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Snowflake

About The Course

Snowflake is a cloud based data platform provided as Software-as-a-Service (SaaS). Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings.

The Snowflake data platform is not built on any existing database technology or “big data” software platforms such as Hadoop. Instead, Snowflake combines a completely new SQL query engine with an innovative architecture natively designed for the cloud. To the user, Snowflake provides all of the functionality of an enterprise analytic database, along with many additional special features and unique capabilities.

Snowflake is a native Cloud Relational Database that is a Data Warehouse as a Service (DWaaS) solution. As a DWaaS, Snowflake handles all of the resource management, availability, configuration, authentication, data protection and optimization. All that is needed is to load and use the data! Snowflake is currently available on Amazon AWS and Microsoft Azure cloud platforms, and, as announced during the Snowflake Summit, will be available on Google Cloud Platform(GCP) in preview in Fall 2019. Snowflake has made connections extremely easy by partnering with many BI, Data Integration, and Advanced Analytical tools. It also provides ODBC, JDBC, Go, .Net. Node.js drivers, connectors for Python, Spark, and Kafka ,SNOWSQL CLI.

There are plenty of things to love about Snowflake, here are a few highlights:

Scalability: Since it is designed and built for the cloud, Snowflake fully leverages the elasticity to offer near infinite scalability. Also, since storage is decoupled from compute, they are independently scalable.

Flexibility: Being able to scale storage, compute, number of users quickly based on requirements and changing the size of a warehouse from a menu is so cool (pun intended)

Pay As You Use: Snowflake billing allows Pay per second and auto-suspend, auto-resume of the virtual warehouses so customers are not paying for “off” times when the warehouses are idle.

Data Cloning: Snowflake lets you clone datasets for say, QA without needing to store (and pay for) the entire dataset multiple times.

Secure Data Sharing: Snowflake lets you securely share read-only access to data with one or more consumers without having to transfer the data out of Snowflake. Note: During Snowflake Summit 2019, Snowflake announced the Data Exchange that provides a data platform for customers to easily and quickly acquire and leverage data from various data providers.

Infrastructure: Traditional data warehousing infrastructure can be time-consuming and expensive at the outset of a project whereas Snowflake customers do not even need AWS or Azure accounts.

SQL:  A language most folks who work with databases are already familiar with

Module 1: Cloud Computing Concepts

  • What is the "Cloud"?
  • Why cloud services
  • Types of cloud models
    • Deployment Models
    • private Cloud deployment model
    • public Cloud deployment model
    • hybrid cloud deployment model
  • Types of cloud services
  • Infrastructure as a Service,
  • Platform as a Service,
  • Software as a Service
  • Comparing Cloud Platforms
    • Microsoft Azure,
    • Amazon Web Services,
    • Google Cloud Platform
  • characteristics of cloud computing
    • On-demand self-service
    • Broad network access
    • Multi-tenancy and resource pooling
    • Rapid elasticity and scalability
    • Measured service
  • Cloud Data Warehouse Architecture
  • Shared Memory architecture
  • Shared Disk architecture
  • Shared Nothing architecture

Module 2: Core Azure services

  • Core Azure Architectural components
  • Core Azure Services and Products
  • Azure solutions
  • Azure management tools

Module 3: Security, Privacy, Compliance

  • Securing network connectivity
  • Core Azure identity services
  • Security tools and features
  • Azure Governance methodologies
  • Monitoring and reportingS
  • Privacy, compliance, and data protection standards

Module 4:Azure Pricing and Support

  • Azure subscriptions
  • Planning and managing costs
  • Azure support options
  • Azure Service Level Agreements (SLAs)
  • Service Lifecycle in Azure

Module 5: Azure SQL Database

  • Introduction Azure SQL Database.
  • Comparing Single Database
  • Managed Instance
  • Creating and Using SQL Server
  • Creating SQL Database Services.
  • Azure SQL Database Tools.
  • Migrating on premise database to SQL Azure.
  • Purchasing Models
  • DTU service tiers
  • vCore based Model
  • Serverless compute tier
  • Service Tiers
    • General purpose / Standard
    • Business Critical / Premium
    • Hyperscale
  • Deployment of an Azure SQL Database
  • Elastic Pools.
  • What is SQL elastic pools
    • Choosing the correct pool size
  • Creating a New Pool
  • Manage Pools
  • Monitoring and Tuning Azure SQL Database
  • Configure SQL Database Auditing
  • Export and Import of Database
  • Automated Backup
  • Point in Time Restore
  • Restore deleted databases
  • Long-term backup retention
  • Active Geo Replication
  • Auto Failover Group

Module 6: Getting Started With Snowflake

  • Planning
    • Deciding on a snowflake edition
    • Choosing a cloud provider and region
    • Examining snowflake’s pricing model
    • Examining Types of snowflake tools
  • Creating a snowflake account
    • Technical requirements creating a new snowflake instance
    • Using snowsql to connect to snowflake
    • Creating a tailored multi cluster virtual warehouse
    • Using snowflake wbUI and executing a query
  • Connecting to snowflake
    • Logging into the snowflake web interface
    • Touring the web interface

Module 7: Building A Virtual Warehouse

  • Over view of snowflake virtual warehouse
    • warehouse sizes and features
    • Multicluster virtual warehouse
  • Virtual warehouse consideration
    • Query design
    • Caching impacts
    • Scaling
  • Building a snowflake virtual warehouse
    • Creating a virtual warehouse
    • Starting, Resuming, Suspending, and Resizing

Module 8: Working With Snowsql

  • Installing snowsql
  • Configuring snowsql
    • Connection settings
    • Configuration variables
  • Snowsql commands
  • Multiple connection names
  • Data loading with snowsql

Module 9: Snowflake Administration

  • Administering roles and users
    • Enforcement model
    • Working with roles and users
  • Administering resources consumption
    • Virtual warehouse usage
    • Data storage usage
    • Data transfer usage
  • Administering databases and warehouses
    • Managing warehouses
    • Managing databases
    • Zero-copy cloning
  • Administering account parameters
  • Administering databases objects
  • Administering data shares
  • Administering clustered tables
  • Snowflake materialized views

Module 10 : Snowflake Security Overview

  • Snowflake security references architecture
    • Virtual private cloud
    • Physical security
    • Network and site access
    • Account and user authentication
    • Object security
    • Security validation
    • Snowflake audit and logging
    • Penetration testing

Module 11: Working With Semistructured Data

  • Supported file formats
  • Advanced data types
  • Working with XML
  • Working with JSON
  • Working with AVRO
  • Working with parquet

Module 12: Secure Data Sharing

  • Secure data sharing
  • Secure table sharing
  • Data sharing using a secure view

Module 13: Snowflake And Data Science

  • Snowflake and the analytics ecosystem
  • Snowflake and Apache spark
  • connector for Apache spark
  • Working with Databricks

Train your teams on the theory and enable technical mastery of cloud computing courses essential to the enterprise such as security, compliance, and migration on AWS, Azure, and Google Cloud Platform.

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