Snowflake Data Warehouse

This is a live, online class taken by an industry expert. You will have the focussed attention of the trainer because group sizes are deliberately kept small. Doubts are cleared on the spot, assignments are discussed and any challenges are addressed.

Live Course

Live Class: Saturday, 21 Oct

Duration: 23 Hours

Enrolled: 4

Offered by: infyni


Live Course


Enrollment Closed Notify Me

About Course

Previously, big data stores were built by organizations in-house. Data engineers used open-source software, like Apache Hadoop to do this. But you needed a team of data engineers to develop and support this kind of a system. Plus, these specialists are in high demand and low supply.
Snowflake provides an enterprise solution that makes the gathering, processing, using big data easy. Its most remarkable feature is the ability to bring up an unlimited number of virtual warehouses. This makes it possible to run an infinite number of independent workloads against the same data without any risk of contention.

Six reasons you need to learn Snowflake :
1. Snowflake puts data warehousing onto the cloud, without locking customers into any vendor. Therefore, Snowflake is seen as a neutral vendor.
2. Snowflake separates compute and storage requirements, so you can scale them up or down independently. This allows greater flexibility.
3. Snowflake is a better platform to start and grow with because it is an overall easier software to approach.
4. It a relational database management system (RDBMS), which uses an SQL database engine designed for the cloud. And doesn’t work on top of an existing database.
5. Snowflake’s architecture enables data sharing among Snowflake users. This allows the provider to create and manage a Snowflake account for a consumer, say users.
6. You could experience concurrency issues (such as delays or failures) when too many queries compete for resources, in a traditional data warehouse. Snowflake on the other hand addresses concurrency issues with its unique multi-cluster architecture.

Skills You Will Gain

Snowflake Architecture Snow SQL DDL / DML SQL Command Snowflake SQL - Set Snowflake SQL - Functions & Transactions DATA Loading Micro-Partitioning and Clustering Virtual Warehouses Performance Tuning Snowflake Tables Time Travel Integrating Snowflake with Tableau Integrating Snowflake with PowerBI Snowflake Best Practices

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 (1)
  • Reviews
  • Introduction
  • Creating Snowflake Account
  • Testing Snowflake
  • 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
  • Subqueries, Case Statements
  • 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
  • Configure AWS S3 for Snowpipes
  • 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
  • SYSADMIN Roles
  • Custom Roles
  • Public Roles
  • Connect Tableau with Snowflake
  • Connect Power BI with Snowflake
  • Creating Graphs and Charts
  • 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
  • Python with Snowflake


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