Snowflake Data Warehouse & Analytics Concepts

A live and interactive, step by step process for learning Snowflake.

Live Class: Friday, 21 Oct

Enrolled: 1

Duration: 36 Hours

Offered by: infyni

$749 60% off

$299

About Course

Snowflake is a cloud-based Data Warehouse.  The IT industry has seen a major shift over the years towards cloud computing because of its subscription-based and pay-per-use model. Data Warehouse is key to business intelligence and for getting better insight before taking strategic decision.

Snowflake is the only data warehouse built for cloud and is becoming increasingly popular over the years because it is faster, easier to use and far more flexible than traditional data warehouse offerings. Snowflake has already change the way we think about data warehouse.

This course is live and interactive for you to learn directly from industry veterans, and is a step by step process for learning Snowflake.

Skills You Will Gain

Business Intelligence Data Warehousing Expected Return Sap Hana

Course Offerings

  • Instructor-led interactive classes
  • Clarify your doubts during class
  • Access recordings of the class
  • Attend on mobile or tablet
  • Live projects to practice
  • Case studies to learn from
  • Lifetime mentorship support
  • Industry specific curriculum
  • Certificate of Completion
  • Employability Opportunity
  • Topics
  • Instructor
  • Creating Snowflake Account
  • Testing Snowflake
  • Introduction
  • Understanding the Web UI Components
  • Installing SnowSql
  • Using Command Line Interface
  • In-Dept Snowflake Architecture 2.0
  • DDL Commands Refresher
  • DDL Creating VW
  • DDL Create DB, Schemas
  • DDL Creating Materialized Views
  • DDL Alter, Drop Etc.
  • DML - Select Statements
  • DML - Operators
  • DML - Group By, Order By, Having Clause
  • DML - Joins, Right, Inner & Outer
  • Sub-query with From Clause, Where, Having Clause
  • Case Statements
  • Operators (UNION, UNION ALL, INTERSECT, Minus)
  • ABS, Ceil, Floor, Coalesce
  • String, Date, Time
  • System, Rollback
  • Bulk Loading DATA / Big Data
  • Data Load - Copy - Bulk Load
  • Apply transformation while Loading
  • Loading COMPRESSED file from AWS S3 to Snowflake
  • Additional Data Load and Transformations
  • Internal Stages
  • Types of Internal Stages (User, Table)
  • External Stages
  • Results Cache
  • Local Cache
  • Disk Cache
  • Creating Cluster Tables
  • Cluster Tables with expressions
  • Order By Clause
  • Manual re-clustering
  • Best practices in Micro-Partitioning and Clustering
  • Multi-Cluster Virtual Warehouses
  • Launching New Clusters
  • Using Dedicated Virtual Warehouses
  • Scale Out - Auto Scale
  • Query Management and Optimization
  • Concurrency Control
  • Establishing Secure Connection AWS-Snowflake
  • AWS Roles
  • Loading data to AWS S3 Buckets
  • Creating Table, External Stage Objects
  • File Format Objects
  • Creating INTERGATION Objects
  • CSV Data Loading from AWS to Snowflake
  • Parquet Data Loading from AWS to Snowflake
  • JSON Data Loading from AWS to Snowflake
  • Nested Data Loading from AWS to Snowflake
  • XML Data Loading from AWS to Snowflake
  • SNOWPIPES
  • Configure AWS S3 for Snowpipe
  • AWS Events
  • SQS Queue
  • Permanent Tables
  • Transient Tables
  • Temporary Tables
  • Set Data Retention Timings
  • Query Historical Data
  • Cloning Historical Objects
  • Time Travel for Data Recovery
  • Detailed Overview
  • Features by Snowflake
  • What is a Tree of Tasks?
  • Implement a Standalone Task
  • Stored Procedures using Tasks
  • Clone Database, Pipes, Streams, Tasks& Stages
  • Clone Schema & Tables
  • Cloning Table Storage Metrics
  • Cloning Using Time Travel
  • Swap Tables
  • Secure data Sharing
  • Sharing with other Snowflake users
  • Sharing with non-Snowflake Users
  • Snowflake Approach to Access Control & Key Concepts
  • Role Hierarchy in Snowflake
  • Connect Tableau with Snowflake
  • Connect Power BI with Snowflake
  • Creating Graphs and Chartsl
  • Best practices while doing clone.
  • Best practice while creating database and tables.
  • Best practice while using virtual warehouse.
  • Best practice while using retention period and time travel

...
Yogesh Agrawal
About Instructor

10+ years of experience in Business Intelligence domain with core experience in design and implementation of Data Warehousing and Data Integration Solutions.


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