 2020.

Since its release it has acquired close to 20% of the data warehouse market. It’s no wonder. Snowflake is built from the ground up to be unique and purely cloud-based. In this course we show you dozens of tips, tricks and demonstrations of cool things Snowflake can do. We cover numerous SQL tips and tricks. We cover cool features such as resource monitors, the amazing Web UI, generators, using Snowflake as a data lake (which you could, and should, be doing), analytical functions in Snowflake, monitors warehouse usage and so much more.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Snowflake User Interface (Web UI) Techniques

Lecture 1: A Quick Tour of the Web UI

Lecture 2: Finding Objects in Your Account and/or Database

Lecture 3: Getting Object information

Lecture 4: Executing SQL Statements

Lecture 5: Search and Replace

Lecture 6: Commenting Your Code

Lecture 7: Copying and Moving Code

Lecture 8: Query and Results History – Part 1

Lecture 9: Query and Results History – Part 2

Chapter 3: SQL Tips and Techniques

Lecture 1: Information_Schema

Lecture 2: Databases and Schemas

Lecture 3: Tables

Lecture 4: Table Constraints

Lecture 5: Columns

Lecture 6: Views

Lecture 7: Data Types

Lecture 8: User-defined Functions

Lecture 9: Users and the Result_Scan Function

Lecture 10: Users Never Logged In

Lecture 11: Query History

Lecture 12: Virtual Warehouses (Compute)

Lecture 13: Dates

Lecture 14: Converting Time zones

Chapter 4: Cool Features and Functions in Snowflake

Lecture 1: 10 Features That Make Snowflake Cool – Plus a Bonus 11th.

Lecture 2: Generators

Lecture 3: Using Snowflake as a Data Lake

Lecture 4: Data Masking

Lecture 5: Creating a Table from a Clone and Time Travel

Lecture 6: Resource Monitors

Lecture 7: Dropping and Un-dropping Objects

Chapter 5: Windowing Functions and Analytical Techniques

Lecture 1: Overview

Lecture 2: Rank

Lecture 3: Lead and Lag

Lecture 4: First and Last

Lecture 5: Ratio_To_Report

Lecture 6: Moving Averages

Lecture 7: Techniques for Percentiles

Lecture 8: Grouping Sets

Chapter 6: Miscellaneous

Lecture 1: Terminology Tips

Lecture 2: Parameters – A Technique for Controlling the Environment

Lecture 3: ListAgg

Lecture 4: The Qualify Function

Lecture 5: The ILIKE Function

Lecture 6: The HASH_AGG Function and Comparing Two Objects

Lecture 7: Killing a Session (Connection)

Lecture 8: Monitoring Warehouse Usage

Lecture 9: Date Extraction Confusion

Lecture 10: Convert a Permanent Table to Transient

Lecture 11: Generate a DDL Statement for an Object

Lecture 12: 20 Performance and Money-Saving Tips

Chapter 7: Test Your Knowledge

Lecture 1: Test Your Knowledge

Instructors

Randy Minder
Lead BI Developer / Power BI / Microsoft Fabric

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 20 votes
4 stars: 52 votes
5 stars: 78 votes

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