Snowflake - Dynamic Table Masterclass & E2E Data Pipeline

What you'll learn
Understand The Challenges with Stream & Task And Future of Declarative Pipeline
Understand the purpose of Snowflake Dynamic Tables and Its Lifecycle
Master all the dynamic table fundamentals & advanced topics
What are the difference between Dynamic Tables & Stream/Task Objects
What are the limitations of Snowflake Dynamic Tables
How to implement a data pipeline & DAG using Snowflake Dynamic Tables
What are the difference between Dynamic Tables & Materialized Views
Requirements
Working knowledge with Snowflake Cloud Data Warehouse
Fundamental understanding of Snowflake stream Objects.
Fundamental understanding of Snowflake Task Objects.
Fundamental understanding of SQL Queries Using Snowflake
Description
Embark on an exciting journey into the world of Snowflake Dynamic Tables with our comprehensive hands-on course designed for snowflake data developers. This course is your key to mastering the construction of declarative data pipelines, providing you with the skills to streamline development processes and minimise object requirements.Explore the intricacies of Dynamic Tables and unlock their intelligent capabilities in determining whether data loading should follow a full or incremental approach. Through engaging hands-on tutorials, we delve into every aspect of Dynamic Tables, shedding light on operational metrics that make it an indispensable native object within the Snowflake ecosystem.This course is your gateway to answering critical questions such as:What is Dynamic Table in Snowflake?How to construct a continuous data pipeline declaratively in Snowflake.Challenges faced in building end-to-end data pipelines using stream and task objects.How Dynamic Tables identify whether data loading should be incremental or full.Understanding lag metrics in Dynamic Tables.Building a Directed Acyclic Graph (DAG) using Dynamic Tables.Support for cloning, time travel, data sharing, and stream features in Dynamic Tables.Join us on this transformative learning experience, where you'll not only find answers but gain the expertise to unlock the full potential of dynamic table development. Get ready to elevate your Snowflake skills and create efficient data pipelines. Enrol now for an immersive learning adventure! #SnowflakeDynamicTables #DataPipelineMastery
Overview
Section 1: Snowflake Dynamic Table Introduction
Lecture 1 Snowflake Dynamic Table Introduction & Declarative Pipeline Concept
Lecture 2 Prerequisite For This Course
Lecture 3 How To Access The SQL Scripts & Data Files
Lecture 4 What To Expect From This Snowflake Dynamic Table Master Class
Section 2:[Optional] Snowflake Widely Used Native Objections
Lecture 5 Introduction - Common Used Snowflake Native Objects
Lecture 6 What Is Snowflake Stage Object & How It Works
Lecture 7 What Is Snowflake File Format Objects & Query External Stage Using It
Lecture 8 What is Snowflake Sequence Object & How To Use Them
Lecture 9 What is Snowflake Stream Object & How Does It Track Changes
Lecture 10 What is Task and Task-Tree & How to Create a DAG Using Task Tree
Lecture 11 Quickly Understand The Common Table Expression
Lecture 12 Quickly Understand Window Function
Section 3: End To End Data Pipeline Requirement In Snowflake
Lecture 13 What Is End To End data flow
Lecture 14 Different Orchestration Options
Lecture 15 Challenges With Stream & Task As Orchestration Tool
Section 4: Build Data Pipeline (DAG) Using Stream/Task Object
Lecture 16 End To End Continuous Data Flow Objective
Lecture 17 Understand The Data (Customer & Order) Set
Lecture 18 Create Database & Schema Objects
Lecture 19 Data Loading Objective & Data Statistics
Lecture 20 Load Country Specific Customer/Order Data Set & Query Them
Lecture 21 RAW Schema Objective
Lecture 22 Continuous Data Ingestion To RAW Schema Layer & Task Tree
Lecture 23 CLEAN Schema Objective
Lecture 24 Continuous Data Ingestion To Clean Layer
Lecture 25 CONSUMPTION Schema Objective
Lecture 26 Continuous Data Ingestion To Consumption Layer
Lecture 27 Activate Pipeline Objective
Lecture 28 Resume Task & Monitor Continuous Customer/Order Data Flow
Lecture 29 Additional Continuous Data Load Objective
Lecture 30 Load Additional Customer/Data, Check Continuous E2E Flow & Monitor Progress
Lecture 31 Task Progress Tracking & Challenges
Lecture 32 Summary - Data Pipeline Using Stream/Task & Challenges
Section 5: All About Snowflake Dynamic Table & How To Build Pipeline Declaratively
Lecture 33 Introduction - What Is Covered In This Section
Lecture 34 Understand The Sample Data Set
Lecture 35 Load Data Set To Internal Stage Location
Lecture 36 Auto Ingest Using Task & Copy Command
Lecture 37 Create Our First Dynamic Table
Lecture 38 Update/Delete Operation On Underlying Table & Impact on Dynamic Table
Lecture 39 Dynamic Table On Stage Location & On Materialized View
Lecture 40 Alter Dynamic Table Paramters
Section 6: Dynamic Table On Multiple Tables
Lecture 41 Understand The Sample Data
Lecture 42 Ingest Data Using Task & Copy Command
Lecture 43 Create Dynamic Table On Multiple Tables
Lecture 44 Downstream Lag
Section 7: End To End Data Flow Using Dynamic Table (Customer/Order Example)
Lecture 45 Create Database & Schema For Dynamic Table E2E Flow
Lecture 46 Load Data Into Stage Location & Auto Ingest Using Task/Copy Objects
Lecture 47 Create Dynamic Tables For Clean Layer
Lecture 48 Create Dynamic Table For Consumption Layer
Lecture 49 Load Additional Data To Continuous Data Flow
Lecture 50 Increment Load Vs. Full Load Scenario
Section 8: Important Dynamic Table Features
Lecture 51 Introduction - Important Dynamic Table Features
Lecture 52 Dynamic Table Activity & Summary Dashboard (Snowsight WebUI)
Lecture 53 Dynamic Table Cost Calculation
Lecture 54 Dynamic Table & Cloning Support
Lecture 55 Dynamic Table & Time Travel Support
Lecture 56 Dynamic Table & Support For Stream Objects For Change Data Capture
Lecture 57 Dynamic Tables & Sharing Capabilities
Lecture 58 Dynamic Table & Table Functions For Run History
Section 9: Quick Dynamic Table Summary
Lecture 59 Dynamic Table & Course Summary
Snowflake Cloud Data Developer,Snowflake Cloud Data Engineer,Snowflake Cloud Data Architect,Snowflake Data Engineer


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